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Delivering on the Dividend Promise: Dynamic Dividend Behavior and Managerial Incentives*
Anzhela Knyazeva†
New York University
This version: August 2006
Previous version: May 2006
Abstract This paper examines the effect of governance and managerial alignment on dynamic dividend behavior of managers. I use a novel empirical approach to provide evidence on the role of governance and managerial alignment in explaining variation in dividend smoothing, incremental dividend decisions, and dynamic dividend behavior. Managers subject to weak monitoring and misaligned incentives are under greater pressure from shareholders to honor the implicit dividend contract as a trade-off between current period’s private benefits and future job security. The main finding is that weak board quality and institutional investor monitoring, CEO characteristics associated with misalignment, and greater separation of ownership and control rights in dual class firms contribute to stronger adherence to the implicit dividend contract, avoidance of dividend cuts and omissions, and non-decreasing persistent dividend path. Misaligned managers are also more likely to raise dividends and use dividend increases as the primary form of additional payouts. Methodologically, this paper contributes to the dividends and governance literature by identifying and addressing endogeneity of managerial alignment and dividend behavior in the instrumental variables framework and adjusting for selection bias.
JEL classification: G30, G34, G35 Keywords: dynamic dividend behavior, dividend smoothing, incremental dividend decisions, corporate governance, endogeneity, instrumental variables, selection model.
* I am thankful to my advisers Kose John, Joseph Stiglitz, Daniel Wolfenzon, David Yermack, and Bernard Yeung for valuable comments and discussions and William Greene, Eli Ofek, Anthony Saunders, and Jeffrey Wurgler for helpful suggestions. The title of the earlier version of the paper was “Delivering on the Dividend Promise: Managerial Incentives, Dividend Smoothing, and Incremental Dividend Decisions”. I am grateful to Paul Gompers, Joy Ishii, and Andrew Metrick for providing the data on dual class shares and to the Institutional Shareholder Services for providing the Corporate Governance Quotient data. I thank Stern School of Business for financial support. All errors and omissions are mine. † Stern School of Business, New York University. 44 West Fourth St., Ste. 7-177, New York, NY 10012. E-mail: aknyazev@stern.nyu.edu.
1. Introduction Dividends remain a puzzle for the corporate finance literature. A significant number
of firms continue to pay dividends despite their cost. Further, dividend cuts are infrequent
and only used as a last resort. Various approaches seek to explain differences in firm
dividend policies, including agency, information asymmetry and signaling, taxes. However,
with much of the focus on cross-sectional variation in dividend levels and incidence, there is
a need for a systematic examination of differences in dynamic dividend behavior.
This paper bridges this gap and contributes in the following ways to the existing
literature. First, it offers evidence on the effects of managerial alignment and governance on
dynamic dividend behavior of managers. The focus of this paper is on managerial decision
making, whereby dynamic dividend behavior arises as the outcome of fulfillment of the
implicit dividend contract between the manager and shareholders. The testable implications
address several understudied aspects of dividend policy: differences in firm propensity for
dividend smoothing, explanation of incremental dividend decisions and dynamic dividend
behavior, role of dividend changes in incremental payout policy decisions. The main result of
the paper is that misaligned managers face greater pressure to uphold an implicit dividend
contract with shareholders and choose to deliver on their dividend promise by maintaining a
smooth non-decreasing dividend path. Misaligned managers attain this through more
persistent dividends, avoidance of cuts and omissions in incremental dividend decisions,
smaller magnitude of dividend decreases and use of dividend increases, reliance on
repurchase decreases in downward payout policy revisions and preference for dividends
during payout increases.
Second, the paper employs a novel empirical approach to examine the relation
between alignment and dividend behavior. The analyses identify and address endogeneity of
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alignment and governance to dividend behavior. To the best of the author’s knowledge, this
is the first paper on dividends and governance to empirically evaluate the issue of causality
and implement the instrumental variables framework. New instruments, reliant on the
emergence of governance as the outcome of shareholder demand and managerial resistance
to shareholder pressure, are constructed and tested for validity. The paper contributes two
other empirical improvements: correction for selection bias and new measurement of
managerial alignment. The analyses correct for selection bias in coefficient estimates that
stems from non-random assignment of firms to the subsample of existing dividend payers
using a two-stage selection model. The paper also constructs new measures of internal
monitoring and the Alignment / Governance Index (AGI) to test the hypotheses. Empirical
analyses use measures of external governance, board monitoring quality, institutional
investor monitoring, CEO alignment characteristics, and separation of cash flow and voting
rights from managerial ownership in dual class firms on a large panel of US firms.
The main predictions of the paper regarding dividend behavior rely on decision
making of rational self-interested managers faced with a dynamic tradeoff. The manager’s
decision to honor the implicit dividend contract with shareholders depends on the immediate
benefit of forgoing a dividend payment and the expected future loss due to shareholder
disciplinary response. The immediate benefit consists of greater flexibility and/or more
private benefits. The future shareholder disciplinary response can include an increase in
scrutiny and disciplinary pressure, stock sales resulting in reduction in the value of
compensation and increase in the cost of capital, or firing (through a successful hostile
takeover or forced turnover). The extent of the shareholder disciplinary response to failure to
deliver on the dividend promise depends on the misalignment of managerial and shareholder
incentives.
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On the one hand, aligned managers deviating from the promised level of dividends
are believed to make value-increasing decisions that increase the expected return on
investment. Therefore, as long as the manager can provide a high return, managerial
deviations from the implicit dividend contract do not cause an increase in shareholder
disciplinary pressure. Shareholders accept a less persistent dividend path with potential for
cuts and omissions when managers are aligned and governance is strong.
On the other hand, misaligned managers (in the presence of weak board quality, a
lack of institutional investor scrutiny, CEO characteristics consistent with misalignment, and
dual classes of shares) that deviate from the implicit dividend promise are believed to invest
suboptimally and destroy firm value. Shareholders subject misaligned managers that fail to
honor the dividend promise to greater disciplinary pressure. As a result, misaligned managers
find it optimal to be more ‘committed’ to the implicit dividend contract in setting the
dynamic path of dividend. Conditional on having made a dividend promise, misaligned
managers show more persistence in dividends, avoid cuts and omissions, exhibit a smaller
magnitude of decreases, and are overall reluctant to compromising the implicit dividend
contract in payout policy decisions.
The proposed explanation is consistent with observed variation in dividend
smoothing, direction and magnitude of dividend changes, and choice of the form of cash
distribution increase.
The rest of the paper is organized as follows. The second section formulates the main
hypotheses. The third section discusses data, variables, empirical methodology and
instrument construction. The fourth section presents empirical results. The fifth section
concludes and outlines questions for future research.
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2. Hypothesis development
Managerial objective and dynamic tradeoff
Agency costs of inefficient investment in projects that increase firm size, diversify
risk or otherwise enhance private utility of the manager lower firm value, as was suggested
by Jensen and Meckling (1976) and in subsequent work. The level of private benefits and
inefficient investment in a given period is higher for poorly monitored managers and
managers with misaligned incentives. The formulation of the problem is practically
unchanged if inefficient investment is instead associated with suboptimally low level of
privately costly managerial effort.
From the shareholder perspective, a significant loss of firm value due to inefficient
investment can be prevented through costly firing and replacement of the current manager.
Alternatively, from the perspective of a potential raider, a drop in market value of the firm
due to inefficient investment will render a takeover more attractive (the cost of takeover
weighed against gain from turning around the firm). Both in the case of forced turnover and a
successful takeover, the manager’s job security, i.e. the likelihood of remaining in the firm
next period, is decreased. The manager has a negative expected utility from being fired. It is
plausible that expected future income of a fired manager is lower than that of a manager who
kept the job. Performance-based firing can weaken managerial reputation, lower expected
future wages and impose costs of job search. In the worst case scenario, the fired manager is
not re-hired and loses the entire stream of expected compensation and private benefits from
future periods.
Therefore, the manager’s suboptimal behavior in a given period affects two
components of expected lifetime utility: first, it directly increases current period’s private
benefits; second, it decreases expected future compensation and private benefits through
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increasing the probability of firing. In other words, the incumbent manager faces a dynamic
tradeoff between current period’s private benefits and future job security.
Managerial incentive to uphold a dividend promise
The described dynamic tradeoff explains managerial actions that may further
shareholder interests in order to alleviate monitoring pressure and increase job security. In
related work, Fluck (1999) models managerial choice of the distribution of equity ownership
that maximizes private benefits against the risk of potential control threats (see also Zwiebel,
1996). John and Knyazeva (2005) argue that design and composition of payout policy
(specifically, the presence of dividends versus repurchases) can serve as a form of pre-
commitment in firms with bad corporate governance.
The interest of this paper is managerial choice of characteristics of dynamic dividend
path - extent of dividend smoothing and incremental dividend decisions – and the effect of
misaligned incentives on the likelihood of delivering on the dividend promise to
shareholders. An imperfectly aligned manager will set firm dividend policy to achieve an
optimal tradeoff between current period’s private benefits and probability of keeping the job
next period. Poorly monitored managers are able to derivate greater private benefits from
suboptimal investment out of free cash flow, resulting in a more severe agency problem and a
larger loss in firm value. In order to mitigate the loss of firm value (and the corresponding
increase in the probability of firing), a misaligned manager can limit the amount of private
benefits by agreeing to disburse cash to shareholders and making a dividend promise. John
and Knyazeva (2005) document higher levels of dividend payout among poorly governed
firms, so this paper does not focus on the initially promised dividend amount. Instead it
examines period-by-period behavior of misaligned managers related to continuing or
modifying dividend policy and dividend smoothing, conditional on a past dividend promise.
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Dividend policy credibly restricts suboptimal behavior of a misaligned manager only
if it implies regular payouts that are not arbitrarily decreased by the manager. Shareholders
rationally expect a misaligned manager to invest inefficiently. Controlling for other factors
(change in the cost of dividends to the firm and extent of the free cash flow), deviations from
the dividend promise will be attributed to increases in managerial private benefits. When a
misaligned manager cuts or omits a dividend payment, shareholders will respond with a
stronger negative market reaction on announcement, which imposes additional monitoring
and reputation costs and can potentially result in firing. Therefore, misaligned managers face
a greater need to uphold the dividend promise they made. Similarly, shareholders expect
misaligned managers to increase the promised dividend in response to an increase in
internally generated firm cash flow or a decrease in investment opportunities.
On the other hand, when a promise of dividends is made by a better aligned manager,
the shareholders are more flexible with respect to deviations from the dividend contract.
Incremental dividend decisions that lower the promised dividend level are optimal for the
firm if the efficiency of allocation of internal cash flow is improved and expected return on
investment is increased as a result. A better aligned manager’s decision to deviate from the
dividend contract is more likely to be due to an increase in expected future investment
opportunities or a decrease in expected internal cash flow rather than to an increase in
managerial private benefits. Shareholders rationally anticipate this and accept less persistent
dividends and a larger likelihood of downward changes. In exchange, they require a higher
expected return on investment. Therefore, better incentive alignment allows the manager to
have more flexibility with dividend policy without sacrificing firm value and, respectively,
job security.
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The proposed argument yields several new empirical predictions about the effect of
incentives on dividend policy implementation in the context of individually optimal
managerial behavior. In particular, the paper examines the issues of dividend smoothing,
incremental dividend changes (dividend cuts, omissions and increases), use of dividends to
distribute additional cash to shareholders.
Managerial alignment and dynamic dividend behavior: hypotheses
Dividend smoothing
As was argued above, misaligned managers face greater pressure from shareholders
and the stock market to uphold the dividend promise. Incentive misalignment implies that
shareholders rationally anticipate less efficient investment and lower expected future returns.
In order to mitigate the ensuing shareholder pressure and threat of firing, a misaligned
manager can make a credible dividend promise to indicate commitment not to destroy
shareholder value. The market’s demand for a credible dividend promise by the manager is
increasing in the degree of incentive misalignment. The manager can make a more credible
dividend promise by undertaking regular and persistent dividend payments. Greater dividend
persistence (dividend smoothing) implies that a restriction on managerial behavior is
consistently upheld over time.
For better aligned managers, high expected return on investment is more important for
addressing shareholder pressure and the threat of firing while a credible dividend promise
contributes relatively less value since the cost of suboptimal managerial behavior is mild.
Existing empirical evidence (see, e.g., Benartzi, Michaely, and Thaler, 1997; Grullon,
Michaely, Benartzi, and Thaler, 2005) indicates that dividends do not carry additional
signaling power about unexpected changes in future firm earnings. Therefore, better aligned
managers will be able to mitigate the threat of firing more effectively by improving earnings
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and firm value directly rather than adhering to a restrictive dividend promise. In addition,
better aligned managers can conserve firm resources and improve efficiency of allocation of
firm cash flow by opting for a more flexible (less persistent) dividend policy. More frequent
deviations from the established dividend level, including downward adjustments, are optimal
for better aligned managers and their shareholders. The presented argument is summarized in
the Hypothesis H1 below.
H1. Misalignment of managers increases dividend smoothing (persistence). Managerial misalignment reduces dividend variability.
In examining dividend smoothing, this paper relates to existing literature that
documents a high degree of dividend persistence for the full sample of firms (see, e.g.
Lintner, 1956; Fama and Babiak, 1968). In subsequent theoretical work, Kumar (1988)
develops a model of coarse dividend signaling of firm productivity type that is consistent
with smoothing. Warther (1994) derives dividend smoothing predictions in an asymmetric
information game between shareholders and management, in which managers must pay a
dividend sufficient to demonstrate adequate profitability. Fudenberg and Tirole (1995)
provide a different theory of dividend and earnings smoothing based on managerial job
security. In more recent work, Dewenter and Warther (1998) perform a comparison of
dividend decisions of US and Japanese companies and find higher dividend persistence and
lower probability of cuts and omissions in the US. Gugler (2003) uses Austrian data and
finds that state-controlled firms are most reluctant and family-controlled firms are least
reluctant to cut dividends when cuts are expected.
Contributing to the existing literature, this paper explains differences in dynamic
dividend behavior through misalignment of managerial incentives, controlling for
information environment of the firm, risk and other factors. It also employs instrumental
variables framework to endogenize managerial incentives (will be discussed in Section 3.).
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Since consistency of dividend payments over time is essential to restraining managerial
opportunism, the empirical findings on this issue provide new insights about the
endogenously determined effectiveness of dividends as an agency cost reduction mechanism
for poorly monitored managers.
Incremental dividend decisions: dividend cuts and omissions
The previous hypothesis suggests that a misaligned manager can succeed at making a
more credible dividend promise if dividend payments are persistent over time. The second
question is how dividend smoothing is implemented by misaligned managers, provided
Hypothesis H1 holds. Analysis of incremental dividend decisions focuses on changes
(increases and decreases, including omissions) of dividend payments.
By exposing the manager to monitoring from the external financing market, a
persistent dividend policy mitigates the problem of inefficient investment and private benefit
consumption. Therefore, dividend decreases by a misaligned manager represent departures
from the promised level of additional monitoring assumed by the manager, controlling for
other effects. Shareholders perceive downward deviations from the promised dividend level
as a misaligned manager’s attempt to increase private benefits at a cost to firm value.
Therefore, dividend smoothing is implemented through avoidance of dividend cuts and
omissions, i.e. protection against downward changes in the promised dividend level.
H2. Misaligned managers avoid dividend cuts and omissions.
Hypothesis H2 suggests that incentive alignment is negatively related to the likelihood
of dividend decreases and negatively related to dividend changes (more negative changes
undertaken by better aligned managers). Combined, hypotheses H1 and H2 predict a
persistent, non-decreasing dividend path for misaligned managers.
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The other implication of this argument is that dividend cuts by misaligned managers
would encounter a more negative market reaction (discussed in Section 4.).
Incremental dividend decisions: dividend increases
The next issue is likelihood of dividend increases by misaligned managers. The earlier
argument implies that better aligned managers are as likely or less likely to increase the
promised dividend level since they do not realize significant gains in job security from
committing a higher amount to dividend payments. For misaligned managers, two
possibilities arise. We will use empirical tests of the likelihood of changes to distinguish
between them.
On the one hand, the promised dividend can be maintained at a high constant level that
imposes a significant constraint on managerial behavior and additional monitoring from the
external financing market. The credibility of the dividend promise is attained through
avoidance of decreases. In this instance, the manager may not want to increase dividends
since a one-time increase will have to be reflected in higher subsequent dividend payments.
If later on a manager is not able to continue these higher dividend payments, a dividend cut
announcement would send a negative signal to the shareholders, which could increase the
threat of firing, contradicting the initial objective of dividend use – to mitigate the
shareholder pressure and firing threat. Therefore, misaligned managers are as likely as better
aligned managers to increase dividends.
On the other hand, a stream of dividends that is strictly increasing over time could be
consistent with the proposed argument. Initially, misaligned managers set dividends at the
moderate initial level sufficient to maintain a credible constraint on managerial behavior.
Since some uncertainty over future free cash flow is present and decreases in dividends are
costly to the manager, the manager realizes expected gains from waiting until next period, i.e.
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retaining the option not to increase the dividend in the future. If the firm’s cash flow
continues to be high or is expected to increase, the misaligned manager can signal a renewed
commitment to uphold shareholder interests by raising the dividend. However, if the firm’s
cash flow does not increase or decreases, the manager can avoid the cost of announcing the
cut of a dividend that had been set at a high level earlier. Therefore, after setting the initial
dividend level, a misaligned manager will either sustain it or increase it, depending on
information about expected future cash flow. Retaining this control over dividend path
enables the manager to supply only positive signals to the market in order to improve job
security. A further consideration is that the optimal dividend change following an increase in
free cash flow (and not only the initial dividend level) depends on the extent of managerial
misalignment. Managerial misalignment raises the magnitude of the dividend increase that is
necessary to maintain the previously established level of constraint following an increase in
free cash flow. Therefore, in this context misaligned managers are overall more likely to
announce a dividend increase.
H3. Dividend increases are non-decreasing in managerial misalignment
The exact sign of the relation between weak incentives and dividend increases
(insignificant or positive) depends on which of the two explanations above holds and will be
identified empirically.
Dynamic dividend behavior: changes in dividend level
The previous discussion of hypotheses about incremental dividend decisions allows the
following characterization of dynamic dividend behavior conditional on managerial
alignment:
H4. Aligned managers undertake lower dividend changes. Managerial misalignment/weak governance causes higher dividend changes.
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Managerial misalignment, including in instances of weak governance, is associated
with upward pressure on managers in the determination of dynamic dividend path. Aligned
managers face less upward dividend pressure and enjoy greater flexibility over downward
deviations from the previously committed dividend level. Managerial behavior described
above is consistent with individually optimal decision-making of the rational manager in the
framework of implicit contracting. In the present context, a previously announced level of
dividends is interpreted as an implicit dividend contract with shareholders. Whether
managers continue to ‘deliver on the promise’ of dividend payments (and are subjected to the
pressure to expand dividend payments over time) is determined by the amount of discretion
that the manager can retain and shareholders are willing to concede with respect to the
dividend policy given the firm’s investment opportunities, cash flow, and, importantly,
managerial alignment and governance quality. Up to this point, the discussion has focused on
the amount of pressure exerted by shareholders in the presence of managerial misalignment
or weak governance mechanism since misaligned managers are believed not to be guaranteed
job security. Besides threatening managerial job security, which is the most direct
implication of the previous argument, shareholders can resort to other channels of exercising
disciplinary pressure over a deviating manager. The ensuing negative effect of sale of shares
(‘voting with their feet’) on stock price can have other consequences than facilitating an
unfriendly takeover offer or board-initiated turnover. Even if allowed to remain in the firm,
the deviating manager can experience lower expected earnings from stock compensation.
Further, a drop in stock price would have a detrimental effect on the cost of capital, should
the firm require external financing, which would lower profitability and/or scope of
accessible projects and lower potential for extraction of private benefits in the future.
Use of dividend changes in payout policy revisions
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Previous predictions characterize dynamic dividend behavior, including persistence,
variability, magnitude and direction of changes. However, incentive misalignment can also
affect the bigger picture of dynamic payout policy. Supplementing the previous argument,
the next hypothesis focus on the following question: when would dividend change be the
preferred choice in payout policy revision? Both increases and decreases will be considered.
Adhering to the baseline dynamic dividend behavior argument, a misaligned manager
would benefit from choosing dividends as the form of payout increase due to higher
shareholder confidence and job security realized as a result of the added disciplining effect of
having to sustain higher future dividends. The cost of the dividend increase (that makes a
misaligned manager’s action more credible) is the need to sustain payout at a higher level in
the future. Alternatively, the manager can make a one-time repurchase instead of distributing
the increase over time in the form of a higher dividend. A large temporary cash distribution
will have a weaker disciplining effect on the manager since no continued effort to follow a
new payout path is necessary but can distribute the same amount of additional cash to
shareholders. In addition to a weaker disciplinary effect, information effects associated with
repurchases can also interfere: for instance, a misaligned manager may be able to time the
repurchase to inaccurately supplied information about firm performance in an attempt to
exploit the advantage over uninformed investors, which would lower the positive effects of a
repurchase. The author believes that the relatively stronger disciplining effect of a dividend
increase is the main reason for the preference of misaligned managers towards dividend
increases.
H5a. Misaligned managers choose to use dividend increases as the form of distributing additional cash payouts.
When downward payout policy decreases become necessary, dividend decreases are
expected to be the least preferred choice of misaligned managers. Provided that alignment
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and governance quality remain weak, a downward payout policy revision that does not cause
a deviation from the implicit dividend contract will prevent a strong disciplinary response on
the part of shareholders. Therefore, a misaligned manager is more likely to scale down the
volume of repurchases rather than announce a dividend cut or omission.
H5a. Misaligned managers prefer to use repurchase decreases (not accompanied by dividend decreases) as the form of payout decrease.
The next section describes data, construction of variables, and empirical methodology.
3. Data and empirical methodology
Empirical analyses in this paper focus on the sample of U.S. firms. Data on firm
characteristics is obtained from Compustat Industrial Annual for 1992-2004. The sample
excludes financial firms (SIC codes 6000-6999) and regulated utilities (SIC codes 4900-
4949). We also omit observations with missing data on book value of total assets (item #6),
firms with asset size below 20 mln, firms incorporated abroad (incorporation code 99), LBOs
(Compustat stock code 4). CRSP monthly file contains information on cash distributions. We
include only ordinary common shares. Certificates, ADRs, shares of beneficial interest, and
units are excluded. We also omit data points corresponding to Americus trust components,
closed-end funds, and REITs. Dividends are defined as the sum of distributions with
distribution code 1232 (ordinary quarterly cash dividends) over four fiscal quarters, adjusted
for splits and stock dividends, to form annual dividend level.
Managerial Alignment
In empirical tests misalignment of managerial incentives is captured through firm
governance characteristics that weaken the scope and intensity of scrutiny of managerial
actions or lower the likelihood of punishment for inefficient behavior and through firm and
CEO characteristics that broaden the gap between managerial and shareholder utilities.
Existing governance literature emphasizes the role of monitoring mechanisms for firm
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performance and decision making, including charter and bylaw provisions that increase
exposure to the market for corporate control (Gompers, Ishii, Metrick, 2003; Bebchuk and
Cohen, 2004), monitoring by a large blockholder (Cremers and Nair, 2005), independence of
the board of directors (Agrawal and Knoeber, 1996), small board size (Yermack, 1996). John
and Knyazeva (2005) empirically identify the link between external and internal governance
mechanisms, payout policy design and dividend behavior.
External governance measure is based on the Gompers, Ishii, and Metrick (2003)
index of takeover defenses. Managers in firms with fewer takeover defenses are exposed to
the market for corporate control and are therefore subject to sufficient discipline without
upholding the implicit dividend contract. More generally, the provisions that comprise the G
index can be said to influence the decision making process in the firm that takes the
bargaining power away from insiders and facilitates independent oversight of the CEO.
The remaining alignment measures involve intensity of institutional investor
monitoring, quality of board monitoring, CEO-level alignment characteristics. These four
characteristics are used together with the Gompers, Ishii, Metrick (2003) external governance
measure to form the Alignment/Governance Index (AGI) that captures various aspects of
managerial misalignment (due to weak external governance, weak internal board or
institutional blockholder monitoring, CEO characteristics consistent with shorter horizon or
stronger entrenchment in the firm, and agency conflict due to separation of ownership and
control rights) and therefore serves as an inclusive determinant of the extent of shareholder
pressure on the manager with respect to the implicit dividend contract. The construction of
the AGI variable and its components is described in Appendix A; for the purposes of the
index, rankings of firms by characteristics believed to be associated with better alignment are
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rescaled to [0,1] and used instead of the absolute values. All key results are checked against
both AGI and five component measures of alignment.
Institutional investor monitoring is expected to be stronger in the presence of a larger
blockholding in the firm3. Further, the higher concentration of institutional ownership and the
lower number of institutional owners would decrease the costs of coordination and improve
the intensity of scrutiny of managerial actions. Finally, some categories of institutional
owners are expected to be more active in monitoring the manager; for this purpose, proxies
are constructed for public pension fund participation in the firm. In sum, managers in firms
with an institutional blockholder and public pension fund investor, larger and more
concentrated institutional ownership, and fewer institutional owners are expected to have less
severe incentive alignment problems. The quality of board monitoring is expected to increase
with independence of directors (and decrease with presence of employee directors), decrease
with board size (see Yermack, 1996), decrease with the introduction of the CEO on key
committees (nominating, compensation, audit, governance; see Shivdasani and Yermack,
1999) and increase with the frequency of board meetings. Certain CEO characteristics are
expected to increase misalignment. First, length of CEO tenure in the firm could indicate the
level of control (bargaining ability) the CEO has over the board and ability to resist
oversight. Second, CEO age could be associated with a shorter horizon in the firm, indicating
potentially higher discrepancy with the profit maximization objective of shareholders.
Presence of dual class shares is expected to be associated with greater separation of control
and cash flow rights of the manager, as in Gompers, Ishii, Metrick (2005), and weaker
alignment of manager and shareholder interests.
Control variables
3 Amihud and Li (2002) argue that a lower degree of information asymmetry between management and institutional owners is the underlying reason for the negative relation between institutional ownership and dividend payout.
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The measures described above characterize various dimensions of monitoring that
restrict a manager’s potential to derive private benefits. The other important part of the
manager’s objective is the strength of ownership incentives. Existing literature uses CEO
ownership stake. Fenn and Liang (2001) find that managerial ownership is positively
associated with payout in firms with low management stock ownership and few investment
opportunities. Further, stock option compensation is an increasingly important component of
executive pay and presence of stock options has been found to limit use of dividends (Fenn
and Liang, 2001). Data on the ownership stake of the CEO in the firm and CEO stock option
grants is obtained from Execucomp (where the series starts from 1992).
Other characteristics that could be correlated with dividend decisions and managerial
incentives are included. One should note that all managerial dividend choices are conditional
on the availability of cash flow and investment opportunities, therefore the level of cash flow
and firm investment opportunities is used to capture the extent of the free cash flow problem.
Firm size is expected to be positively related to dividends (Fama and French, 2001). Hoberg
and Prabhala (2005) examine the negative effect of risk on dividends, and Jagannathan,
Stephens, and Weisbach (2000) emphasize the financial flexibility of payout policies.
Measures of firm risk based on cash flow uncertainty and of industry-level volatility are
expected to be associated with lower dividends and more dividend decreases. Regressions
also control for measures of information asymmetry of the firm - number of analysts with
one-year-ahead forecasts of firm earnings. Bid-ask spread proxies for liquidity of the firm’s
shares; firms with more liquid shares may pay lower and more variable dividends as
investors value dividends less. The other control is change in median dividend level, which is
used to capture industry conditions and, potentially, propensity of firms to follow a generally
accepted dividend level. Variable definitions are described in more detail in Appendix A.
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Econometric analysis
Empirical tests address the hypotheses formulated in the previous section. First, the
coefficient on the lag of dividends for better aligned and misaligned managers in the dividend
regressions for firms that register positive dividends is estimated to test Hypothesis H1. The
sign on the interaction term is hypothesized to be negative, i.e. governance quality lowers
dividend persistence. Coefficients of persistence are also estimated for each firm using the
standard model of dividend level. These coefficients (available only in the cross-section) are
subsequently regressed on averages of firm characteristics and governance quality (expected
to enter negatively). In addition, several measures of dividend variability are used. Both in
the full sample and in the cross-section, dividends are expected to vary less when
alignment/governance is weak. To filter out the effect of potential interfering firm-level
factors, standard deviation of residuals from the expanded dividend regression is used as a
proxy for variability.
The other hypotheses examine dividend changes from the point of view of magnitude,
frequency, and direction. Hypotheses H2 and H3 that deal with dividend changes of different
type are tested in the Probit framework. In addition, the model of the likelihood of any
change in dividends (regardless of direction) is estimated. Alignment and governance quality
variables are expected to enter positively in the dividend decreases equation and positively
(or insignificantly) in the dividend increase equation. Further, the magnitude as well as
direction of dividend changes is examined in the regression framework using change in the
level of dividend relative to lagged dividend as the dependent variable. Governance is
expected to enter negatively in the change in dividend level equation. Dividend data for the
previous fiscal year must be available for all of these analyses.
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Finally, managerial preference towards method of payout policy changes is examined
in the Multinomial Logit framework. To examine the likelihood of dividend increase
(decrease) relative to an upward (downward) payout revision not involving dividends, we
construct categorical variables for the type of payout policy change (no change, change in
repurchases but not in dividends, change in dividends). Unlike in the case of ordered logit,
outcomes are not subject to a specific ordering.
From the methodological standpoint, this paper differs from existing literature on
dividends in recognizing and empirically addressing the potential issues of endogeneity of
governance and sample selection bias. Therefore, regressions correcting for selection bias
and endogeneity are presented following regular empirical analyses.
Endogeneity of governance
When measures of managerial incentive alignment used on the right hand side are not
exogenous to incremental dividend decisions, explanatory variables are correlated with the
error term in dividend equation. Endogeneity of governance will bias OLS estimates even if
all relevant control variables are included in the dividend equation (no omitted variable bias)
and incentive alignment is measured without error (no error-in-variables problem). Palia
(1999) examines endogeneity in the link between CEO ownership and performance. Brick,
Palia, and Wang (2005) and Chidambaran, Palia, and Zheng (2006) examine the causal link
between governance and performance. Hermalin and Weisbach (1998) provide an analytical
argument regarding endogeneity of boards.
To the best of the author’s knowledge, this is the first paper to identify and correct for
the endogeneity of governance and alignment to dividend behavior in the instrumental
20
variables framework4. One could offer an argument that illustrates potential for simultaneity
or reverse causality specifically in the case of dividends. First, endogeneity of governance
could be due to simultaneous choice of incentive structure and characteristics of the implicit
dividend contract that binds the manager. For instance, instead of increasing the intensity of
monitoring and degree of incentive alignment, shareholders can agree to a non-decreasing
persistent dividend path that provides an alternative way of constraining the manager.
Depending on the anticipated future cost of dividends to the firm relative to the cost of
setting up a strong monitoring and incentive structure, an optimal tradeoff of governance and
dividends is attained. Although governance would be negatively related to dividends, it will
not “cause” dividend decisions in this case. Second, instead of being simultaneously
determined, governance and dividends could exhibit reverse causality. From the manager’s
perspective, consistent compliance with the implicit dividend contract could earn a more
favorable shareholder attitude and potentially a reduction in monitoring intensity. In both
cases, the empirical relationship between governance and features of dividend policy will
have the hypothesized sign but will not be informative about causality.
This paper examines the hypothesized dividends – governance effects with explicit
recognition of potential endogeneity in the instrumental variables framework. At the first
stage, governance is predicted using a set of instruments (described below). At the second
stage, dividend behavior examined using instrumented governance variables.
The right-hand-side economic controls are believed to be exogenous variables (X1)
whereas the AGI variable and component alignment and governance measures are suspected
for endogeneity (X2). A set of exogenous instruments (Z), with at least one instrument per
each variable in the set X2, is chosen. Instruments affect governance but do not affect 4 Grinstein and Michaely (2005) employ VAR methodology to analyze institutional ownership and payout policy, but the scope of the present paper is governance and managerial alignment (and instrumental variables methodology is used to account for potential endogeneity).
21
dividends through channels other than governance quality (alignment). In the instrumental
variables estimation framework, two conditions on the validity of instruments should be met.
First, instrument relevance, i.e. significant predictive power of instruments in explaining
endogenous governance variables in the first-stage (governance) equation: Corr(X2,Z)�0.
Violation of this condition results in nonnormal sample distribution of the IV statistics,
resulting in unreliable hypothesis tests (for more on the weak instrument problem, see, e.g.
Stock and Yogo, 2002); in the extreme case of instrument irrelevance, estimates are
inconsistent. Second, instrument excludability, i.e. insignificant correlation of instruments
with the errors of the second-stage (dividend) equation: Corr(�,Z)=0; violation of this
condition results in inconsistent estimation (as with original endogenous regressors).
In the course of the empirical analysis the proposed instruments are tested against the
above criteria. First-stage F statistics (the rule of thumb in Staiger and Stock (1997) for a
single endogenous regressor is that F statistic should exceed 10), Shea partial R2 values (that
address correlation between instruments), and Anderson canonical correlations
underidentification test statistics are examined. In addition, rejection of the null hypothesis of
weak instruments using the Cragg and Donald (1993) test is used to validate instrument
strength, as suggested in Stock and Yogo (2002). The null hypotheses of instrument
irrelevance and instrument weakness are rejected (see discussion in the next section).
Another econometric issue concerns the need to use instrumental variables. If
ordinary least squares produces consistent estimates, i.e. there is no evidence of significant
correlation between governance variables and errors in the dividend equation, OLS
estimation is the preferred choice since it is more efficient. Tests of overidentifying
restrictions using the Hansen J statistic are performed to assess exogeneity of governance
variables and their respective instruments. This test is robust to the presence of
22
heteroscedasticity, including within-cluster heteroscedasticity used to adjust standard error
estimates in the performed regressions. Rejection of the null hypothesis suggests that
endogeneity is present. The null hypothesis is expected to be rejected in the equation without
instrumental variables if governance is endogenous; it is expected not to be rejected in the
equation with instrumental variables if instruments are exogenous. The results of the tests of
overidentifying restrictions and instrument relevance satisfy these requirements, as discussed
in the next section.
The construction of instruments is described below. The search for instruments is
focused on determinants that affect corporate governance and managerial incentives but not
dividend policy changes. Governance quality is believed to arises as the outcome of
shareholder demand for a sound monitoring structure (level of concern about strong
governance) and managerial ability to thwart shareholder efforts aimed at maintaining good
governance (managerial resistance to monitoring).
First, shareholder demand for strong governance is captured by market premium for
good governance quality. Market governance premium is computed at the industry-year level
(see Appendix A for details of its construction). The premium is defined separately for the
aggregate AGI measure and component governance measures and is related to the
interpretation of the dividend premium in Baker and Wurgler (2004). Market-wide
governance premium is exogenous to firm-level dividend decisions and serves as a measure
of intensity of shareholder demand for good corporate governance and therefore can be
argued to predict choice of governance quality. Institutional investor involvement with other
firms in the portfolio can serve as a proxy for the attention span and level of dedication of the
investor to an individual firm. Three measures are used to proxy focus (concentration of
holdings in the portfolio), involvement (average ownership stake among firms in the
23
institutional blockholder’s portfolio), and attention span (number of firms in the portfolio).
More focused and involved blockholders build up more significant exposures to each
individual firm and therefore have a stronger demand for governance quality of an individual
firm. Firms that are owned by ‘distracted’ institutional investors with dispersed portfolios
will be under relatively less pressure to maintain good governance since sale of the firm’s
shares is the easiest solution for the institutional investor in the case of an agency conflict.
Shareholder demand for monitoring and governance is also expected to be affected by
the value of managerial discretion given the nature of the industry. In industries where value-
enhancing managerial effort is much less observable, monitoring (disciplining) mechanisms
can frequently fail to identify inefficient investment projects. The higher level of noise and
false negatives associated with the monitoring structure could reduce overall shareholder
demand for strong governance. One could argue that high-tech industries fulfill this criterion
due to extensive presence of innovative projects with a high degree of asymmetric
information and investments whose return depends considerably on managerial skill, hence
the value placed of managerial discretion is high. The high-tech industry dummy is defined
according to Kasznik and Lev (1995): companies in pharmaceutical (SIC codes 2833-2836),
computer (SIC codes 3570-3577), electronics (SIC codes 3600-3674), programming (SIC
codes 7371-7379), and R&D services (SIC codes 8731-8734) industries.
Second, managerial ability to thwart shareholder efforts aimed at maintaining good
governance is conditional on the practice related to governance in a given industry and state.
If most firms follow sound governance practices, the manager’s ability to negotiate an
inferior governance structure is hampered. A manager that disagrees with the prevalent
governance and monitoring level is more likely to be fired and replaced with a manager that
works ‘within the accepted governance standards’. An individual firm’s manager is unlikely
24
to be able to influence the distribution of governance quality in the industry / location, which
defends the instrument’s exogeneity. Presence of state anti-takeover laws represents another
exogenous proxy for the ease of weakening the governance structure at the firm level. A
firm’s internal and external governance is expected to be correlated with median governance
quality and state laws. The advantage of the last two proposed instruments for governance
quality is that a strong argument can be made for their exogeneity to an individual firm’s
dividend policy. However, these measures are also potentially noisier and can have a low
correlation with the underlying endogenous firm-level governance variables. Therefore, a
firm-level proxy for managerial resistance to governance is used. It is expected that managers
in firms with strong market power are in a better position to provide a steady stream of
earnings for shareholders and thwart attempts to impose additional monitoring (entrenchment
effect). Market power of the firm is captured by its share in industry sales in a given year.
Finally, market environment conditions at the time of the firm’s entry affected the
bargaining power of the shareholders and the management when the early firm governance
structure was formed. Governance mechanisms evolve slowly over time, so entry-year
determinants of governance would arguably predict today’s governance quality. The
proposed instrument focuses on the level of market for corporate control activity in the year
of entry into CRSP database (the fraction of firms delisted due to merger). Unlike the year of
entry variable, which could be responsible for the direct age effect on dividends, more
aggressive takeover market activity in the year of entry is likely to specifically affect
formation of a better governance mechanism. Use of the CRSP historical data has advantage
over Compustat due to longer time series, hence more accurate measurement for more mature
firms.
Addressing selection bias
25
Examination of dynamic dividend path primarily relies on the sample of past dividend
payers. The data requirement for dividend regressions is availability of positive dividends in
the previous period. A potential econometric issue with the analysis of dividend persistence
and dividend changes is the use of a potentially non-random sample of firms. Determinants
of entry into the sample (i.e. determinants of the firm being a past dividend payer) can be
correlated with variables of interest in dividend regressions. Specifically, one could argue
that firms with lower risk, larger size, and more severe incentive problems would be in the
sample of dividend payers. The same characteristics are expected to be associated with lower
likelihood of dividend cuts, higher dividend changes, and a greater degree of dividend
smoothing, which potentially biases coefficient estimates in the regressions. Two-step
Heckman selection model is used to correct for selection bias. The self-selection parameter
(lambda) is expected to enter positively.
Univariate statistics and correlations are presented in Tables 1-2.
4. Results
The first set of results documents differences in dividend persistence across firms
with varying levels of managerial alignment and governance quality.
[TABLE 3]
The results in Table 3 suggest that better managerial alignment is associated with less
persistent dividends (lower coefficient on the lag of dividends). This is consistent with
Hypothesis H1. Managers in better governed firms are under less pressure to maintain the
previous period’s dividend level. The second column examines interactions with component
alignment measures. Internal monitoring by board of directors and institutional blockholders
is the channel through which alignment alleviates pressure to uphold the implicit dividend
contract. External governance is not significantly related to dividend persistence.
26
Results for relative dividend changes are presented in Table 4. Changes in dividend
level will be higher (more positive) if firms avoid dividend cuts and/or favor dividend
increases.
[TABLE 4]
The first result of Table 4 is the negative effect of governance quality on dividend
changes. Managers in firms with higher AGI values undertake lower dividend changes. This
result is consistent with the result in Table 3. It also lends support to Hypothesis H4.
The second column of Table 4 offers the results for component measures to identify
governance and alignment characteristics that have the strongest effect on dynamic dividend
behavior. The quality of board monitoring and institutional investor monitoring are
associated with lower dividend changes. CEO characteristics indicative of misalignment are
associated with higher dividend changes. Presence of takeover defenses is associated with
lower dividend changes, which is contrary to the hypothesized effect; potential explanations
will be discussed shortly.
While the magnitude of dividend increases tends to be much smaller than the
magnitude dividend cuts, dividend cuts are much less frequent, so it is not clear whether the
effect is dominated by increases or avoidance of decreases. The next set of results examines
the likelihood of dividend changes in the Probit framework, looking only at the frequency
and direction of changes. Unlike the results on relative dividend changes, Probit results take
out the asymmetric effect of large dividend decreases compared to smaller dividend increases
and only focus on the decision to adjust dividends.
[TABLE 5]
Better alignment is associated with less frequent dividend changes. The remainder of
the table disaggregates dividend changes into increases and decreases to examine the
27
direction effects. Consistent with Hypothesis H2, the probability of cuts and omissions is
higher for poorly governed firms (low AGI), in particular for firms with weak boards, low
intensity of institutional investor monitoring, and CEO characteristics indicating
misalignment. The likelihood of increases is significantly lower for well-governed managers,
suggesting that a strict form of Hypothesis H3 holds. Misaligned managers find an upward-
sloping smooth dividend path more beneficial than sustaining an invariable dividend level.
Arguably, a more conservative strategy with respect to setting of the initial dividend level
combines favorably with frequent small dividend increases that become possible as
uncertainty over future cash flow is resolved. Since increases are much more frequent than
decreases, the negative sign on governance quality in the likelihood of increases equation
dominates the negative effect of governance quality on the likelihood of any dividend
changes.
Out of the three presented sets of tests, in one instance external governance entered
with a positive sign. One possibility is that the sign will reverse (or the variable become
insignificant) after endogeneity or selection corrections are applied. If, however, the
underlying effect of a lack of takeover defenses on dividend changes is positive, the
following is the possible cause.
Internal monitoring on the part of the board and institutional owners provides a fairly
accurate assessment of managerial actions, yielding a less noisy link between suboptimal
managerial behavior and firing. If monitoring succeeds at addressing the suboptimal
investment problem, the manager can deviate from the dividend contract and still meet
shareholder expectations. External governance differs in two important respects. First, John
and Knyazeva (2005) argue that the market primarily observes firm-level underperformance;
even after filtering out common shocks, it is a noisier measure of managerial behavior and
28
can detect underperformance due to firm-specific factors other than suboptimal managerial
investment (false rejection of the ‘good managerial behavior’ hypothesis). Thus, investor and
potential raider actions based on stock market performance can provide a less targeted or
weaker disciplinary effect. Second, presence of anti-takeover defenses in the firm charter
(poor external governance) can directly affect job security by offering an entrenchment
mechanism in addition to increasing the misalignment. If, despite the weak alignment, the
manager can effectively thwart a takeover, she will be immune to shareholder pressure to
some degree and can choose to ignore the previous dividend promise without consequences.
Overall, the conclusion from Tables 3-5 is that failures in internal monitoring increase
the discretion of the manager in undertaking suboptimal investment choices and increase the
pressure from shareholders to sustain the previous dividend level, as hypothesized earlier.
However, one should exercise caution when interpreting OLS estimates due to potential
endogeneity or selection biases.
Tables 6A-C replicate the results in the selection model framework using a set of
determinants of being a past dividend payer in the first-stage selection equation and the
regression specification from earlier tables in the second-stage equation.
[TABLE 6A-6C]
Correction for self-selection in the selection model framework does not take away the
significance or reverse the signs of coefficient estimates observed in Table 3. Note that the
self-selection parameter (lambda, capturing selection hazard) is positive and statistically
significant, confirming the earlier suspicion that firms that in the past dividend payer sample
also possess characteristics associated with significantly higher dividend changes. Therefore,
it is important to allow for self-selection in any such analysis of dividend decisions. A similar
pattern is observed in Table 6B that predicts dynamic dividend behavior. Coefficients on
29
alignment variables become slightly more negative. The coefficient on external governance
loses its significance. In Table 6C, Probit model with selection is estimated. The estimate of
correlation between the selection and the main Probit equation is negative for dividend
decreases, suggesting that firms selected into the past dividend payer sample are also less
likely to cut dividends, which is intuitive.
The preliminary conclusion is that selection bias is significant but that overall
governance quality continues to affect dynamic dividend behavior in the hypothesized
manner, particularly through the channels of board quality, institutional investor monitoring,
and CEO alignment characteristics.
Instrumental variables estimation results are presented in Tables 7A-7C.
[TABLES 7A-7C]
The first two columns of Table 6A provides OLS estimates of the effect of alignment
on dynamic dividend behavior and tests of orthogonality of suspected alignment measure.
The C test of overidentifying restrictions performs a test of the original set of orthogonality
conditions, where the null hypothesis is that respective right-hand-side variables are
exogenous. It is computed as the difference of the two Hansen J statistics – restricted
(efficient), using the entire set of overidentifying restrictions, and unrestricted (inefficient but
consistent) using a smaller set of restrictions, in which specified variables are removed from
the set of exogenous variables. The advantage of the test is that it can be guaranteed to
produce nonnegative statistics in finite samples (for more on the issue, see Baum, Schaffer,
Stillman, 2003), including when robust standard errors are used. The p-values of the test
statistics are low and suggest rejection of the null hypothesis, indicating that correction for
endogeneity is warranted. Columns III-IV of Table 6A report estimates from instrumental
variables regressions of dynamic dividend behavior, instrumenting the full set of alignment
30
variables. The Hansen J statistic has high p-values, suggesting that the null hypothesis of
instrument orthogonality to dividend equation errors is not rejected, i.e. the instrument
excludability requirement is satisfied. Table 6B reports first-stage test statistics for the IV
regressions to check for instrument relevance and strength. F-statistics are considerably
above 10, all partial R2 are high, underidentification tests (Anderson canonical correlation
and Cragg-Donald) indicate rejection of the irrelevance hypothesis. The Cragg-Donald weak
identification test produces high test statistics, rejecting weakness of instruments.
Coefficient estimates in the IV regressions are comparable with OLS estimates in
terms of signs and significance. Among the differences is the insignificance of external
governance and significance of the dual class variable in the IV specification. It appears that
the positive OLS coefficient on external governance was affected by endogeneity bias
(consistent with a possible negotiation scenario) in addition to selection bias whereas the dual
class share effect was likely affected by endogeneity. Similarly, board quality, institutional
investor monitoring, and CEO characteristics remain significant and dual class effect enters
positively and significantly (in the case of dividend increases) after using Amemiya
Generalized Least Squares Probit estimation with endogenous predictors.
The conclusion from the presented set of results is that boards, institutional monitors,
CEO alignment characteristics and separation of ownership and control in dual class firms
are all significant determinants of managerial compliance with the implicit dividend contract
consistent with the formulated hypothesis.
Additional evidence on dividend variability and characteristics of dynamic dividend
behavior is presented in Tables 8A-8B. Managerial alignment is associated with more
dividend variability, particularly in the presence of effective boards and institutional investor
monitors.
31
[TABLES 8A-B]
Table 8B provides evidence on differences in dividend persistence across firms in
addition to examining dividend variability. Consistent with Hypothesis H1, standard
deviation of differenced dividends and dividend residuals is increasing in governance quality,
and the selection effect is significant and negative: firms with past dividend data are less
likely to have variable dividends. The last two columns document proportion of dividend
increases and dividend decreases over the sample period (for firms with positive past
dividends). Consistent with Hypotheses H2 and H3 and evidence in earlier Tables, dividend
decreases are less frequent when managers are misaligned, the opposite holds true for
dividend increases.
Multinomial Logit results in Table 9 indicate that dividend increases are the preferred
form of distributing additional payouts when managers are misaligned, consistent with
Hypothesis H5. Further, repurchases are the preferred method of cutting down on corporate
payout for firms with low values of the alignment index.
[TABLE 9]
Alternative explanations and tests
‘Quiet Life’ theory of dividend smoothing
One alternative explanation for dividend smoothing by misaligned managers
hypothesized in H1 and documented in Table 3 is based on a version of the “Quiet Life”
theory (see, e.g., Bertrand and Mullainathan, 2003). Misaligned managers are reluctant to
make any dividend changes because a stable payout policy lowers the amount of new
information that can be used by shareholders to update beliefs about the manager and
managerial quality and limits their exposure to present (hence, avoidance of cuts) and future
market scrutiny (leading to avoidance of increases failure to sustain which would increase
32
future scrutiny). Payout increases will be made through flexible repurchases. As can be seen
from previous tables (for instance, higher likelihood of dividend changes and dividend
increases for misaligned managers), the “quiet life” explanation is inconsistent with the
presented empirical results that support the main argument and hypotheses from Section 2.
Additional evidence: Stock market reaction to dividend decreases
Consistent with the preceding analysis, misaligned managers that cut dividends will
experience a significant adverse stock market response because they are deviating from the
dividend promise. Some evidence in support of this prediction is provided in Table 10.
Controlling for the change in dividends, managers in firms with better board monitoring face
a less negative reaction to dividend cut announcements. This is consistent with the
disciplining response of the shareholders when misaligned managers deviate from the
implicit dividend contract.
[TABLE 10]
Alternative weighting for the governance index: factor analysis
The main governance index used in the analysis was based on equal weighting of firm
rankings based on characteristics that are believed to affect managerial alignment. A different
approach to weighting would be the data reduction technique known as factor analysis. It
takes into account correlations among variables to produce the best linear combination of
factors with respective factor loadings. Inputs into the AGI, including all unadjusted
variables that were used to form rankings for the board quality, institutional investor
monitoring, and CEO characteristics indexes, as well as G index components, dual class
dummy variable and a few additional variables were subjected to factor analysis to identify
principal factors.
[TABLE 11]
33
Seven Aggregate Governance Factors (AGFs) were chosen using the eigenvalue
above 1 criterion, Cumulatively, they explain 87% of variation in the underlying variables.
The factor loadings obtained from orthogonal varimax rotation were used to construct the
new governance variables. Factor loadings with absolute value of at least 0.40 were used.
Based on the variables with the highest loadings, one can denote factors as follows: 1
institutional blockholders, 2 board structure and director duties, 3 CEO on key committees, 4
institutional ownership concentration, 5 takeover defenses, 6 separation of voting and cash
flow rights, 7 CEO characteristics. In both the OLS and IV regressions in Table 11, the CEO
characteristics factor is significant and positive. The board structure factor is negative and
significant. In the OLS specification, institutional investor monitoring enters significantly
and negatively, as predicted. In the IV specification (that is preferable due to endogeneity
bias in the OLS), separation of voting and cash flow rights enters positively and significantly.
The results obtained through factor analysis employed a different methodology but offer
predictions consistent with the earlier findings.
Two-way causality
Instrumental variables results are adjusted for potential feedback effect of dividends
on alignment in order to produce consistent estimates. 2SLS can be used to examine possible
two-way causality directly. In unreported 2SLS results (with lagged median dividend and
dividend premium added to the dividend equation and previous instrument set added to the
ownership and AGI equations), dividend changes have no significant effect on governance
whereas governance has a significant negative effect on dividend changes.
Endogeneity in dividend smoothing analyses
Previous analyses have focused on endogeneity in dynamic dividend behavior. In
unreported results, the specification from Table 3 is tested for endogeneity using the same set
34
of instruments for governance, dividend premium and lagged median dividend as well as
interaction between lagged premium dividend and governance premium as instruments for
dividend interaction with governance. C statistics have high p-values, indicating a lack of
rejection of the hypothesis that there is no endogeneity, whether we test dividend interaction
alone, or dividend interaction jointly with AGI and CEO ownership.
Conclusion
This paper examined the effect of governance and managerial characteristics on
dividend persistence and incremental dividend decisions and provided evidence on the
difference in managerial choice of the dynamic path of dividends. Firm managers choose
characteristics of dividend policy to trade off current private benefits and future job security.
Incentive misalignment due to governance failures, CEO characteristics, and separation of
ownership and control rights increases the potential for private benefits and inefficient
investment and simultaneously increases the likelihood of firing. To protect their job
security, misaligned managers respond to shareholder pressure by making and upholding a
credible dividend promise. Credibility of the dividend promise can be increases by using
persistent non-decreasing dividends. This paper has provided empirical evidence on the
dynamic dividend path consistent with this argument.
Misaligned managers were found to exhibit a greater degree of dividend smoothing.
The primary mechanism through misaligned managers implement dividend smoothing is
avoidance of dividend cuts and omissions. At the same time, misaligned managers are overall
more likely to increase dividends. Further, the disciplining effect of dividend increases makes
them the first choice of misaligned managers who distribute additional payouts to
shareholders. Of the forms of governance and incentive alignment mechanisms considered,
internal governance has the most pronounced effect on incremental dividend decisions.
35
From the methodological standpoint, this paper has contributed to dividend research
by allowing for endogeneity of managerial incentives and adjusting for selection bias, both of
which were present in the data but did not qualitatively change the main results. The
proposed instruments addressed two kinds of governance determinants: shareholder demand
for strong governance and managerial ability to resist monitoring.
The analysis in this paper sheds new light on the interpretation of stylized facts about
dividends, such as dividend smoothing and infrequency of dividend decreases. As John and
Knyazeva (2005) showed, poor governance is associated with use of dividends. This paper
has explained and documented the observed lack of flexibility in dividend policy as the
optimal choice of self-interested managers with misaligned incentives. Several issues are
open for future research. Dividend changes have been examined in relation to misaligned
managerial incentives, however, this leaves open the question of the effects of dividend
persistence on the signaling power of dividends and other forms of payout. In this paper the
main focus was on dividend policy changes. However, the effect of endogenously determined
managerial incentives on incremental capital structure decisions can be examined in future
work.
36
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Appendix A. Data and variables
Sample selection criteria
The results are obtained using a sample of Compustat Industrial Annual firms for 1993-2004, excluding firms with book value of total assets less than 20 mln. and firms in financial (SIC codes 6000-6999) and regulated utilities industries (SIC codes 4949-4999). We require that governance, compensation, and CRSP dividend data be available. Regressions of dividend smoothing, dynamic dividend behavior, and likelihood of dividend increases use the sample of firms with positive current and lagged dividends (5,438 obs.) Models of the likelihood of any dividend changes/dividend decreases (cuts and omissions) use the sample of past dividend payers (5,564 obs.). Selection models use the full sample of firms (9,854 obs.). Dependent variables in the analyses
Dividend smoothing: DIVt, dividends per share; computed as the sum of ordinary quarterly dividends per share (code 1232) adjusted for splits, in a fiscal year. Source: CRSP monthly. Dividends are regressed on lagged dividends (DIVt_1), a set of controls (see below) including governance (see below). Of interest are coefficients on the interaction of DIVt_1 and alignment/governance.
Dynamic dividend behavior: DIV_CHANGE=[DIVt-DIVt_1]/DIVt_1, change in dividends per share; see above. Change in dividends is regressed on a set of controls. Of interests are coefficients on alignment/governance variables.
Incremental dividend decisions: Likelihood of a change in dividends from DIVt_1 to DIVt: - any change (increase or decrease, including omission); defined for past dividend payers; - increase (DIVt is higher than DIVt-1), defined for firms with positive current and lagged dividends; - decrease (DIVt is lower than DIVt-1, including omission of dividend), defined for past dividend payers.
Dividend variability: DIV_SD (positive values only), annual standard deviation of ordinary quarterly dividends per share (code 1232) adjusted for splits, in a fiscal year. Source: CRSP monthly.
Dividend variability, cross-section: standard deviations were computed over the sample period from annual observations for firms with positive current and lagged dividends; at least two annual observations for a given firm were required to construct a standard deviation measure, yielding a total of 701 firm-level observations. Two measures were used: (i) SD_DIFF, standard deviation of annual differenced dividends (DIVt-DIVt_1); (ii) SD_RESID, standard deviation of residuals obtained from the annual dividends regression on lagged dividends, growth in sales, market-to-book, R&D to assets, asset size, analyst following, CEO stock option grants, CEO ownership, volatility, index of takeover defenses, institutional investor monitoring, and board monitoring, and industry and year dummies.
Dividend persistence, cross-section: coefficient of dividend persistence (PERSIST) from the regression of ordinary quarterly dividends per share (code 1232) adjusted for splits on lagged dividends, earnings per share, and index of governance, estimated for each firm over the sample period, yielding 775 firm-level obs. (note that quarterly rather than annual frequency of data was used).
Frequency of dividend changes, cross-section: P_INCR, the fraction of sample period years with annual dividend increases (see above) for past dividend payers; P_DECR, the fraction of sample period years with annual dividend decreases (see above) for past dividend payers; 787 firm-level obs. for past dividend payers.
Type of payout policy change: the analysis employs Multinomial Logit estimation to determine whether dividend increases (decreases) are the preferred form of upward (downward) payout policy revision conditional on managerial alignment. Two categorical variables for type of payout policy revision are used (no ordering is imposed): UPWARD_CHANGE: 1 no increase in dividends or repurchases; 2 increase in repurchases, no increase in dividends; 3 increase in dividends. DOWNWARD_CHANGE: 1 no decrease in dividends or repurchases; 2 decrease in repurchases, no decrease in dividends; 3 decrease (cut or omission) in dividends. For definition of dividends, see above. Repurchases are defined as item #115 in Compustat Industrial Annual; 0 if missing, following Frank and Goyal (2002). Changes are evaluated on an annual basis. Of interest are the coefficients on alignment/governance variables in equations comparing the likelihood of outcome 3 versus outcome 2 for each of the two variables. Explanatory variables in the analyses
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CASH_FLOW – ratio of earnings before interest, taxes, and depreciation (item #13) to lagged book value of total assets (item #6). Source: Compustat Industrial Annual.
SIZE – natural log of total assets (item #6), lagged one year. Source: Compustat Industrial Annual.
INV_OPP – ratio of firm market value (item #25, number of shares outstanding, times item #199, share price at fiscal year-end, plus item #9, plus item #34) to the book value of total assets (item #6). Use of alternative market value definition (item #25, number of shares outstanding time item #199, share price at fiscal year-end, minus item #60, book value of common equity, plus item #6, book value of total assets) does not affect the results. Source: Compustat Industrial Annual.
GROWTH_OPP – growth of net sales (item #12). Source: Compustat Industrial Annual.
RISK_1 – moving standard deviation of quarterly net income (item #8 in Compustat Industrial Quarterly) computed over up to 12 quarters (current fiscal year and two previous fiscal years). Source: Compustat Industrial Quarterly.
RISK_2 – three-year moving standard deviation of excess stock return (excluding dividends, using CRSP value-weighted return) computed at the industry median. Source: CRSP monthly.
CEO_OPTIONS – percentage of stock options owned by the CEO in the total number of shares outstanding. Source: Execucomp.
CEO_OWN – percentage stake of the CEO in the total number of shares outstanding. Source: Execucomp.
ANALYSTS – natural log of the number of one-year-ahead analyst forecasts of annual earnings per share. Source: I/B/E/S summary database.
LIQUIDITY – bid-ask spread normalized by stock price, adjusted for splits and stock dividends. Source: CRSP monthly.
TAX – ratio of item #16, income taxes, to item #170, pretax income. Source: Compustat Industrial Annual.
MED_CHANGE – change in dividends per share computed at the industry median. For the definition of dividends per share, see above.
DIVt_1 - value of DIVt lagged one year; the variable is used in dividend smoothing analyses. Alignment/governance variables (AGI, BOARD_MONIT, INST_MONIT, EXT_GOV, DUAL_CLASS) are described below. Dividend smoothing regressions include interactions of DIVt_1 with alignment/governance variables.
INDUSTRY and YEAR controls – Fama-French industry dummies and year dummies are included in all regression analyses. Selection equation variables Selection model (full maximum likelihood model with clustering of errors by firm id) is used to test and adjust for the potential bias that arises due to non-randomness of firms in the sample of past dividend payers that can be correlated with governance. Full maximum likelihood probit model with sample selection is used for incremental dividend decisions. In both cases, the first stage estimates the probability of the firms being in the sample (i.e. having positive DIVt-1). The selection equation uses the following variables: STATE_LAWS, CASH_FLOW, SIZE(SALES), MED_LAG_DIVt_1, D_HITECH, CEO_OWN, CEO_OPTIONS. SIZE(SALES) - natural log of net sales (item #12), lagged one year. Source: Compustat Industrial Annual. MED_LAG_DIVt_1 – lagged dividends per share, computed at the industry median. Event study of dividend decreases The sample of dividend decreases is based on CRSP monthly data. Besides sample selection criteria outlined above, a firm is required to register a negative change in DIVt (as defined above). A previous dividend payment is required to be recorded in the preceding 183 calendar days. CRSP daily file must contain enough data to compute normal and abnormal returns for the event. The announcement date is the declaration date of the dividend announcement in CRSP, corresponding to a decrease in DIVt. The event window is -1 to +1, where 0 is the day of the announcement. The estimation window is -150 to -30 days before the event (firm-events with fewer than 90 obs. in the estimation window are dropped).
Alignment/Governance Index (AGI) and Component Indexes
Alignment/Governance Index (AGI) is constructed by equally weighting the following component indexes/variables: 1. Institutional Investor Monitoring (INSTIT_MONIT) (+); 2. Board Monitoring (BOARD_MONIT) (+); 3. CEO Characteristics (-); 4. External Governance Quality (EXT_GOV); 5. Separation of Ownership and Control (DUAL_CLASS) (-). The construction of the component indexes and data on component variables is described below. The reported means, medians, and standard deviations are computed from the full sample (9854 obs.) for the underlying variables listed in the second column. All correlations between underlying variables and component indexes/AGI are significant at 1% level.
Component Indexes/Variablesa Variable Construction
Effect on
align- ment
Corr. with
compo- nent
Corr. with AGI
Mean Median SD
I. INSTIT_MONIT + 1.00 0.45 0.477 0.499 0.188 a. Largest inst. owner stake (+) Sum of firm rankingsb increasing in: [Source of inputs: Thomson Financial, 13f] Largest institutional owner stake in the firm + 0.68 0.28 8.975 8.488 4.079 Largest stake of “other institutional investor” (type 5) + 0.43 0.18 5.678 4.794 4.649 Largest stake of the public pension fundc
+ 0.31 0.15 1.206 0.783 1.388 b. Presence of a blockholder (+) Sum of dummy variablesd for the presence of: [Source of inputs: Thomson Financial, 13f] Institutional blockholder (at 5% or higher) + 0.71 0.29 0.824 1.000 0.337 Public pension fund blockholderc (at 5% or higher) + 0.77 0.32 0.047 0.048 0.027 c. Number of institutional owners (-) Sum of firm rankingsb decreasing in: [Source of inputs: Thomson Financial, 13f] The number of institutional owners (log) - -0.74 -0.36 5.000 4.956 0.723 The number of public pension fund owners (log) - -0.48 -0.28 1.993 2.169 0.553 d. Institutional ownership concentration (+) Sum of firm rankingsb increasing in [Source of inputs: Thomson Financial, 13f] Total institutional ownership concentration + 0.68 0.32 0.057 0.049 0.035 Concentration of institutional blockholdings + 0.78 0.35 0.051 0.046 0.038 II. BOARD_MONIT + 1.00 0.40 0.590 0.592 0.121 a. Board independence (+) Sum of firm rankingsb by: [Source of inputs: IRRC Directorse] Fraction of independent directors on the board (incr.) + 0.47 0.04 0.633 0.667 0.178 Fraction of employee directors on the board (decr.) - -0.41 -0.03 0.215 0.182 0.115 b. Board size (-) Firm rankingb by log of board size (decr.) - -0.39 -0.45 2.206 2.197 0.278 [Source of inputs: IRRC Directorse]
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c. CEO’s presence on key committees (-) sum of dummy variablesd for the presence of: - [Source of inputs: IRRC Directorse] CEO on nominating committee - -0.21 -0.07 0.075 0.000 0.264 CEO on compensation committee - -0.15 -0.03 0.017 0.000 0.129 CEO on governance committee - -0.14 -0.06 0.023 0.000 0.151 CEO on audit committee - -0.10 -0.03 0.009 0.000 0.094 d. Board meetings (+) Firm rankingb by log of number of board meetings + 0.67 0.15 1.895 1.946 0.354 [Source of inputs: Execucomp] (incr.) III. CEO_CHARACT - 1.00 -0.52 0.475 0.461 0.232 a. CEO age (log) Firm rankingb increasing in log of age of the CEO - 0.75 -0.46 3.998 4.007 0.131 [Source of inputs: IRRC Directorse] b. CEO tenure (log) Firm rankingb increasing in log of tenure of the CEO - 0.79 -0.36 1.527 1.609 1.007 [Source of inputs: Execucomp] (replaced to 0 if the CEO started in the firm this year) IV. EXT_GOV Firm rankingb decreasing in: + 1.00 0.54 0.450 0.439 0.290 [Source: IRRC Governancef; Gompers, Ishii, Metrick (2003)] G Index of takeover defenses - -0.98 -0.53 9.328 9.000 2.710 V. SEPARATION OWN-P/CONTROL Dummy for having dual classes of shares - 1.00 -0.40 0.049 0.000 0.216 [Source: Gompers, Ishii, Metrick (2005)]
Notes: a – Component indexes add firm governance characteristics (equally weighted) listed in the first column. b – Where indicated, annual firm rankings are constructed based on each of the input variables in the second column to capture relative alignment/governance quality. Firms with lower values of \ variables with “-” effect on alignment and with higher values of variables with “+” effect on alignment are rated higher. The resulting rankings are rescaled to [0,1] such that higher values are associated with better alignment/governance and equally weighted to produce firm governance characteristics in the first column that are subsequently aggregated into one of the indexes. c – Public pension funds are identified from Thomson Financial using the list in Cremers and Nair (2005). d – Where applicable, dummy variables (or one minus the indicated dummy variable, if it has a “-” effect on alignment) are equally weighted to produce firm governance characteristics in the first column that are subsequently aggregated into one of the indexes. e – IRRC Directors issued a notice about (imprecise) matching of ‘CEO’ title to individual directors (e.g. non-CEO directors holding a CEO position in another firm). Where the name of a director’s primary employer was available, the author hand-checked for accurate matching of the CEO flag to director id. Data is available for 1996-2004; data for 1993-1995 was backfilled using year 1996 data. f –Data is available for 1993, 1995, 1998, 2000, 20002, 2004; data for gap years was filled in using (averages of) data from adjacent years.
Instrumental variables Instrumental variables regressions predict corporate governance at the first stage and dividend behavior in the second stage. First-stage regressions employ the following instruments:
Instruments for Alignment/Governance Index (AGI) and CEO ownership
STATE_LAWS – the index of six state anti-takeover laws, converted into ranking (more antitakeover laws indicates worse governance), rescaled to [0,1]; higher values indicate better alignment; the following state laws are included: business combination law; control share acquisition law; cash out law; fair price law; director's duties law; antigreenmail (recapture of profits) laws. MED_INT_CEO – median of the index of board monitoring, institutional monitoring, CEO characteristics (equally weighted) computed for each industry – state pair; MED_CEO_OWN – median of CEO_OWN computed for each industry – state pair; MKTBPR_AGI – market premium for governance quality, computed as the differential in log of asset-weighted average market-to-book ratio (computed at the 3-digit SIC industry level; 2-digit SIC industry level if not available; 1-digit SIC industry level if not available; at the market level if not available) of firms with AGI above and below sample median. A related variable, dividend premium, is used in Baker and Wurgler (2004); MKTBPR_CEO_OWN - market premium for CEO ownership, computed as the differential in log of asset-weighted average market-to-book ratio of firms with CEO_OWN above and below sample median; MARKET_SHARE – share of the firm’s net sales (item #12) in total sales in the industry (at the 3-digit SIC level) in a given year. Source: Compustat Industrial Annual; D_HITECH – dummy variable equal to 1 if the firm belongs to the SIC codes 2833-2836 (drugs), 3570-3577 (computers), 3600-3674 (electronics), 7371-7379 (programming), 8731-8734 (R&D services); 0 otherwise; the classification is based on Kasznik and Lev (1995). TAKEOVERS_YR_ENTRY – takeover activity in the year the firm appeared in the CRSP database; takeover activity is measured by the fraction of firms delisted with the delisting code 2 (merger);
Instruments for the full set of alignment/governance variables (BOARD_MONIT, INSTIT_MONIT, CEO_CHARACT, EXT_GOV, DUAL_CLASS) and CEO ownership
MED_BOARD_MONIT – median of BOARD_MONIT computed for each industry – state pair; MED_INSTIT_MONIT – median of INSTIT_MONIT computed for each industry – state pair; MED_CEO_CHARACT – median of CEO_CHARACT computed for each industry – state pair; MED_SEPARATION – median of the difference in voting and cash flow rights held by insiders, computed for each industry – state pair; MED_EXT_GOV – median of EXT_GOV computed for each industry – state pair; MKTBPR_BOARD_MONIT - market premium for quality of board monitoring, computed as the differential in log of asset-weighted average market-to-book ratio of firms with BOARD_MONIT above and below sample median (see above); MKTBPR_INSTIT_MONIT - market premium for intensity of institutional investor monitoring, computed as the differential in log of asset-weighted average market-to-book ratio of firms with INSTIT_MONIT above and below sample median (see above); MKTBPR_EXT_GOV - market premium for quality of external governance, computed as the differential in log of asset-weighted average market-to-book ratio of firms with EXT_GOV above and below sample median (see above); MKTBPR_CEO_CHARACT - market premium for CEO characteristics, computed as the differential in log of asset-weighted average market-to-book ratio of firms with CEO_CHARACT above and below sample median (see above); BLOCKHR_FOCUS – average concentration of portfolio (excluding stake in this firm) of institutional investors with stakes in the firm; BLOCKHR_INVOLVEMENT – average holding in the firm in the portfolio (excluding stake in this firm) of institutional investors with stakes in the firm; BLOCKHR_ATTENTION_SPAN – average number of other firms in the portfolio (a measure of ‘attention span’ / busyness) of institutional investors with stakes in the firm; and STATE_LAWS, MED_CEO_OWN, MKTBPR_CEO_OWN, MARKET_SHARE, D_HITECH, TAKEOVERS_YR_ENTRY.
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Table 1. Summary statistics of the main variables Sample selection criteria and variable definitions are provided in Appendix A.
Obs. Mean Med. SD DIVt 5438 0.521 0.400 0.415 DIVt_1 5564 0.498 0.400 0.408 DIV_CHANGE 5438 0.074 0.033 0.269 D_DIV_CHANGE 5564 0.653 1.000 0.476 D_DIV_INCR 5438 0.572 1.000 0.495 D_DIV_DECR 5564 0.094 0.000 0.292 DIV_SD (>0 only) 1913 1.043 0.500 1.546 AGI 9854 0.599 0.599 0.099 BOARD_MONIT 9854 0.590 0.592 0.121 INSTIT_MONIT 9854 0.477 0.499 0.188 CEO_CHARACT 9854 0.475 0.461 0.232 EXT_GOV 9854 0.450 0.439 0.290 DUAL_CLASS 9854 0.049 0.000 0.216 CASH_FLOW 9854 0.170 0.161 0.125 SIZE 9854 7.248 7.077 1.457 GROWTH_OPP 9854 0.115 0.079 0.296 INV_OPP 9854 1.797 1.317 1.788 RISK1 9854 0.587 0.159 1.304 RISK2 9854 0.107 0.102 0.033 CEO_OPTIONS 9854 1.230 0.863 1.273 ANALYSTS 9854 11.542 9.667 8.075 LIQUIDITY 9854 0.250 0.174 0.305 TAX 9854 0.338 0.359 1.686 MED_CHANGE 9854 0.040 0.030 0.107 Cross-section SD_DIFF 701 6.035 2.907 7.853 SD_RESID 701 6.137 2.987 7.451 PERSIST 775 0.595 0.762 0.565 P_INCR 787 0.523 0.500 0.375 P_DECR 787 0.135 0.000 0.238
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Table 2. Correlations of the main variables Sample selection criteria and variable definitions are provided in Appendix A. Pairwise correlations between the following variables: 1 DIVt; 2 DIVt_1; 3 DIV_CHANGE; 4 D_DIV_CHANGE; 5 D_DIV_INCR; 6 D_DIV_DECR; 7 AGI; 8 BOARD_MONIT; 9 INSTIT_MONIT; 10 CEO_CHARACT; 11 EXT_GOV; 12 DUAL_CLASS; 13 CASH_FLOW; 14 SIZE; 15 GROWTH_OPP; 16 INV_OPP; 17 RISK_1; 18 RISK_2; 19 CEO_OPTIONS; 20 ANALYSTS; 21 LIQUIDITY; 22 TAX; 23 MED_CHANGE. Correlations significant at 5% are underlined.
Panel A. Pairwise correlations of main variables
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 1 2 0.97 3 -0.03 -0.19 4 0.01 -0.03 0.20 5 0.06 -0.05 0.43 0.86 6 -0.09 0.00 -0.44 0.23 -0.32 7 -0.09 -0.08 -0.04 -0.13 -0.18 0.10 8 0.13 0.15 -0.08 -0.11 -0.15 0.08 0.40 9 -0.20 -0.18 -0.10 -0.22 -0.27 0.12 0.45 0.08 10 -0.05 -0.05 0.04 0.03 0.05 -0.04 -0.52 -0.16 -0.03 11 -0.15 -0.14 0.06 0.03 0.02 0.02 0.54 -0.03 0.10 0.03 12 -0.04 -0.04 -0.01 0.04 0.04 0.00 -0.40 -0.16 0.05 0.05 0.13 13 -0.04 -0.06 0.20 0.20 0.29 -0.17 -0.11 -0.11 -0.23 0.02 0.02 -0.01 14 0.37 0.35 0.01 0.07 0.09 -0.04 -0.37 -0.04 -0.61 0.03 -0.20 -0.02 -0.01 15 -0.13 -0.14 0.12 0.04 0.09 -0.10 0.05 -0.02 -0.03 -0.01 0.08 -0.02 0.23 -0.08 16 -0.09 -0.10 0.13 0.20 0.23 -0.07 0.02 0.00 -0.19 -0.02 0.13 -0.01 0.37 -0.10 0.23 17 0.23 0.22 0.00 0.05 0.04 0.01 -0.10 0.06 -0.40 -0.03 0.01 -0.03 0.02 0.57 0.06 0.09 18 -0.16 -0.14 -0.04 -0.05 -0.09 0.08 0.16 0.10 0.04 -0.07 0.14 -0.01 -0.06 -0.13 0.05 0.18 0.09 19 -0.20 -0.19 -0.02 -0.14 -0.17 0.07 0.18 0.09 0.30 0.03 0.08 -0.03 -0.13 -0.36 -0.01 -0.04 -0.19 0.14 20 0.15 0.12 0.08 0.11 0.15 -0.08 -0.23 0.01 -0.60 0.00 -0.06 -0.08 0.20 0.64 0.08 0.22 0.47 -0.02 -0.30 21 -0.32 -0.32 0.06 0.06 0.04 0.04 0.11 0.08 -0.03 -0.02 0.14 -0.03 0.16 -0.09 0.16 0.28 0.05 0.18 0.02 0.14 22 -0.01 -0.01 0.00 0.01 0.01 -0.01 -0.01 0.00 -0.02 -0.01 -0.01 0.00 0.02 0.03 0.01 0.00 0.00 0.00 -0.01 0.03 0.00 23 -0.03 -0.06 0.35 0.09 0.18 -0.16 0.01 0.01 -0.03 0.00 0.02 -0.03 0.06 0.00 0.00 0.05 -0.01 -0.11 -0.02 0.04 0.00 -0.01
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Panel B. Pairwise correlations for cross-section analyses
1 2 3 4 5 6 7 8 9 10 1 SD_DIFF 2 SD_RESID 0.99 3 PERSIST 0.05 0.01 4 P_INCR -0.13 -0.15 0.38 5 P_DECR 0.50 0.49 -0.15 -0.44 6 AGI 0.04 0.04 -0.20 -0.24 0.17 7 BOARD_MONIT 0.12 0.12 -0.08 -0.22 0.10 0.41 8 INSTIT_MONIT -0.07 -0.06 -0.23 -0.32 0.20 0.45 0.08 9 CEO_CHARACT -0.08 -0.08 0.05 0.08 -0.08 -0.48 -0.19 -0.01
10 EXT_GOV -0.01 -0.02 -0.08 -0.01 0.04 0.58 -0.04 0.13 0.05 11 DUAL_CLASS -0.03 -0.04 0.04 0.04 -0.01 -0.40 -0.18 0.03 0.06 0.14
Table 3. Dividend smoothing and managerial alignment/governance Dividend smoothing and managerial alignment. OLS regressions of dividend level (DIVt). Robust standard errors (clustering by firm id) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria and variables are defined in Appendix A.
I II DIVt_1 1.059 *** 1.050 *** (.044) (.027) DIVt_1xAGI -0.175 * (.081) DIVt_1xBOARD_MONIT -0.078 * (.040) DIVt_1xINSTIT_MONIT -0.096 *** (.024) DIVt_1xCEO_CHARACT 0.008 (.022) DIVt_1xEXT_GOV -0.017 (.018) DIVt_1xDUAL_CLASS 0.004 (.024) AGI 0.037 0.019 (.029) (.029) CEO_OWN 0.047 † 0.054 † (.025) (.028) CASH_FLOW 0.229 *** 0.208 *** (.027) (.027) SIZE 0.009 *** 0.007 * (.002) (.003) GROWTH_OPP -0.014 -0.013 (.009) (.009) INV_OPP -0.004 * -0.004 * (.002) (.002) RISK_1 -0.001 -0.002 (.002) (.001) RISK_2 -0.205 -0.212 (.161) (.160) CEO_OPTIONS -0.001 -0.001 (.001) (.001) ANALYSTS 5.0E-04 4.2E-04 (3.6E-04) (3.5E-04) LIQUIDITY -0.043 *** -0.042 ** (.011) (.010) TAX -4.7E-04 -4.5E-04 (.001) (.001) MED_CHANGE 0.181 *** 0.185 *** (.033) (.033) Number of obs. 5438 5438 Number of groups 767 767 R2 0.945 0.946 Adj. R2 0.945 0.945
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
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Table 4. Dynamic dividend behavior and managerial alignment/governance Dynamic dividend behavior and managerial alignment. OLS regressions of dividend changes (DIV_CHANGE). Robust standard errors (clustering by firm id) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria and variables are defined in Appendix A.
I II AGI -0.118 * (.046) BOARD_MONIT -0.100 ** (.032) INST_MONIT -0.098 *** (.029) CEO_CHARACT 0.039 * (.016) EXT_GOV 0.033 * (.016) DUAL_CLASS 0.015 (.014) CEO_OWN 0.232 ** 0.148 † (.080) (.078) CASH_FLOW 0.497 *** 0.468 *** (.075) (.075) SIZE -0.002 -0.006 (.005) (.005) GROWTH_OPP 0.036 0.031 (.022) (.022) INV_OPP -0.001 -0.003 (.006) (.006) RISK_1 -0.003 -0.005 (.003) (.003) RISK_2 -0.300 -0.292 (.304) (.306) CEO_OPTIONS -0.001 0.000 (.004) (.004) ANALYSTS 0.002 * 0.002 * (.001) (.001) LIQUIDITY 0.035 * 0.035 † (.018) (.018) TAX 0.001 0.001 (.001) (.001) MED_CHANGE 0.983 *** 0.979 *** (.167) (.167) Number of obs. 5438 5438 Number of groups 767 767 R2 0.190 0.196 Adj. R2 0.180 0.185
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
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Table 5. Incremental dividend decisions and managerial alignment
Incremental dividend decisions and managerial alignment. Probit regressions of the likelihood of dividend changes: any changes (D_DIV_CHANGE), increase (D_DIV_INCR), decrease (D_DIV_DECR). Robust standard errors (clustering by firm id) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria and variables are defined in Appendix A. ANY CHANGE INCREASE DECREASE I II III IV V VI AGI -1.459 *** -2.103 *** 1.466 *** (.347) (.354) (.341) BOARD_MONIT -0.990 *** -1.415 *** 0.850 ** (.260) (.274) (.280) INST_MONIT -1.351 *** -1.620 *** 0.738 ** (.209) (.218) (.242) CEO_CHARACT 0.171 0.275 * -0.267 * (.125) (.129) (.127) EXT_GOV 0.063 -0.003 0.130 (.123) (.131) (.113) DUAL_CLASS 0.161 0.216 -0.088 (.145) (.144) (.148) CEO_OWN -0.171 -0.454 0.118 -0.233 -0.674 -0.449 (.628) (.641) (.623) (.631) (.777) (.749) CASH_FLOW 1.811 ** 1.375 * 3.601 *** 3.131 *** -4.119 *** -3.842 *** (.640) (.603) (.706) (.686) (.647) (.655) SIZE 0.086 * 0.026 0.114 * 0.047 -0.066 † -0.041 (.042) (.043) (.046) (.048) (.039) (.043) GROWTH_OPP -0.087 -0.114 0.059 0.030 -0.238 -0.217 (.126) (.123) (.139) (.135) (.181) (.177) INV_OPP 0.160 * 0.137 * 0.091 0.068 0.088 * 0.096 * (.077) (.068) (.062) (.055) (.043) (.043) RISK_1 -0.009 -0.021 -0.038 -0.053 * 0.067 * 0.071 ** (.027) (.028) (.028) (.027) (.028) (.027) RISK_2 -0.042 0.041 -2.128 -2.095 1.676 1.524 (2.058) (2.095) (2.080) (2.117) (2.691) (2.683) CEO_OPTIONS -0.103 *** -0.088 ** -0.124 *** -0.105 ** 0.042 0.035 (.032) (.032) (.037) (.037) (.030) (.031) ANALYSTS -0.008 -0.012 † -0.005 -0.010 -0.008 -0.006 (.007) (.007) (.008) (.007) (.007) (.007) LIQUIDITY 0.302 0.317 0.059 0.072 0.421 * 0.415 * (.221) (.222) (.138) (.137) (.179) (.176) TAX 0.010 0.009 0.018 * 0.018 * -0.012 -0.012 (.009) (.009) (.008) (.008) (.015) (.014) MED_CHANGE 0.627 * 0.646 * 2.314 *** 2.296 ** -3.601 *** -3.620 *** (.306) (.311) (.719) (.746) (.629) (.645) Number of obs. 5564 5564 5438 5438 5564 5564 Number of groups 787 787 767 767 787 787 Pseudo R2 0.089 0.104 0.146 0.166 0.147 0.152 AIC 6672.7 6575.9 6477.3 6336.4 3085.6 3077.6 BIC 7116.5 7046.2 6919.5 6805.1 3509.6 3528.1
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
49
Table 6A. Dividend smoothing and managerial alignment/governance: selection model Dividend smoothing and managerial alignment/governance: accounting for selection bias. Selection model (full maximum likelihood estimation) of dividend level (DIVt). Selection equation includes STATE_LAWS, CASH_FLOW, SIZE(SALES), MED_LAG_DIVt_1, D_HITECH, CEO_OWN, CEO_OPTIONS, and year dummies. Robust standard errors (clustering by firm id) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria and variables are defined in Appendix A.
I II DIVt_1 1.060 *** 1.050 *** (.044) (.027) DIVt_1xAGI -0.175 * (.081) DIVt_1xBOARD_MONIT -0.077 * (.039) DIVt_1xINSTIT_MONIT -0.095 *** (.024) DIVt_1xCEO_CHARACT 0.007 (.022) DIVt_1xEXT_GOV -0.019 (.018) DIVt_1xDUAL 0.005 (.023) AGI 0.034 0.016 (.029) (.029) CEO_OWN 0.032 0.040 (.026) (.028) CASH_FLOW 0.240 *** 0.218 *** (.027) (.027) SIZE 0.011 *** 0.009 *** (.003) (.003) GROWTH_OPP -0.015 † -0.014 (.009) (.009) INV_OPP -0.004 * -0.004 * (.002) (.002) RISK_1 -0.001 -0.002 (.001) (.001) RISK_2 -0.213 -0.219 (.160) (.158) CEO_OPTIONS -0.003 * -0.003 † (.002) (.002) ANALYSTS 4.3E-04 3.6E-04 (3.5E-04) (3.5E-04) LIQUIDITY -0.044 *** -0.043 *** (.011) (.010) TAX -4.6E-04 -4.3E-04 (.001) (.001) MED_CHANGE 0.180 *** 0.183 *** (.032) (.033) Inverse Mills' Ratio (Lambda) 0.018 *** 0.017 *** (.005) (.005) Number of obs. 9854 9854 Censored obs. 4416 4416 Number of groups 787 787 Chi2 16.35 12.98 AIC 674.8 638.9 BIC 1329.6 1322.5
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
50
Table 6B. Dynamic dividend behavior and managerial alignment/governance: selection model
Dynamic dividend behavior and managerial alignment/governance: accounting for selection bias. Selection model (full maximum likelihood estimation) of changes in dividends (DIV_CHANGE). Selection equation includes STATE_LAWS, CASH_FLOW, SIZE(SALES), MED_LAG_DIVt_1, D_HITECH, CEO_OWN, CEO_OPTIONS, and year dummies. Robust standard errors (clustering by firm id) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria and variables are defined in Appendix A.
I II AGI -0.175 *** (.044) BOARD_MONIT -0.113 *** (.032) INST_MONIT -0.121 *** (.027) CEO_CHARACT 0.034 * (.015) EXT_GOV 0.007 (.015) DUAL_CLASS 0.019 (.013) CEO_OWN 0.046 -0.001 (.113) (.113) CASH_FLOW 0.668 *** 0.627 *** (.080) (.079) SIZE 0.034 *** 0.029 *** (.006) (.006) GROWTH_OPP 0.007 0.004 (.025) (.025) INV_OPP -0.007 -0.008 (.006) (.006) RISK_1 -0.005 -0.006 † (.003) (.003) RISK_2 -0.456 -0.474 (.310) (.311) CEO_OPTIONS -0.024 *** -0.023 *** (.007) (.007) ANALYSTS 0.001 † 0.001 (.001) (.001) LIQUIDITY -0.001 -2.6E-04 (.018) (.017) TAX 0.001 0.001 (.001) (.001) MED_CHANGE 0.809 *** 0.803 *** (.158) (.159) Inverse Mills' Ratio (Lambda) 0.233 *** 0.233 *** (.021) (.021) Number of obs. 9854 9854 Censored obs. 4416 4416 Number of groups 1609 1609 Chi2 181.99 181.66 AIC 10310.5 10284.4 BIC 10951.0 10953.6
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
51
Table 6C. Incremental dividend decisions and managerial alignment/governance: instrumental variables
Incremental dividend decisions and managerial alignment/governance: accounting for selection bias. Selection model (maximum likelihood Probit model with selection) of the likelihood of dividend changes: any changes (D_DIV_CHANGE), increase (D_DIV_INCR), decrease (D_DIV_DECR). Selection equation includes STATE_LAWS, CASH_FLOW, SIZE(SALES), MED_LAG_DIVt_1, D_HITECH, CEO_OWN, CEO_OPTIONS, and year dummies. Robust standard errors (clustering by firm id) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria and variables are defined in Appendix A.
ANY CHANGE INCREASE DECREASE I II III IV V VI AGI -1.421 *** -2.205 *** 1.495 *** (.349) (.352) (.331) BOARD_MONIT -0.977 *** -1.395 *** 0.815 ** (.257) (.269) (.270) INST_MONIT -1.329 *** -1.641 *** 0.730 ** (.206) (.216) (.234) CEO_CHARACT 0.170 0.314 * -0.258 * (.123) (.126) (.124) EXT_GOV 0.091 -0.003 0.167 (.122) (.131) (.110) DUAL_CLASS 0.152 0.225 -0.095 (.144) (.141) (.142) CEO_OWN -0.042 -0.268 0.142 -0.129 -0.288 -0.158 (.650) (.653) (.634) (.638) (.80) (.777) CASH_FLOW 1.735 ** 1.244 * 3.739 *** 3.164 *** -4.105 *** -3.847 *** (.628) (.590) (.691) (.673) (.626) (.636) SIZE 0.065 -0.008 0.117 0.031 -0.121 ** -0.092 * (.048) (.048) (.051) (.054) (.042) (.046) GROWTH_OPP -0.074 -0.093 0.065 0.045 -0.189 -0.175 (.125) (.122) (.136) (.131) (.175) (.172) INV_OPP 0.161 * 0.139 * 0.085 0.064 0.090 * 0.097 * (.076) (.066) (.060) (.053) (.041) (.041) RISK_1 -0.009 -0.022 -0.040 -0.055 * 0.065 * 0.069 ** (.027) (.027) (.027) (.027) (.027) (.027) RISK_2 0.008 0.126 -1.974 -1.825 1.764 1.617 (2.050) (2.072) (2.061) (2.084) (2.570) (2.580) CEO_OPTIONS -0.088 * -0.064 † -0.125 *** -0.095 * 0.078 * 0.069 † (.035) (.034) (.039) (.040) (.034) (.036) ANALYSTS -0.007 -0.011 -0.006 -0.010 -0.007 -0.005 (.007) (.007) (.008) (.007) (.007) (.007) LIQUIDITY 0.308 0.324 0.041 0.058 0.425 * 0.419 * (.222) (.224) (.132) (.131) (.177) (.174) TAX 0.009 0.009 0.018 * 0.018 * -0.012 -0.012 (.009) (.008) (.008) (.008) (.014) (.013) MED_CHANGE 0.627 * 0.642 * 2.378 *** 2.358 ** -3.457 *** -3.491 *** (.304) (.306) (.725) (.750) (.613) (.632)
-0.143 -0.240 † -0.017 -0.144 -0.366 * -0.342 * Corr. betw sel-n & reg. eqs. (rho) (.144) (.136) (.147) (.167) (.144) (.153) Number of obs. 9854 9854 9854 9854 9854 9854 Censored obs. 4290 4290 4290 4290 4290 4290 Number of groups 1609 1609 1609 1609 1609 1609 Chi2 0.955 2.861 0.014 0.717 5.337 4.206 AIC 17106.0 17006.3 17023.9 16879.0 13515.2 13508.3 BIC 17732.1 17661.1 17649.9 17533.8 14119.6 14141.5
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
52
Table 7A. Dynamic dividend behavior and managerial alignment/governance: endogeneity and instrumental variables estimation
Dynamic dividend behavior and managerial alignment/governance: testing and accounting for endogeneity. OLS (Columns I-II) and instrumental variables estimation (Columns III-IV) of changes in dividends (DIV_CHANGE). Instrumented variables are CEO_OWN and AGI (Column III); CEO_OWN, BOARD_MONIT, INSTIT_MONIT, CEO_CHARACT, EXT_GOV, DUAL_CLASS (Column IV). Robust standard errors (clustering by firm id) are reported. Test statistics for test of orthogonality of suspect governance variables (Columns I-II) and Hansen J statistic for overidentification test of instruments (Columns III-IV) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria, variables, and instruments are defined in Appendix A.
OLS IV I II III IV AGI -0.118 ** -0.303 *** (.046) (.067) BOARD_MONIT -0.100 ** -0.087 * (.032) (.037) INST_MONIT -0.098 *** -0.097 ** (.029) (.036) CEO_CHARACT 0.039 * 0.042 * (.016) (.016) EXT_GOV 0.033 * 0.024 (.016) (.019) DUAL_CLASS 0.015 0.068 ** (.014) (.021) CEO_OWN 0.232 ** 0.148 † 0.154 † 0.101 (.079) (.078) (.089) (.087) CASH_FLOW 0.497 *** 0.468 *** 0.484 *** 0.476 *** (.075) (.075) (.074) (.074) SIZE -0.002 -0.006 -0.007 -0.007 (.005) (.005) (.005) (.006) GROWTH_OPP 0.036 0.031 0.034 0.031 (.022) (.022) (.022) (.022) INV_OPP -0.001 -0.003 -0.001 -0.003 (.006) (.005) (.006) (.006) RISK_1 -0.003 -0.005 -0.001 -0.004 (.003) (.003) (.003) (.003) RISK_2 -0.300 -0.292 -0.302 -0.287 (.302) (.304) (.303) (.304) CEO_OPTIONS -0.001 0.000 -0.002 0.000 (.004) (.004) (.004) (.004) ANALYSTS 0.002 * 0.002 * 0.002 * 0.002 * (.001) (.001) (.001) (.001) LIQUIDITY 0.035 * 0.035 * 0.037 * 0.035 * (.018) (.018) (.018) (.018) TAX 0.001 0.001 0.001 0.001 (.001) (.001) (.001) (.001) MED_CHANGE 0.983 *** 0.979 *** 0.990 *** 0.982 *** (.166) (.166) (.166) (.166) Number of obs. 5438 5438 5438 5438 Number of groups 767 767 767 767 Anderson canon. corr. LR 2436.7 *** 3163.0 *** Suspect var. orthog. (C stat) 9.735 ** 13.683 * Overid. (Hansen J stat) 7.087 15.405 R2 0.190 0.196 0.186 0.194 Adj. R2 0.180 0.185 0.176 0.183
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
53
Testing for instrument relevance (first stage)
Column III. Instrumented variables: AGI, CEO_OWN. Instruments: STATE_LAWS, MED_INT_CEO, MED_CEO_OWN, MKTBPR_AGI, MKTBPR_CEO_OWN, MARKET_SHARE, D_HITECH, TAKEOVERS_YR_ENTRY.
Shea Partial R2 Partial R2 F stat CEO_OWN 0.764 0.791 555.6 ***
AGI 0.362 0.374 108.9 ***
Cragg-Donald weak id. test 379.0 ***
Cragg-Donald underid. test 3074.2 ***
Anderson canon. corr. LR statistic 2436.7 *** (identification/IV relevance test)
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10% Column IV. Instrumented variables: BOARD_MONIT, INSTIT_MONIT, CEO_CHARACT, EXT_GOV, DUAL_CLASS, CEO_OWN. Instruments: MED_BOARD_MONIT, MED_INSTIT_MONIT, MED_CEO_CHARACT, MED_SEPARATION, MED_EXT_GOV, MED_CEO_OWN, MKTBPR_BOARD_MONIT, MKTBPR_INSTIT_MONIT, MKTBPR_CEO_CHARACT, MKTBPR_EXT_GOV, MKTBPR_CEO_OWN, BLOCKHR_FOCUS, BLOCKHR_INVOLVEMENT, BLOCKHR_ATTENTION_SPAN, MARKET_SHARE, D_HITECH, TAKEOVERS_YR_ENTRY.
Shea Partial R2 Partial R2 F stat
CEO_OWN 0.786 0.793 306.7 *** BOARD_MONIT 0.770 0.785 643.7 *** INSTIT_MONIT 0.597 0.597 96.9 *** CEO_CHARACT 0.765 0.770 741.7 *** EXT_GOV 0.723 0.738 400.2 *** DUAL_CLASS 0.443 0.459 21.7 ***
Cragg-Donald weak id. test 234.7
Cragg-Donald underid. test 4290.4 ***
Anderson canon. corr. LR statistic 3163.0 *** (identification/IV relevance test)
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
Note: For the underidentification test, Ho: matrix of reduced form coefficients is underidentified (has rank K-1). Ha: matrix has rank>=K (identified). For more on instrument relevance and weak instrument tests, see, Staiger and Stock (1997), Shea (1997), Cragg and Donald (1993), Stock and Yogo (2002).
54
Table 7B. Incremental dividend decisions and managerial alignment/governance: endogeneity
Incremental dividend decisions and managerial alignment/governance: endogeneity. Amemiya Generalized Least Squares Probit estimation with endogenous predictors of the likelihood of dividend changes: any changes (D_DIV_CHANGE), increase (D_DIV_INCR), decrease (D_DIV_DECR). Instrumented variables are CEO_OWN and AGI (Column I, III, V); CEO_OWN, BOARD_MONIT, INSTIT_MONIT, CEO_CHARACT, EXT_GOV, DUAL_CLASS (Column II, IV, VI). Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria, variables, and instruments are defined in Appendix A.
ANY CHANGE INCREASE DECREASE I II III IV V VI AGI -3.224 *** -4.121 *** 2.045 *** (.365) (.375) (.504) BOARD_MONIT -0.998 *** -1.410 *** 0.714 ** (.197) (.203) (.271) INST_MONIT -1.456 *** -1.777 *** 0.958 *** (.189) (.191) (.267) CEO_CHARACT 0.189 † 0.304 ** -0.283 * (.097) (.10) (.137) EXT_GOV -0.022 -0.145 † 0.264 * (.086) (.087) (.118) DUAL_CLASS 0.577 *** 0.638 *** -0.207 (.141) (.139) (.184) CEO_OWN -0.711 -0.757 -0.343 -0.388 -1.024 -0.906 (.465) (.479) (.479) (.494) (.734) (.759) CASH_FLOW 1.664 *** 1.359 *** 3.453 *** 3.089 *** -4.088 *** -3.778 *** (.319) (.325) (.324) (.333) (.444) (.460) SIZE 0.042 0.011 0.066 0.029 -0.056 -0.022 (.026) (.028) (.027) (.029) (.035) (.039) GROWTH_OPP -0.095 -0.117 0.047 0.026 -0.224 -0.212 (.106) (.106) (.109) (.109) (.143) (.143) INV_OPP 0.159 *** 0.134 *** 0.090 *** 0.065 * 0.089 * 0.097 ** (.029) (.029) (.027) (.027) (.035) (.035) RISK_1 0.013 -0.015 -0.014 -0.045 * 0.060 * 0.067 ** (.019) (.019) (.019) (.019) (.025) (.025) RISK_2 -0.078 0.014 -2.178 -2.012 1.849 1.706 (1.774) (1.779) (1.858) (1.866) (2.435) (2.447) CEO_OPTIONS -0.108 *** -0.086 *** -0.131 *** -0.103 *** 0.042 0.036 (.020) (.020) (.021) (.021) (.026) (.027) ANALYSTS -0.009 * -0.011 ** -0.006 -0.009 * -0.007 -0.005 (.004) (.004) (.004) (.004) (.006) (.006) LIQUIDITY 0.314 *** 0.323 *** 0.069 0.078 0.417 *** 0.408 *** (.098) (.098) (.099) (.099) (.111) (.112) TAX 0.009 0.009 0.018 0.017 -0.011 -0.012 (.011) (.011) (.012) (.012) (.016) (.016) MED_CHANGE 0.653 ** 0.658 ** 2.412 *** 2.347 *** -3.592 *** -3.639 *** (.239) (.238) (.326) (.324) (.527) (.523) Number of obs. 5564 5564 5438 5438 5564 5564 Number of groups 787 787 767 767 787 787 Pseudo R2 0.094 0.101 0.150 0.161 0.146 0.151 Chi2 676.8 725.8 1115.4 1193.8 506.2 523.1 AIC 6637.7 6596.7 6442.6 6372.3 3090.3 3081.3 BIC 7081.5 7067.0 6884.9 6841.0 3514.2 3531.8
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
55
Table 8A. Dividend variability and managerial alignment: endogeneity and selection Dividend variability and managerial alignment/governance: testing for endogeneity and selection. OLS (Columns I-II) and selection model (full maximum likelihood estimation) (Columns III-IV) of annual standard deviation of quarterly ordinary dividends (DIVt). Selection equation includes STATE_LAWS, CASH_FLOW, SIZE(SALES), MED_LAG_DIVt_1, D_HITECH, CEO_OWN, CEO_OPTIONS, and year dummies. Robust standard errors (clustering by firm id) are reported. Test statistics for test of orthogonality of suspect governance variables (Column I: CEO_OWN, AGI; Column II: CEO_OWN, BOARD_MONIT, INSTIT_MONIT, CEO_CHARACT, EXT_GOV, DUAL_CLASS) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria, variables, and instruments are defined in Appendix A.
Testing for endogeneity Heckman selection I II III IV AGI 1.585 *** 1.591 *** (.436) (.436) BOARD_MONIT 0.859 * 0.859 * (.392) (.392) INST_MONIT 0.951 *** 0.951 *** (.275) (.275) CEO_CHARACT -0.258 -0.258 (.158) (.158) EXT_GOV -0.001 -0.001 (.156) (.157) DUAL_CLASS -0.276 † -0.276 † (.153) (.153) CEO_OWN 0.052 0.565 0.075 0.564 (.722) (.720) (.715) (.711) CASH_FLOW -2.301 *** -2.029 ** -2.388 *** -2.028 ** (.672) (.674) (.702) (.763) SIZE 0.264 *** 0.308 *** 0.256 *** 0.308 *** (.063) (.068) (.063) (.073) GROWTH_OPP -0.034 -0.031 -0.028 -0.031 (.296) (.296) (.297) (.298) INV_OPP 0.018 0.036 0.019 0.036 (.035) (.036) (.035) (.036) RISK_1 -0.006 0.000 -0.007 8.8E-05 (.036) (.034) (.036) (.034) RISK_2 1.927 1.112 1.932 1.111 (3.177) (3.179) (3.179) (3.183) CEO_OPTIONS 0.048 0.032 0.056 0.032 (.044) (.047) (.046) (.052) ANALYSTS -0.025 ** -0.024 ** -0.025 ** -0.024 ** (.009) (.009) (.009) (.009) LIQUIDITY -0.043 -0.065 -0.041 -0.065 (.181) (.182) (.181) (.182) TAX -0.083 -0.082 -0.084 -0.082 (.116) (.113) (.116) (.113) MED_CHANGE 0.205 0.221 0.207 0.221 (.238) (.234) (.238) (.234) MED_SD_DIVt 0.811 *** 0.805 *** 0.811 *** 0.805 *** (.139) (.138) (.139) (.138) Inverse Mills' Ratio (Lambda) -0.062 0.001 (.094) (.201) Number of obs. 1913 1913 9854 9854 Censored obs. 7941 7941 Number of groups 522 522 1598 1598 Instrument orthog. (C stat.) 1.563 6.241 R2 0.278 0.285 Adj. R2 0.252 0.257 Chi2 0.43 0.00 AIC 15303.6 15292.7 BIC 15951.2 15969.1
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
56
Table 8B. Dividend variability, persistence, predictability and dynamic dividend behavior: selection model (cross-section)
Dividend variability, persistence, predictability, dynamic dividend behavior, and managerial alignment/governance: selection model in the cross-section. Selection model (full maximum likelihood estimation) of standard deviation of annual dividends minus lagged dividends, SD_DIFF (Column I) and standard deviation of annual dividend residuals (SD_RESID) computed over the sample period; coefficient of dividend persistence obtained from firm-level regressions of ordinary quarterly dividends, PERSIST (Column III); firm-level fraction of sample period years with annual dividend increases for past dividend payers, P_INCR (Column IV); firm-level fraction of sample period years with annual dividend decreases for past dividend payers, P_DECR (Column V). Selection equation includes STATE_LAWS, CASH_FLOW, SIZE(SALES), MED_LAG_DIVt_1, D_HITECH, CEO_OWN, CEO_OPTIONS, and year dummies. Robust standard errors (clustering by firm id) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria and variables are defined in Appendix A. SD_DIFF SD_RESID PERSIST P_INCR P_DECR I II III IV V AGI 10.975 ** 10.783 ** -0.943 *** -0.652 *** 0.351 ** (3.989) (3.80) (.240) (.156) (.112) CEO_OWN 2.126 1.439 -0.456 0.071 -0.002 (5.796) (5.512) (.559) (.248) (.205) CASH_FLOW -10.683 † -12.294 * 0.789 + 1.197 *** -0.693 *** (6.209) (5.981) (.472) (.282) (.193) SIZE 1.086 * 0.945 * 0.201 *** 0.063 ** -0.024 * (.463) (.437) (.041) (.020) (.012) GROWTH_OPP -6.660 -6.960 † 0.618 * 0.339 ** -0.186 † (4.110) (3.908) (.248) (.120) (.111) INV_OPP 0.538 0.595 0.083 0.032 0.018 (.489) (.469) (.056) (.025) (.016) RISK_1 0.151 0.130 -0.037 -0.016 0.009 (.398) (.376) (.025) (.015) (.008) RISK_2 -59.407 † -54.576 † -2.438 -1.277 0.066 (31.402) (29.950) (1.547) (1.068) (.836) CEO_OPTIONS -0.134 -0.129 -0.088 ** -0.036 * 0.006 (.283) (.267) (.033) (.018) (.010) ANALYSTS -0.074 -0.064 -0.013 ** -0.007 * 0.000 (.082) (.078) (.005) (.003) (.002) LIQUIDITY -4.205 ** -4.009 ** 0.064 0.052 0.173 * (1.475) (1.380) (.176) (.092) (.073) TAX 0.140 0.204 0.019 -0.002 0.007 (.169) (.151) (.017) (.009) (.012) MED_CHANGE -12.723 -16.864 -0.332 0.748 *** -0.628 ** (12.485) (11.821) (.404) (.206) (.210) Inverse Mills' Ratio (Lambda) -1.935 *** -1.815 *** 0.476 *** -0.006 -0.009 (.439) (.399) (.145) (.066) (.011) Number of obs. 1609 1609 1609 1609 1609 Censored obs. 908 908 834 822 822 Chi2 21.64 23.39 11.29 0.01 0.8 AIC 6601.0 6527.5 3000.2 2296.5 1652.9 BIC 6961.6 6888.2 3360.9 2657.2 2013.5
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
57
Table 9. Type of payout policy change and managerial alignment/governance Type of payout policy change and managerial alignment/governance. Multinomial Logit estimation of the likelihood of different payout policy changes. The dependent variable is UPWARD_CHANGE (Columns I-II), DOWNWARD_CHANGE (Columns III-IV). The reported results compare the likelihood of an increase in dividends versus an increase in repurchases, without an increase in dividends (Columns I-II); the likelihood of a decrease in dividends versus a decrease in repurchases, without a decrease in dividends (Columns III-IV). Robust standard errors (clustering by firm id) are reported. Industry dummies, year effects, and intercept are included but not reported. Sample selection criteria and variables are defined in Appendix A.
Increase Dividends vs
Increase Repurchases Only Decrease Dividends vs
Decrease Repurchases Only I II III IV AGI -3.472 *** 3.161 *** (.897) (.709) BOARD_MONIT -1.972 *** 1.640 ** (.617) (.579) INST_MONIT -2.101 *** 1.564 ** (.491) (.512) CEO_CHARACT 0.271 -0.680 * (.301) (.270) EXT_GOV -0.248 0.191 (.283) (.235) DUAL_CLASS 0.651 † -0.313 (.372) (.299) CEO_OWN -0.959 -1.154 -1.207 -0.447 (1.217) (1.236) (1.618) (1.578) CASH_FLOW 2.639 * 1.993 -9.467 *** -8.940 *** (1.303) (1.278) (1.496) (1.524) SIZE 0.087 0.002 -0.089 -0.039 (.114) (.111) (.082) (.090) GROWTH_OPP 0.651 † 0.594 -0.242 -0.186 (.380) (.370) (.357) (.354) INV_OPP 0.100 0.074 0.213 * 0.228 ** (.136) (.114) (.089) (.086) RISK_1 -0.078 -0.095 0.085 0.101 † (.064) (.063) (.054) (.053) RISK_2 4.937 4.670 2.966 2.847 (5.125) (5.188) (5.541) (5.531) CEO_OPTIONS -0.285 *** -0.256 *** 0.064 0.051 (.069) (.068) (.062) (.066) ANALYSTS 0.007 0.003 -0.016 -0.013 (.019) (.019) (.015) (.015) LIQUIDITY -0.254 -0.228 1.063 + 1.068 * (.280) (.276) (.544) (.539) TAX 0.031 * 0.031 * -0.011 -0.012 (.014) (.014) (.027) (.024) MED_CHANGE 5.646 *** 5.738 *** -6.764 *** -6.764 *** (1.697) (1.772) (1.290) (1.295) Number of obs. 5564 5564 5564 5564 Pseudo R2 0.151 0.165 0.081 0.083 *** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
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Table 10. Governance quality and market reaction to announcements of dividend decreases
Market reaction to announcements of dividend decreases, the dependent variable is CAR_DECREASE ([-1, +1] cumulative abnormal return on announcement). Sample selection criteria and variables are defined in Appendix A.
I II III
coef. t-stat coef. t-stat coef. t-stat
DIV_CHANGE 0.036 4.07 *** 0.033 4.95 *** 0.045 5.14 ***
BOARD 0.003 2.05 **
INST -1.8E-04 -0.15
EXT_GOV -0.022 -1.47
Obs. 548 885 501
R2 0.036 0.026 0.047
Adj. R2 0.033 0.024 0.044 *** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
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Table 11. Aggregate Governance Factors and dynamic dividend behavior OLS IV AFACTOR1 -0.012 ** -0.008
(.004) (.007)
AFACTOR2 -0.035 *** -0.069 *
(.009) (.031)
AFACTOR3 -0.007 0.019
(.005) (.041)
AFACTOR4 -0.030 † -0.047
(.017) (.031)
AFACTOR5 -0.003 0.009
(.006) (.021)
AFACTOR6 0.023 0.058 **
(.015) (.021)
AFACTOR7 0.034 * 0.036 *
(.014) (.016)
CEO_OWN 0.201 * 0.184 *
(.081) (.086)
CASH_FLOW 0.458 *** 0.449 ***
(.076) (.079)
SIZE -0.006 -0.008
(.007) (.010)
GROWTH_OPP 0.033 0.027
(.022) (.023)
INV_OPP -0.002 -0.001
(.006) (.006)
RISK_1 -0.004 -0.003
(.003) (.004)
RISK_2 -0.341 -0.389
(.312) (.323)
CEO_OPTIONS -0.001 0.000
(.004) (.004)
ANALYSTS 0.001 + 0.001
(.001) (.001)
LIQUIDITY 0.037 * 0.038 *
(.018) (.018)
TAX 0.001 0.001
(.001) (.001)
MED_CHANGE 0.976 *** 0.971 ***
(.166) (.168)
Number of obs. 5438 5438
Anderson stat 147.0 ***
Cragg-Donald stat 149.0 ***
C stat 17.4 *
Hansen J stat 24.7 7.1
R2 0.197 0.190
Adj. R2 0.186 0.179
*** significance at 0.1%; ** significance at 1%; * significance at 5%; † significance at 10%
Factor analysis results Eigenvalue Proportion Cumulative Factor1 Institutional blockholders 5.070 0.288 0.288 Factor2 Board structure and director duties 2.991 0.170 0.458 Factor3 CEO on key committees 2.243 0.128 0.586 Factor4 Institutional ownership concentration 1.582 0.090 0.676 Factor5 Takeover defenses 1.304 0.074 0.750 Factor6 Separation of voting/cash flow rights 1.088 0.062 0.812 Factor7 CEO characteristics 1.053 0.060 0.872
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Aggregate Governance Factors: factor loadings F1 F2 F3 F4 F5 F6 F7 Advance notice requirement -0.03 0.12 -0.01 -0.15 0.41 -0.11 -0.10 Antigreenmail -0.01 0.24 0.00 -0.08 0.08 -0.03 0.03 Blank check 0.01 0.04 0.00 -0.10 0.23 -0.03 -0.05 Compensation plan 0.03 0.31 -0.02 -0.07 0.13 -0.09 -0.10 Classified board 0.04 0.11 0.01 0.04 0.47 -0.08 -0.03 Cumulative voting -0.04 0.13 -0.01 0.08 -0.20 -0.01 0.03 Cumulative voting for substantial shareholder 0.00 0.06 0.00 0.00 0.02 -0.02 -0.02 Director indemnification -0.10 0.47 -0.03 0.05 -0.05 0.10 0.16 Indemnification contracts -0.04 0.31 -0.02 0.03 -0.01 0.02 0.06 Director liability -0.12 0.60 -0.01 -0.06 -0.05 0.10 0.20 Director duties - nonfinancial impact -0.02 0.04 0.01 0.06 0.28 0.05 0.02 Fair price provision -0.08 0.34 -0.03 -0.04 0.26 -0.02 0.01 Golden parachute 0.14 0.29 0.00 0.03 0.21 -0.14 -0.23 Limits to amend bylaw -0.01 0.00 -0.03 0.02 0.45 0.02 0.07 Limits to amend charter 0.00 0.02 0.00 0.04 0.16 0.02 0.00 Limits on calling special meetings -0.04 0.07 -0.04 -0.14 0.56 -0.09 -0.03 Limits on acting by written consent -0.01 0.04 -0.05 -0.09 0.60 -0.05 -0.03 Pension parachute 0.02 0.22 -0.05 -0.05 0.07 0.01 -0.02 Poison pill 0.07 0.30 -0.01 0.03 0.26 -0.23 -0.15 Secret ballot -0.12 0.25 -0.03 -0.31 0.04 -0.02 -0.01 Severance agreement -0.01 -0.16 -0.02 -0.02 -0.04 0.05 0.08 Silver parachute -0.02 0.17 -0.01 -0.09 -0.01 -0.03 -0.01 Supermajority to approve mergers 0.01 0.13 0.03 0.09 0.25 0.04 0.06 Unequal voting -0.02 0.08 0.02 0.11 0.08 0.04 0.02 Ranking, largest institutional investor stake 0.85 -0.02 -0.01 -0.08 -0.03 -0.02 0.01 Ranking, largest 'other institutional investor' stake 0.57 0.04 -0.02 -0.07 -0.01 0.02 -0.01 Ranking, largest public pension fund stake 0.31 0.02 0.01 0.14 0.01 0.09 -0.03 Dummy, blockholder 0.80 -0.08 0.02 -0.06 0.04 -0.05 -0.05 Dummy, public pension fund blockholder 0.79 -0.11 0.02 0.20 0.01 -0.01 -0.03 Raning, low number of institutional owners 0.38 -0.24 0.03 0.85 -0.05 -0.02 -0.01 Ranking, low number of public pension fund owners 0.24 -0.31 0.02 0.82 -0.05 -0.04 -0.02 Ranking, concentration of institutional ownership 0.74 -0.10 0.01 0.40 -0.05 0.00 0.06 Ranking, concentration of institutional blockholdings 0.90 -0.06 0.01 0.22 -0.04 -0.02 0.04 Ranking, high fraction of independent directors 0.06 0.49 -0.01 -0.15 0.05 -0.15 -0.30 Ranking, low fraction of employee directors 0.05 0.50 0.02 -0.11 0.06 -0.09 -0.30 Ranking, board meetings -0.03 0.18 -0.02 -0.17 0.04 -0.05 -0.18 Ranking, small board size 0.18 -0.39 -0.03 0.29 -0.17 -0.13 -0.04 CEO as chairman 0.02 0.18 0.02 -0.17 0.07 -0.06 0.29 CEO on a key committee 0.02 -0.04 0.98 0.03 0.03 0.00 0.03 CEO on compensation committee 0.01 -0.08 0.37 0.03 -0.04 0.01 0.13 CEO on nominating committee 0.01 -0.01 0.91 0.02 0.05 -0.02 -0.03 CEO on governance committee 0.00 0.06 0.50 -0.03 0.03 0.01 -0.07 CEO on audit committee -0.01 -0.03 0.26 0.01 -0.05 0.02 0.05 CEO interlock -0.06 -0.11 0.05 0.07 -0.02 0.05 0.20 Ranking, CEO age 0.00 0.18 0.04 -0.09 0.04 -0.02 0.51 Dummy, CEO > 65 0.03 -0.03 0.03 0.03 0.00 0.01 0.48 Ranking, CEO tenure 0.00 -0.10 0.02 0.02 -0.07 0.01 0.42 Wedge between cash flow and voting rights 0.04 -0.08 0.01 0.02 -0.04 0.79 0.01 DUAL_CLASS 0.05 -0.10 0.04 0.02 -0.04 0.81 0.03