Journal of Management Studies ••:•• 2009
doi: 10.1111/j.1467-6486.2009.00861.x
Relative CEO Underpayment and CEO Behaviour
Towards R&D Spending
joms_861
1..28
Eric A. Fong
University of Alabama in Huntsville
abstract Arguments based on labour market theory suggest that there may be CEO
behavioural issues related to pay deviations from the labour market rate for CEO pay;
however, few studies examine this phenomenon. This study attempts to address such
behavioural issues by examining the influence of relative CEO underpayment on reductions
in R&D spending, the differences in this relationship between firms in high R&D intensive
versus low R&D intensive industries, and the moderating affect of ownership structure on
the CEO underpayment and R&D spending relationship. Results suggest that relative CEO
underpayment is associated with reductions in R&D spending in low R&D intensive industries
and increases in R&D spending in high R&D intensive industries. Also, greater relative
CEO underpayment leads to greater reductions in R&D spending in manager-controlled
organizations as compared to owner-controlled organizations. This study provides evidence
that pay deviations may, in fact, affect certain CEO behaviours, specifically relating to
innovation.
INTRODUCTION
Given the expectation that chief executive officers (CEOs) play a major role in firm
performance ( Jensen and Murphy, 1990), a large stream of literature has been devoted
to the motivational effects of CEO compensation relating to firm performance. Interestingly, most of these studies focus on the relationship between CEO pay and performance and assume that CEO behaviour will adhere to such alignment (i.e. CEO pay
indirectly affects firm performance through CEO behaviour; Devers et al., 2007).
However, despite the multitude of studies on CEO pay, little is known about CEO
behaviour based on their compensation. This may be, in part, because it is difficult to
pinpoint the many forces acting on both CEO behaviour and the CEO pay setting
process. For example, compensation committees must balance opposing social and
political forces that affect the pay setting process and thus both CEO pay and CEO
behaviour. However, Ezzamel and Watson (1998, 2002) and Miller (1995) suggest that
Address for reprints: Eric A. Fong, Department of Management & Marketing, College of Business Administration, University of Alabama in Huntsville, 202 Business Administration Building, Huntsville, AL 35899,
USA ([email protected]).
© Blackwell Publishing Ltd 2009. Published by Blackwell Publishing, 9600 Garsington Road, Oxford, OX4 2DQ, UK
and 350 Main Street, Malden, MA 02148, USA.
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E. A. Fong
CEO pay equity (i.e. fairness), or pay deviations, may be one particular social force that
may provide a fruitful avenue of research with regard to understanding CEO behaviour.
In essence, they argue that CEO behaviours may be tied to their relative, rather than
absolute, pay; yet, little has been done to examine the relationship between CEO pay,
particularly pay deviations, and CEO behaviour.
CEO behaviour towards research and development (R&D) spending may provide
insight into CEO pay deviations and CEO behavioural issues given that R&D spending
is directly influenced by the CEO and is related to both firm performance and CEO pay
(Cheng, 2004). Although innovation, and thus R&D spending, is important for creating
firm value and a sustainable competitive advantage (Lev and Sougiannis, 1996), research
shows that CEOs will opportunistically target R&D spending because R&D projects are
associated with information asymmetry and risk (Aboody and Lev, 2000; Kothari et al.,
2002). Because R&D spending is negatively associated with CEO pay (Bizjak et al.,
1993), CEOs may manipulate R&D spending as a means of increasing their pay. In light
of this research, this paper examines opportunistic CEO behaviour concerning R&D
spending when CEOs are underpaid relative to their labour market wage rate. In doing
so, this study attempts to contribute to two areas: (1) the study attempts to advance the
social comparison research by showing that CEO pay deviations, specifically CEO
underpayment relative to the labour market, is associated with CEO behaviour that may
impact firm performance through R&D spending; (2) this study attempts to extend the
agency theory research on the alignment between CEO pay and performance to show
that there may be value in aligning CEO pay with CEO behaviour (e.g. CEO actions
towards R&D spending) and thus compensation committees may benefit by making a
greater portion of a CEO’s pay contingent on the CEO’s behaviour.
Controlling for industry and using time- and CEO-level variables from a sample of
large publicly-traded corporations in the United States, I examine whether relative CEO
underpayment affects R&D spending. Also, given the differences between CEO compensation contracts in high versus low technology firms (Balkin et al., 2000), I examine
the possibility that industry type (high versus low R&D intensity) moderates the relationship such that the effect of CEO underpayment on R&D spending will be weaker in high
than in low R&D intensive industries. Finally, because reducing R&D spending can hurt
long-term profitability, CEOs facing less monitoring from firm owners may be more
likely to influence R&D without punishment and thus I examine the possible moderating
effect of ownership structure on the relationship between relative CEO underpayment
and reductions in R&D spending. Prior to these examinations I review the R&D
spending, CEO labour market comparisons, and ownership structure literatures. I conclude with the implications for the literatures on CEO pay and innovation, as well as the
implications for the CEO pay setting process.
THEORY AND HYPOTHESES
CEO Pay and CEO Behaviour Towards R&D Spending
In a meta-analytic review of CEO pay studies, Tosi et al. (2000) find a weak relationship
between pay and performance; however, compensation researchers suggest these equivo© Blackwell Publishing Ltd 2009
Relative CEO Underpayment and R&D Spending
3
cal results are not surprising given firm performance is a function of both CEO behaviours and forces outside of the CEO’s control (Devers et al., 2007; McGahan and Porter,
1997; Yermack, 1997). Thus, CEO compensation research has begun to move beyond
focusing on the relationship between pay and performance and to examining the direct
behavioural outcomes of aligning CEO pay with firm performance. The proposition that
the alignment of pay with performance should motivate CEOs to engage in actions that
maximize long-term firm performance is grounded in agency theory. Similarly, the
research examining CEO pay and more specific CEO behaviours, such as accounting
manipulations and fraudulent financial reporting, when CEO pay is aligned with firm
performance, is also grounded in agency theory (e.g. Burns and Kedia, 2006; Donoher
et al., 2007; O’Conner et al., 2006).
Agency theory ( Jensen and Meckling, 1976) focuses on control issues resulting from
conflicts of interest between shareholders and managers and conceptualizes controls in
the form of optimal contracts designed to correct these conflicts (see Eisenhardt, 1989, for
an overview of agency theory). Because CEOs control organizational resources and are
likely to have firm specific information difficult for owners to obtain (i.e. information
asymmetry), the possibility for moral hazard (CEO behaviours that reduce shareholder
value for the CEO’s self-interests) exists (Rutherford et al., 2007). Agency research
recognizes that CEOs’ and shareholders’ interests diverge with respect to firm risk, with
CEOs’ preferences for less firm risk and shareholders’ preferences for more firm risk (e.g.
Beatty and Zajac, 1994; Tosi and Gomez-Mejia, 1989). Differences occur because CEOs
are less diversified than shareholders and both the CEO’s pay and employment is tied
to the firm; thus CEOs prefer short-term outcomes that have inherently less risk than
long-term outcomes. Fama (1980) suggests that managerial time horizons influence the
degree to which a manager will ‘over consume’ from their present position. The tendency is towards immediate gain; long-term incentives should reduce this tendency given
that long-term incentives impose an ex-post settlement such that current over consumption leads to future losses.
However, the results surrounding the line of research examining CEO pay and CEO
behaviours when pay is aligned with long-term performance (i.e. a situation with ex-post
settlement) are disappointing (see Devers et al., 2007, for an overview). For example,
O’Conner et al. (2006) showed a positive relationship between annual stock options and
fraudulent financial reporting under certain power conditions even though CEO pay was
aligned with long-term performance. In essence, CEO behaviours were towards shortterm outcomes through manipulating short-term firm performance to receive higher
short-term pay despite having their pay aligned with long-term performance, meaning
the CEO could face long-term compensation losses for taking these short-term actions.
This is not surprising given that Fama (1980) notes that situations may exist where
anticipated future wage changes (i.e. long-term incentives) may not be sufficient to
reduce short-term overconsumption. Thus, the research on opportunism suggests that
some CEOs will pursue their own preferences, which tend to be short-term, whether
those preferences are aligned with shareholders or not.
Reductions in R&D spending, as a form of opportunism, merits considerable attention
because R&D spending is a primary input into innovation (Heeley et al., 2007) and thus
a firm’s competitive advantage (Makri et al., 2006). Furthermore, innovation is an
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E. A. Fong
inherently risky endeavour (Kothari et al., 2002) and reductions in R&D can quickly
increase a firm’s short-term market performance at the expense of innovation and
long-term returns. R&D investments also inherently involve information asymmetry
between principals and agents (Clinch, 1991), even in high technology firms (Aboody
and Lev, 2000). Jensen and Meckling (1976) suggest that CEOs should possess the most
knowledge about the firm, which implies that CEOs should have a better understanding
than owners about the optimal level of R&D spending, thus allowing for more informed,
opportunistic action by the CEO. This information asymmetry allows CEOs to make
opportunistic reductions in R&D spending, which Knight (2002) and O’Conner et al.
(2006) note is problematic because decisions that benefit short-term performance often
do not lead to long-term benefits for shareholders. These consequences make reductions
in R&D spending relevant because shareholders generally find R&D spending desirable
(Lev and Sougiannis, 1996) due to their interests in greater risk-taking than CEOs and
their interests in long-term firm performance.
More importantly, R&D spending has been found to be negatively associated with
CEO pay (Bizjak et al., 1993). US generally-accepted accounting practice (GAAP)
requires the immediate expensing of R&D spending, and thus a reduction in R&D
spending increases short-term performance through increases in current market and
accounting performance. Similar to the research on accounting manipulations to
increase short-term CEO pay through bonuses (e.g. Healy, 1985) and exercisable options
(Donoher et al., 2007), CEOs may use reductions in R&D spending as a means of
increasing short-term performance to increase their short-term pay through bonuses and
stock options.
In fact, research on R&D spending shows that when a CEO approaches retirement
(the horizon problem) or when the firm faces a potential reduction in firm performance
(the myopia problem) CEOs tend to reduce R&D spending (Baber et al., 1991; Cheng,
2004; Dechow and Sloan, 1991). First, CEOs approaching retirement no longer financially gain from the long-term benefits associated with current R&D spending; instead,
they financially gain when R&D is reduced due to the immediate expensing of R&D
based on GAAP requirements (Dechow and Skinner, 2000). Second, if firm performance
decreases, the CEO could face termination, which again reduces the CEO’s opportunity
to gain from current R&D spending. Given the strategic importance of R&D spending
on long-term firm performance, Cheng (2004) shows that compensation committees will
adjust CEO compensation contracts to reduce opportunistic manipulations of R&D
spending when the firm encounters the horizon problem or the myopia problem, conditions under which R&D manipulation is likely to occur. However, the arguments
provided by agency theory suggest that CEOs may be encouraged to behave opportunistically towards R&D spending outside of the specific conditions presented by the
horizon and myopia problems, which may be when the CEO’s pay deviates from the
labour market rate.
CEO Labour Markets and Relative CEO Pay
The weak relationship between CEO pay and firm performance may also be partially
explained by research suggesting that firm performance is only one of many factors,
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Relative CEO Underpayment and R&D Spending
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including social (e.g. O’Reilly et al., 1988; Wade et al., 2006b) and political (e.g.
Finkelstein and Hambrick, 1988, 1989; Zajac and Westphal, 1995) factors, involved in
the CEO pay setting process. For example, Finkelstein and Hambrick (1988, 1989)
suggest that CEO pay depends on political processes related to power differences
between CEOs and compensation committees. It may be that more powerful CEOs can
override compensation committee recommendations concerning the CEO’s pay, which
may decouple pay and performance. O’Reilly et al. (1988) suggest that a social comparison process occurs when setting CEO compensation contracts such that compensation
committee members use their own pay to determine the focal CEO’s pay. Such social
comparisons may lead to a possible misalignment of pay and performance.
With respect to the social influences on CEO compensation, researchers have begun
to examine CEO reactions to their pay relative to the CEO labour market (e.g. Wade
et al., 2006a; Watson et al., 1996). For instance, Watson et al. (1996) found that a
manager’s level of job satisfaction was related to their relative over- and under-payment
compared to the labour market and not their absolute pay. Wade et al. (2006a) examined
whether relative over- and under- payment compared to the CEO labour market wage
rate (measured using the residuals of a ‘CEO wage equation’) affected lower level
employee compensation as well as the employee’s propensity to turnover. Wade et al.
(2006a) suggest that CEOs may be reacting to issues related to fairness by creating
compensation policies for subordinates that reflect the CEO’s own over- or underpayment relative to the CEO’s labour market. In turn, firm effectiveness may be influenced through high wages for all employees relative to the employees’ labour market rate
or through employee turnover when employee pay was low relative to the employee’s
labour market.
Porac et al. (1999) suggest that the complex causes of organizational outcomes can
motivate, or even necessitate, social comparisons by CEOs and thus they could recognize
the going labour market rate for their services and possible deviations from such rates.
Goodman (1974) suggests that individuals will make comparisons with others who have
similar abilities, which suggests that when CEOs assess their own managerial ability,
performance, and pay, they must make comparisons with other CEOs. These explanations provide some insight into Watson et al.’s (1996) findings that job satisfaction and
relative CEO pay are related as well as Wade et al.’s (2006a) suggestion that CEOs create
compensation policies for subordinates that reflect the CEO’s own relative pay. In spite
of this research showing that CEO pay can deviate from the labour market rate and that
CEOs can recognize such deviations, very little research has examined the potential
negative effects of deviations from the CEO labour market rate.
Through social comparisons, CEOs can recognize that their pay lies above or below
the prevailing labour market rate of pay; however, an underpaid CEO may take action
to remedy the situation. Research using theories based on norms of fairness, such as
equity theory (Adams, 1965) and social comparison theory (Festinger, 1954), show that
relative underpayment leads to actions that may lead to a fairer situation; such actions
can take the form of increasing outcomes or reducing inputs. For example, Greenberg
(1993) shows that underpayment inequity led to increased theft (i.e. increased outcomes)
and both Dittrich and Carrell (1979) and Wade et al. (2006a) show underpayment
inequity led to increased turnover (i.e. reduced inputs). According to Wade et al. (2006a),
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E. A. Fong
all fairness theories share two assumptions: (1) social comparisons are required to determine fairness; and (2) fairness, or lack of fairness, influences people’s responses to these
comparisons. Thus, it is an individual’s relative evaluation of the situation that may
motivate a response to make such an evaluation fair. According to organizational
theorists, this view may be even more salient for CEOs. Marris (1964) and Simon (1947)
both suggest that CEOs place high value on prestige and power. One might view
executives’ pay as a direct reflection of these values; thus, relatively low pay may reflect
relatively low prestige. March (1984, p. 60) notes that ‘compensation schemes reassure
managers that they are important, respected, competent people’. If a CEO receives
relatively low pay, the CEO may have a greater incentive to behave in ways that can lead
to higher pay than a CEO who receives higher pay, all else equal.
As suggested by Miller (1995), equity theory may play a particularly relevant role in
CEO pay deviations. The emphasis in equity theory rests on the notion that individuals
can feel either underpayment inequity or overpayment inequity. With regard to underpayment, CEOs may attempt to reduce inputs (e.g. CEO efforts) or increase outcomes
(i.e. increase pay) to create a more equitable condition. Although it is feasible that CEOs
may attempt to reduce inputs to create a fairer situation, if pay reflects prestige, as is
argued above, then CEO preferences would be towards increasing their outcomes when
underpaid rather than reducing their inputs. Furthermore, the reduction of inputs may
have negative consequences for the CEO, such as dismissal. The information asymmetry
between CEOs and shareholders inherent in R&D spending provides CEOs the opportunity for behaviour towards reducing R&D, which increases outcomes through
increased pay (Bizjak et al., 1993), specifically short-term pay such as bonus and options.
Also, since Fama (1980) argues that CEO time horizons are towards immediate gains
and that situations may exist where long-term incentives may not be enough to encourage the CEO to forgo these immediate gains, CEOs may have the motivation to behave
opportunistically towards R&D spending when underpaid (i.e. current underpayment
may be one condition where ex-post settlement through long-term incentives does not
discourage immediate gains through R&D manipulation). Cheng (2004) shows that
compensation committees must, and do, account for such possible R&D manipulations
when the firm faces the horizon and myopia problems. However, when the horizon and
myopia problems do not exist, the motivation, or incentive, may be the CEO’s relative
underpayment. Thus, underpayment may encourage CEOs to reduce R&D spending.
Hypothesis 1: Relative CEO underpayment will be associated with decreases in R&D
spending.
For the overpaid CEO, although reactions to overpayment may exist, Adams (1965)
suggests that individuals will be less sensitive to overpayment than underpayment situations. One such reason for this lower sensitivity to overpayment is that overpaid
individuals are likely to re-evaluate the situation to make it equitable (i.e. change their
perceptions of the situation to make it fairer). However, even though a change in
perceptions is a likely outcome, if reactions to overpayment do occur then they will be in
the form of increased inputs rather than decreased outcomes (Adams, 1965), which
suggests that overpaid CEOs would appropriately invest in R&D spending. Appropriate
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Relative CEO Underpayment and R&D Spending
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investment could lead the CEO to increase, decrease, or leave R&D spending
unchanged depending upon the organization’s particular circumstance. As such, it
would be difficult to determine the CEO’s actions towards R&D when overpaid.
CEO Incentives in R&D-Intensive Industries
Differences in CEO reactions to underpayment may exist between high and low technology industries. Balkin et al. (2000) note that innovation is more critical for success in
high technology firms than in low technology firms. Thus, the benefits CEOs gain
through information asymmetry in less technology oriented industries may not be the
same in high technology industries given that reductions in R&D spending may signal
that a high technology firm is unsuccessful. Barth et al. (2001) show that high R&D
intensive firms have significantly more analyst coverage than less R&D intensive firms,
which suggests that opportunistic downward adjustments in high R&D intensive firms
are more likely to be noticed. Thus, the market is more likely to catch and punish
downward adjustments in R&D spending in high R&D intensive industries than in low
R&D intensive industries. Aboody and Lev (2000), for example, show that CEOs in high
technology firms are likely to financially benefit from information asymmetry stemming
from the complexity of R&D projects and not necessarily from reductions in R&D. As
such, CEOs may be provided less opportunity in high versus low R&D intensive industries to manipulate R&D for their own self-interests because high R&D intensive industries face greater market oversight and have less information asymmetry related to
reductions in R&D.
Furthermore, given that innovation is a primary requisite for survival in high technology industries (Hamel and Prahalad, 1994), Balkin et al. (2000) show that compensation committees in high technology industries are more likely to align short-term CEO
pay, specifically CEO cash pay (cash and bonus), with R&D spending than compensation committees in low technology industries. Makri et al. (2006) similarly show that
CEO total pay was associated with innovation behaviour in high technology firms. In
essence, both Balkin et al. (2000) and Makri et al. (2006) suggest that compensation
committees are more likely to align CEO pay with behaviours towards R&D in high than
low R&D intensive firms and thus reductions in R&D in high R&D intensive firms may
not lead to short-term pay increases for underpaid CEOs.
However, this does not suggest that R&D spending is not important in low technology
industries. Cohen and Leventhal (1990) suggest innovation improves the quality, cost,
speed, and/or features provided by products and services, which are beneficial improvements in any industry. Low R&D intensive industries still have firms that invest in R&D
given that some firms in these industries may attempt to differentiate their products
and/or services and innovation is one means of pursuing such differentiation; thus,
reductions in R&D may be costly to some firms in these industries. Despite the fact that
R&D investments may be important in low R&D intensive industries, it is clear that
CEO pay alignment with R&D is more likely to occur in high R&D intensive industries
(Balkin et al., 2000; Makri et al., 2006) and thus CEOs in high R&D intensive firms will
be less likely than CEOs in low R&D intensive firms to decrease R&D spending when
underpaid because such decreases are less likely to lead to short-term pay increases.
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E. A. Fong
Hypothesis 2: The association between CEO underpayment and decreases in R&D will
be weaker in high R&D intensive industries than in low R&D intensive industries.
Ownership Structure and CEO Power
Because decisions made by CEOs that benefit short-term performance do not necessarily
benefit shareholders in the form of long-term performance (Knight, 1998; O’Conner
et al., 2006), CEO power is likely to moderate the relationship between CEO underpayment and changes in R&D spending. According to Hambrick and Finkelstein (1987),
power plays a more significant role if the pursuit of action is in opposition to the interests
of owners. Finkelstein (1992) suggests that a CEO’s power will influence a CEO’s ability
to affect firm outcomes.
Prior research on ownership structure suggests that certain ownership conditions
enable CEOs to pursue self-interests (Marris, 1964; Williamson, 1964) and influence the
CEO’s own pay (Finkelstein and Hambrick, 1989; Hambrick and Finkelstein, 1995).
Tosi and Gomez-Mejia (1989, 1994) suggest that CEOs in owner-controlled firms (i.e.
firms with at least one dominant owner) face more effective monitoring activities compared to CEOs in manager-controlled firms. Thus, CEOs in owner-controlled firms
would not be afforded opportunities to adjust R&D spending specifically for their own
benefit. On the other hand, CEOs in manager-controlled firms who are paid below the
labour market rate, accounting for their power (i.e. compared to other CEOs in similar
monitoring conditions), may attempt to indirectly influence their pay through opportunistic changes in R&D spending given that their direct influence has still left them
underpaid compared to other CEOs in similar conditions.
Hypothesis 3: The association between relative CEO underpayment and decreases in
R&D will be stronger in manager-controlled versus owner-controlled firms.
METHODS
Data and Sample
The initial sample consisted of 900 observations from more than 250 CEOs of US
publicly traded corporations from 26 industries (see Appendix for a list of industries by
four-digit SIC code included in the study) randomly selected from the Compustat
database. The archival data were obtained from Compustat, Execucomp, and Compact
Disclosure databases and CEO human capital data, which were hand collected, were
gathered from proxy statements, 10-Ks, annual reports, and the Dun and Bradstreet
Reference Book of Corporate Management for the time period 1991–97. The number of
observations for each CEO varied between 3 and 7 years. The panel is unbalanced
because the number of years of data per CEO varies. After lagging the data one year and
accounting for missing data, the final sample used to test the hypotheses included a total
of 621 observations from 227 CEOs. As with prior research examining CEO pay and
R&D spending (e.g. Cheng, 2004; Dechow and Sloan, 1991), a one year lag is used given
the expectation that prior pay influences current R&D spending. An independent
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Relative CEO Underpayment and R&D Spending
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samples t test was performed on the residual of the CEO wage equation, based on total
CEO pay (described below), to test the differences between the final sample of CEOs and
those that were dropped due to missing data and no differences were found between the
dropped CEOs and those in the final sample. All financial data are adjusted to 1990
dollars using the consumer price index.
Variables
Dependent variable. R&D expenditures are collected from the Compustat database, which
includes both internal R&D spending and acquired in-progress R&D spending in millions. I calculate R&D spending as log of R&D expenditures, to account for extreme
values, at year t; however, the results are similar when this transformation is not used.
Independent variables. Examining relative total pay as well as the separate elements of CEO
compensation structure, relative cash pay (cash and bonus) and relative options pay (all
forms of pay are measured in thousands), may provide insight into whether short- or
long-term incentives influence CEO behaviours towards R&D spending when underpaid. Similar to Wade et al. (2006a), to determine whether a CEO was under- or overpaid
relative to other CEOs, I constructed the following CEO wage equations for total, cash,
and options pay[1] all in year t - 1 where t represents the year that R&D spending (the
dependent variable) is measured given prior pay is likely to affect current R&D spending:
Ln (CEO Total Pay ) = β1 ∗ Experience + β2 ∗ CEO tenure + β3 ∗ Inside CEO +
β 4 ∗ Ln (no. of employees) + β5 ∗ Return on assets +
β6 ∗ Outsider ratio + β7 ∗ Duality.
Year dummies were included for 1992, 1993, 1994, 1995, 1996, and 1997 (1991 was
the omitted reference year). These variables were used to estimate fixed-effects regression models. In this study, the use of fixed effects models is equivalent to adding a
dummy variable for each industry, which controls for unmeasured differences across
industries that may explain pay differences. More importantly, Porac et al. (1999)
suggest that CEOs will likely make within-industry comparisons and propose the use of
a fixed effects model to control for industry in the estimation accounts for these industry comparisons.
CEO under- or overpayment was measured by taking the residuals from the CEO
wage equations. Residuals have been used as independent variables in previous CEO
pay studies (e.g. Carpenter and Sanders, 2002; Wade et al., 2006a). More importantly,
the use of the wage equation to develop residuals accounts for CEO inputs, which are an
important element regarding equity theory and social comparisons (Adams, 1965). Thus
residuals from the wage equation may be more appropriate than using deviations from
the mean CEO pay in the industry, which does not account for CEO inputs. A negative
residual suggested that the CEO was underpaid because the CEO’s actual pay was less
than their predicted pay. A positive residual means that the CEO was overpaid because
the CEO’s actual pay was greater than their predicted pay.
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E. A. Fong
Similar to Wade et al. (2006a), the residuals from the total, cash, and options wage
equations were split to develop variables representing CEO underpayment and CEO
overpayment. CEO underpayment for total, cash, and options was developed by setting the
measures equal to the negative residual values from the wage equations and zero
otherwise. Thus, three CEO underpayment variables, total, cash, and options, were
developed from the three CEO wage equations. The sign was reversed to make the
interpretation of the CEO underpayment variables more clear-cut (i.e. larger positive
values indicated greater underpayment). CEO overpayment, entered as a control, was set
equal to the positive residual values and zero otherwise. Similar to underpayment, three
CEO overpayment variables were developed.
CEO total pay consists of salary, annual bonus, stock options, stock grants, deferred
pay, fringe benefits, and pension accruals. Similar to Murphy (1985), stock options are
valued using a modified version of the Black–Scholes method (Black and Scholes, 1973)
that allows for the inclusion of dividend payments. Stock options are valued only in the
year they were granted. Cash pay consists of salary and annual bonus, consistent with
Balkin et al. (2000) who show that R&D spending may be aligned with short-term
incentives. Options pay consists of stock options and stock grants. As in prior studies (e.g.
Cheng, 2004; Jensen and Murphy, 1990), the log of compensation was used to minimize
heteroscedasticity.
Outsider ratio and duality were included in the wage equations because CEO influence over the compensation committee, a subset of the board, would determine relative
pay, and duality states that the CEO holds multiple positions (i.e. CEO and chairman of
the board) and thus the CEO may expect higher pay. For example, Stevenson and Radin
(2009) show that the influence of the compensation committee is reduced when the CEO
is also the chairman of the board. Rediker and Seth (1995) note that outsider ratio,
calculated as the number of outside directors divided by the total number of directors, is
the most commonly used indicator of governance provided by the board of directors. As
in prior studies (e.g. O’Conner et al., 2006; Wade et al., 2006a), CEO duality is captured
using a dummy variable equal to 1 if the CEO is also the chairman of the board and zero
otherwise. Human capital variables such as experience (i.e. prior position), inside CEO
(whether CEO was an inside promotion or not), and CEO tenure (measured as the number
of years since being appointed to the position of CEO) were included in the wage
equation as research suggests that these factors may influence compensation (Buchholtz
et al., 2003).
Industry type was measured using a dummy variable where industry type = 1 if
the firm is in a high R&D intensive industry and zero otherwise. Similar to Dechow
and Sloan (1991), high R&D intensive industries were identified based on the average
industry ratio of R&D spending to sales. Firms in four-digit SIC code industries
with the average industry R&D/Sales > 5 per cent were coded as in a high R&D
intensive industry. The Appendix shows the list of the industries in this study and
their inclusion as high R&D intensive or not. Industry type serves as a proxy for CEO
pay alignment with R&D spending given that Balkin et al. (2000) and Makri et al.
(2006) provide evidence that compensation committees are more likely to align CEO
pay with behaviours towards R&D in high technology firms than in low technology
firms.
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As with previous studies, ownership structure is assessed using a 5 per cent equityholding threshold (e.g. Hambrick and Finkelstein, 1995; Tosi and Gomez-Mejia, 1989)
and organizations are sorted into three categories: (1) manager-controlled firms, where no
single equity holder owns 5 per cent or more of the organization’s common stock; (2)
owner-managed firms, where the CEO owns 5 per cent or more of the common stock; and
(3) owner-controlled firms, where at least one equity holder, who is not the CEO, owns 5
per cent or more of the common stock. Using dummy variables, I define managercontrolled = 1 if the organization is manager-controlled and zero otherwise, and ownermanaged = 1 if the organization is owner-managed and zero otherwise. Owner-controlled
firms become the omitted reference category in the tests of the hypotheses. The inclusion
of owner-managed as a control is important because research has shown that managerial
ownership reduces opportunism towards R&D spending (Dechow and Sloan, 1991).
Control variables. Rediker and Seth (1995) note that there are many governance mechanisms that may influence the level of control afforded to CEOs and thus institutional
ownership and director ownership are added as controls. Davis and Thompson (1994)
suggest that institutional ownership acts as a governance mechanism. Given the importance
of R&D spending in organizations, institutional ownership may impact the CEO’s
influence over R&D spending. To measure the variable, I used the residuals of a
regression of the average percentage of a firm’s common voting shares held by institutions on the average percentage of 5 per cent block-holding. This eliminates overlap
between the SEC’s 13(f) reporting, which contains the average percentage of a firm’s
common voting shares held by institutions, and the institutional holdings captured in
the CEO ownership categories. Director ownership represents a governance mechanism
(Dalton et al., 2003; Fama, 1980) and thus may influence R&D spending. Director
ownership is measured here as the residuals from a regression of the average percentage
of a firm’s common voting shares held by the board of directors on the average percentage of CEO stock holdings and the average percentage of 5 per cent block-holdings.
Similar to institutional ownership, this procedure removes potential overlap with the
CEO ownership categories.
Prior R&D spending is measured as the log of R&D expenditures at year t - 1 and was
entered as a control. Balkin et al. (2000) note that R&D spending and number of patents
are highly correlated, with number of patents representing innovative output. Thus,
prior R&D spending serves as a proxy for innovative performance.
Research shows an association between R&D spending and both related and unrelated firm diversification (Baysinger and Hoskisson, 1989; Hoskisson and Hitt, 1988).
Xue (2007) suggests that CEO compensation contracts may encourage a ‘make’ or ‘buy’
decision relating to R&D spending and thus acquisitions may be one means of increasing
R&D. However, diversification strategies may take more than one year to become
realized, and thus increases or decreases in R&D based on diversification decisions may
not be compensation dependent (i.e. prior diversification strategies may have become
realized in the current period of analysis). Thus both related diversification and unrelated
diversification are added as controls. Diversification variables are operationalized using the
entropy measure ( Jacquemin and Berry, 1979).
Firm performance was measured using shareholder return and change in shareholder
return (Change in SR). According to Baber et al. (1991), opportunistic reductions in R&D
© Blackwell Publishing Ltd 2009
12
E. A. Fong
spending are more likely to occur when the firm faces an earnings decline and thus both
market performance and changes in market performance were added as controls.
Change in SR was operationalized as (t - [t - 1]), where t represents firm performance in
any given year and t - 1 represents firm performance the prior year.
Dechow and Sloan (1991) suggest that as CEOs approach retirement age they tend to
reduce R&D investment as a means of increasing short-term earnings and thus CEO age
is included as a control.
Real gross domestic product (Real GDP) is entered to control for possible period effects
such as changes in overall economic activity that may affect R&D spending.
Industry will likely play a role in the level of R&D spending a CEO pursues and thus is
accounted for in the estimation procedure (see the data analysis section for further
explanation).
Data Analysis
The study consists of a panel design in the form of repeated observations hierarchically
nested within firms that are hierarchically nested within industries, which requires an
estimation technique able to deal with three levels of analysis. Therefore, this study
incorporates hierarchical linear modelling (HLM; Raudenbush and Bryk, 2002) as the
statistical analytic technique. To analyse changes in R&D spending, the model must
account for time-varying factors (e.g. CEO under- and overpayment, CEO age, etc),
Table I. Descriptive statistics and correlations for the variables use in the tests of the hypothesesa
Variables
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
Mean
S.D.
R&D spending
3.31
2.08
Total CEO underpayment
0.30
0.48
Total CEO overpayment
0.32
0.58
Cash CEO underpayment
0.29
0.44
Cash CEO overpayment
0.31
0.48
Options CEO underpayment
0.34
0.63
Options CEO overpayment
0.38
0.51
Industry type
0.40
0.49
Manager-controlled
0.06
0.24
Owner-managed
0.26
0.44
Unrelated diversification
0.09
0.24
Related diversification
0.03
0.12
Shareholder return
0.26
0.66
Change in SR
-0.04
0.86
CEO age
54.33
8.68
Institutional ownership
0.05
0.22
Director ownership
0.00
0.10
Prior R&D spending
3.18
2.07
Real GDP
8252.16 592.17
Notes: a Correlations are based upon pooled data. n = 621.
* p < 0.05; two-tailed tests.
© Blackwell Publishing Ltd 2009
1
2
3
4
5
6
1.00
-0.11*
0.08*
-0.10*
0.16*
-0.17*
-0.01
0.20*
0.37*
-0.32*
0.11*
0.23*
0.07
-0.03
-0.09*
0.37*
0.09*
0.98*
-0.09*
1.00
-0.35*
0.63*
-0.37*
0.73*
-0.46*
-0.03
-0.04
0.10*
-0.06
-0.05
-0.05
0.07
-0.05
-0.14*
-0.07
-0.11*
0.01
1.00
-0.27*
0.50*
-0.30*
0.85*
-0.06
-0.01
0.08
-0.01
-0.03
0.14*
-0.12*
-0.04
0.10*
0.06
0.07
-0.03
1.00
-0.43*
0.23*
-0.18*
-0.04
-0.04
0.04
-0.07
-0.05
-0.02
0.07
-0.08
-0.11*
-0.08
-0.11*
0.00
1.00
-0.14*
0.25*
-0.04
0.06
0.00
0.03
-0.06
0.01
-0.02
0.09*
0.09*
0.06
0.17*
-0.01
1.00
-0.40*
0.00
-0.074
0.10*
-0.12*
-0.07
-0.03
0.01
0.02
-0.13*
-0.13*
-0.17*
0.02
Relative CEO Underpayment and R&D Spending
13
firm-level factors (manager-controlled, owner-managed, etc), and industry-level differences (the variance in industry differences is explicitly modelled). The partitioning out of
the variance across industries into its own level of analysis in the estimation, as is done in
HLM, effectively controls for industry effects (Bloom and Milkovich, 1998). Also, HLM
allows for the modelling of the within- and between-firm components as well as the
within- and between-industry components simultaneously, which minimizes potential
biases imposed by the violation of independence presented by such nesting (Raudenbush
and Bryk, 2002). The violation of independence may make the use of standard regression
techniques, such as ordinary least squares, inappropriate for the tests of the hypotheses
using this data. Bryk and Raudenbush (1989) state that HLM provides unbiased and
efficient estimates of the regression coefficients and their standard errors, irrespective of
the dependence among individual responses due to the nested nature of the data. In
addition, since the interactions are cross-level interactions (underpayment is a time-level
variable and both industry type and ownership structure are firm-level variables), the use
of HLM is particularly relevant given that HLM appropriately investigates cross-level
interactions (Gavin and Hofmann, 2002; Raudenbush and Bryk, 2002).
RESULTS
Table I displays the descriptive statistics and correlations for the variables in the tests of
the hypotheses. To save space, I only report these statistics for the pooled sample.
7
8
9
10
11
12
13
14
15
16
17
18
1.00
-0.05
-0.03
0.13*
0.01
-0.02
0.11*
-0.10*
-0.04
0.01
0.02
-0.02
-0.02
1.00
0.14*
-0.20*
-0.03
0.12*
0.02
-0.01
-0.02
0.03
-0.03
0.19*
-0.09*
1.00
-0.15*
0.01
0.32*
-0.03
0.01
0.09*
-0.02
0.02
0.37*
-0.06
1.00
-0.15*
-0.11*
0.03
0.03
-0.02
-0.26*
0.06
-0.33*
0.05
1.00
0.24*
-0.05
0.01
0.14*
0.09*
-0.08*
0.13*
-0.09*
1.00
-0.05
0.02
0.09*
0.05
0.04
0.24*
-0.11*
1.00
-0.67*
-0.08*
0.10*
0.16*
0.03
-0.11*
1.00
0.00
-0.03
0.00
-0.01
0.03
1.00
-0.14*
0.00
-0.07
0.02
1.00
-0.04
0.36*
-0.01
1.00
0.07
-0.06
1.00
-0.10*
© Blackwell Publishing Ltd 2009
14
E. A. Fong
Table II. CEO wage equation predicting the log of CEO pay
Variables
Ln(CEO total pay)
Ln(CEO cash pay)
Ln(CEO options pay)
Intercept
5.74***
(0.30)
0.08
(0.06)
-0.01
(0.00)
-0.18*
(0.08)
0.38***
(0.02)
0.02
(0.23)
0.66*
(0.28)
-0.02
(0.08)
-0.26†
(0.14)
-0.34**
(0.13)
-0.23*
(0.11)
-0.23*
(0.11)
-0.03
(0.11)
0.05
(0.10)
0.45
4.96***
(0.22)
0.07†
(0.04)
0.01**
(0.00)
-0.03
(0.06)
0.33***
(0.02)
-0.03
(0.17)
0.54**
(0.20)
0.13*
(0.06)
-0.10
(0.10)
-0.08
(0.09)
-0.06
(0.08)
-0.08
(0.08)
-0.05
(0.08)
-0.09
(0.07)
0.54
4.27***
(0.69)
0.19
(0.13)
-0.04***
(0.01)
-0.38*
(0.18)
0.52***
(0.05)
-0.24
(0.52)
0.74
(0.64)
-0.23
(0.19)
-0.70*
(0.33)
-0.91**
(0.30)
-0.67**
(0.26)
-0.42†
(0.25)
-0.19
(0.24)
0.12
(0.23)
0.33
Experience
CEO tenure
Inside CEO
Ln(no. of employees)
Return on assets
Outsider ratio
Duality
1992
1993
1994
1995
1996
1997
R-squared
Notes:
†
p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001; two-tailed tests. Standard errors are shown in parentheses.
Table II shows the generalized least squares with fixed effects regression coefficients and
standard errors for the CEO wage equations used to determine the CEO under- and
overpayment variables. In general, the findings are consistent with previous research on
CEO pay, which suggests a strong relationship between firm size and CEO pay (e.g. Tosi
et al., 2000). Also, consistent with prior research using residuals from wage equations (e.g.
Wade et al., 2006a), the wage equations explain a significant amount of variance in pay.
Table III displays the results of the HLM analyses used to test the hypotheses. I
estimate 13 models: (1) Model 1, which includes the control variables as well as industry
type and the ownership structure variables; (2) Models 2, 6, and 10, which include the
control variables and adds CEO underpayment in the form of total, cash, and options
pay (the independent variables used to test Hypothesis 1, respectively); (3) Models 3, 7,
and 11, which test Hypothesis 2 by including the interactions between CEO underpayment (total, cash, and options) and industry type; (4) Models 4, 8, and 12, which test
Hypothesis 3 by including the interactions between CEO underpayment and both
© Blackwell Publishing Ltd 2009
Relative CEO Underpayment and R&D Spending
15
manager-controlled and owner-managed firms versus owner-controlled firms; and (5)
Models 5, 9, and 13, which are the full models including all the interactions. Consistent
with HLM guidelines (Raudenbush and Bryk, 2002), the measure of model fit is reported
in the form of a likelihood ratio (LR) test comparing the more complex models to their
respective fully unconditional models with no predictors. The LR test statistic has a
chi-square distribution with degrees of freedom equal to the difference in the number
of parameters between the models (Raudenbush and Bryk, 2002) and, as noted in
Table III, the models are significant. Coefficients are shown as individual gamma
weights, which are analogous to beta weights in traditional regression analysis. However,
given the logarithmic transformation of CEO pay and the splitting of the residuals from
the CEO wage equations to develop CEO under- and over-payment for total, cash, and
options pay, the sizes of the effects are not readily amenable to interpretation. Similar to
Wade et al. (2006a), the focus is on the significance and direction of the coefficients when
determining the support, or lack of support, for the hypotheses. The robust standard
errors automatically generated by the HLM statistical package were used because these
correct for departures from the assumptions of the variance–covariance matrix (i.e.
heteroscedasticity; Raudenbush and Bryk, 2002; Raudenbush et al., 2000). No evidence
of auto-correlation was found using standard tests for auto-correlation (Durbin–Watson
test; see Greene, 2000).
Model 1 provides the effects of the control variables on R&D spending. It is interesting
to note the positive relationship between industry type and R&D spending (g = 0.10;
p < 0.001), which suggests that firms in high R&D intensive industries significantly
increased R&D spending relative to firms in low R&D intensive industries.
Models 2, 6, and 10 show there is no main effect of prior year CEO underpayment on
R&D spending, all else being equal. Thus, Hypothesis 1 is not supported. Models 2, 6,
and 10 also introduce the relationship between CEO overpayment on R&D spending
and it is interesting to note that there is no relationship between CEO overpayment and
R&D spending.
Models 3, 7, and 11 include the interaction of industry type on the relationship
between CEO underpayment and R&D spending. The main effect term for CEO
underpayment, which tests the relationship between underpayment and R&D spending
in low R&D industries, is negative and significant for both total (g = -0.07; p < 0.05) and
cash (g = -0.11; p < 0.05) underpayment, Models 3 and 7 respectively. To reiterate, the
sign was reversed for CEO underpayment and thus the negative relationship suggests
that greater relative underpayment leads to greater reductions in R&D spending. The
interaction term for industry type and CEO underpayment is positive and significant for
Models 3 and 7. The positive coefficients suggest that the negative relationship between
CEO underpayment and R&D spending found in low R&D intensive industries is
weaker in high R&D intensive industries when CEOs are underpaid based on total pay
(g = 0.16; p < 0.01) and cash pay (g = 0.13; p < 0.10). These results support Hypothesis 2.
In fact, Figures 1 and 2 show that CEOs in high R&D intensive industries who are
relatively underpaid based on both total and cash pay increase R&D spending while
underpaid CEOs in low R&D intensive industries decrease R&D spending. As noted
earlier, given the size of the effects are not amenable to interpretation, the Figures reflect
the direction of the tests of the interactions and not the size of their effects.
© Blackwell Publishing Ltd 2009
16
E. A. Fong
Table III. Results of the HLM analysis of R&D spendinga,b
Variables
Controls
Model 1
Intercept
Unrelated diversification
Related diversification
Shareholder return
Change in SR
Real GDP
CEO age
Industry type
Prior R&D spending
Institutional ownership
Director ownership
Manager-controlled
Owner-managed
3.27***
(0.04)
-0.03
(0.05)
-0.03
(0.05)
0.17**
(0.05)
0.06*
(0.03)
0.00***
(0.00)
0.01
(0.00)
0.10***
(0.02)
0.94***
(0.04)
0.44†
(0.24)
0.87†
(0.49)
0.06†
(0.03)
0.00
(0.04)
CEO overpayment
CEO underpayment
Relative total pay
Model 2
3.22***
(0.03)
-0.02
(0.05)
-0.07
(0.08)
0.18***
(0.03)
0.03
(0.05)
0.00*
(0.00)
0.00
(0.01)
0.14***
(0.03)
0.97***
(0.01)
0.24**
(0.08)
0.42**
(0.15)
0.09**
(0.03)
-0.02
(0.03)
0.11
(0.10)
0.07
(0.05)
CEO underpayment ¥ industry type
Model 3
3.23***
(0.03)
-0.04
(0.06)
-0.07
(0.09)
0.18***
(0.04)
0.04
(0.03)
0.00†
(0.00)
0.00
(0.01)
0.13***
(0.03)
0.97***
(0.01)
0.24**
(0.08)
0.39*
(0.17)
0.09**
(0.03)
-0.01
(0.03)
0.12
(0.12)
-0.07*
(0.04)
0.16**
(0.06)
CEO underpayment ¥ manager-controlled
CEO underpayment ¥ owner-managed
Dc2
1075.44*
1056.70*
1068.59*
Model 4
3.22***
(0.03)
-0.01
(0.05)
-0.08
(0.07)
0.17***
(0.03)
0.02
(0.04)
0.00†
(0.00)
-0.01
(0.02)
0.14***
(0.03)
0.97***
(0.01)
0.25**
(0.08)
0.40*
(0.17)
0.10**
(0.03)
0.00
(0.03)
0.14
(0.10)
0.08†
(0.05)
-0.16*
(0.08)
0.02
(0.10)
1064.45*
Model 5
3.22***
(0.03)
-0.01
(0.05)
-0.09
(0.07)
0.17***
(0.03)
0.02
(0.04)
0.00
(0.00)
-0.01
(0.02)
0.15***
(0.03)
0.97***
(0.01)
0.25**
(0.08)
0.41*
(0.17)
0.10**
(0.03)
0.00
(0.03)
0.12
(0.08)
-0.03
(0.04)
0.13*
(0.07)
-0.18*
(0.09)
0.03
(0.09)
1060.93*
Notes: a Robust standard errors are shown.
b
In supplementary analyses not reported here, the inclusion of firm size in the analyses did not affect the support for the
hypotheses.
†
p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001; two-tailed tests.
© Blackwell Publishing Ltd 2009
Relative CEO Underpayment and R&D Spending
Relative cash pay
Model 6
3.24***
(0.02)
-0.01
(0.05)
-0.08
(0.10)
0.14***
(0.03)
0.03
(0.03)
0.00†
(0.00)
0.00
(0.00)
0.13***
(0.03)
0.98***
(0.01)
0.19**
(0.06)
0.37*
(0.16)
0.06
(0.04)
-0.02
(0.03)
0.23
(0.19)
0.04
(0.05)
1208.41*
Model 7
3.29***
(0.02)
-0.04
(0.04)
-0.03
(0.09)
0.15**
(0.04)
0.04
(0.04)
0.00
(0.00)
0.00†
(0.00)
0.07*
(0.03)
0.97***
(0.02)
0.19†
(0.10)
0.22†
(0.12)
-0.02
(0.04)
0.04
(0.04)
0.00
(0.10)
-0.11*
(0.04)
0.13†
(0.08)
1292.71*
Model 8
3.26***
(0.02)
-0.03
(0.04)
-0.15*
(0.08)
0.14***
(0.04)
0.05
(0.03)
0.00
(0.00)
0.00
(0.00)
0.10***
(0.03)
0.98***
(0.01)
0.21*
(0.07)
0.23†
(0.14)
0.01
(0.03)
-0.02
(0.04)
0.07
(0.10)
0.03
(0.06)
-0.18*
(0.08)
0.05
(0.09)
1236.53*
17
Relative options pay
Model 9
Model 10
Model 11
Model 12
Model 13
3.29***
3.34***
3.36***
3.40***
3.33***
(0.03)
(0.03)
(0.04)
(0.06)
(0.03)
-0.05
-0.02
-0.06
-0.06
-0.02
(0.04)
(0.06)
(0.07)
(0.07)
(0.06)
-0.01
-0.11
-0.10
-0.11
-0.09
(0.09)
(0.10)
(0.08)
(0.07)
(0.08)
0.15**
0.16***
0.16***
0.16***
0.16***
(0.05)
(0.03)
(0.03)
(0.03)
(0.03)
0.04
0.04†
0.04*
0.05*
0.05*
(0.04)
(0.02)
(0.02)
(0.02)
(0.03)
0.00
0.00
0.00†
0.00
0.00
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
0.00
0.01
0.01
0.01†
0.01
(0.00)
(0.01)
(0.00)
(0.01)
(0.00)
0.06*
0.07†
0.02
0.02
0.08*
(0.03)
(0.04)
(0.05)
(0.05)
(0.04)
0.97***
0.98***
0.93***
0.93***
0.98***
(0.02)
(0.01)
(0.07)
(0.06)
(0.01)
0.25†
0.23**
0.75
0.76
0.25**
(0.13)
(0.08)
(0.58)
(0.54)
(0.08)
0.19
0.30†
0.28
0.29*
0.29†
(0.13)
(0.16)
(0.18)
(0.19)
(0.17)
-0.05
0.06
0.11
0.10
0.08†
(0.04)
(0.04)
(0.09)
(0.10)
(0.04)
0.02
-0.03
0.00
-0.01
-0.02
(0.04)
(0.05)
(0.05)
(0.05)
(0.05)
0.02
0.03
0.02
-0.03
0.04
(0.11)
(0.04)
(0.06)
(0.08)
(0.04)
-0.17*
0.01
0.14
0.04
0.06
(0.09)
(0.02)
(0.12)
(0.04)
(0.07)
0.19†
-0.09
-0.05
(0.10)
(0.13)
(0.07)
-0.14*
0.07
0.21
(0.07)
(0.10)
(0.17)
0.13
-0.10
-0.12
(0.14)
(0.09)
(0.09)
1290.06*
1125.17*
1194.42*
1170.88*
1129.69*
Models 4, 8, and 12 include the interactions of manager-controlled and ownermanaged firms versus owner-controlled firms on the relationship between CEO underpayment and change in R&D spending. The main effect term in Model 4, the relative
total pay model, is significant, which suggests a positive relationship between total
underpayment and R&D spending in owner-controlled firms. However, the main effect
terms are not significant in Models 8 and 12, which suggests no relationship between
© Blackwell Publishing Ltd 2009
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E. A. Fong
3.4
3.35
Low R&D
3.3
R&D spending
High R&D
3.25
3.2
3.15
3.1
3.05
3
No underpayment
Underpayment
Relative pay
Figure 1. Interaction of CEO total underpayment and industry type (R&D intensity) on R&D spending
(Model 3)
3.4
3.35
Low R&D
R&D spending
3.3
High R&D
3.25
3.2
3.15
3.1
3.05
3
No underpayment
Underpayment
Relative pay
Figure 2. Interaction of CEO cash underpayment and industry type (R&D intensity) on R&D spending
(Model 7)
cash and options underpayment and R&D spending in owner-controlled firms. The
interaction term for the manager-controlled firms is negative and significant for total
(g = -0.16; p < 0.05) and cash (g = -0.14; p < 0.05) underpayment. R&D spending
related to total and cash underpayment differ for CEOs in manager-controlled versus
owner-controlled firms, but do not differ for owner-managed versus owner-controlled
firms. The negative relationships between total and cash underpayment and R&D
spending in manager-controlled firms as compared to owner-controlled firms suggest
© Blackwell Publishing Ltd 2009
Relative CEO Underpayment and R&D Spending
19
3.4
Owner-controlled
3.35
Manager-controlled
R&D spending
3.3
3.25
3.2
3.15
3.1
3.05
No underpayment
Underpayment
Relative pay
Figure 3. Interaction of CEO total underpayment and ownership structure on R&D spending (Model 4)
3.4
Owner-controlled
3.35
Manager-controlled
R&D spending
3.3
3.25
3.2
3.15
3.1
3.05
No underpayment
Underpayment
Relative pay
Figure 4. Interaction of CEO cash underpayment and ownership structure on R&D spending (Model 8)
that manager-controlled firms reduce R&D spending when relatively underpaid based
on total and cash pay, which supports Hypothesis 3. Figures 3 and 4 show that when a
CEO is relatively underpaid based on both total and cash pay in a manager-controlled
situation, R&D spending decreases. Interestingly, Figure 3 also shows that underpaid
CEOs in owner-controlled firms increase R&D spending.
Models 5, 9, and 13 include the full models with all the interactions. The results show
that the industry type interaction is positive and significant for total (g = 0.13; p < 0.05)
and cash (g = 0.19; p < 0.10) underpayment, Models 5 and 9 respectively, which is
© Blackwell Publishing Ltd 2009
20
E. A. Fong
consistent with Hypothesis 2. Also, Models 5 and 9 show that the manager-controlled
interaction is negative and significant for the relative total pay (g = -0.18; p < 0.05) and
relative cash pay (g = -0.14; p < 0.05), consistent with Hypothesis 3. The non-significant
main effect for underpayment in the relative total pay model (Model 5), which represents
relative underpayment in owner-controlled firms in low R&D intensity industries, suggests that ownership dominates this relationship. Note that Model 3 provides a significant
main effect at p < 0.05 for underpayment associated with the industry type interaction
and Model 4 provides a significant main effect at p < 0.10 for underpayment associated
with ownership interactions; Model 5 more closely reflects Model 4, the ownership
model. However, Model 9, the relative cash pay full model, reflects a significant negative
relationship between CEO cash underpayment and R&D spending (g = -0.17; p < 0.05)
in owner-controlled firms in low technology industries. The results in Model 9 more
closely reflect the results in Model 7, which suggests that industry type dominates the
relationship when underpayment is based on cash compensation.
DISCUSSION
The results show that CEO total, cash, and options underpayment does not directly
affect R&D spending; however, in less R&D intensive industries both total and cash
underpayment is associated with R&D spending decreases. The results also show that in
manager-controlled firms both total and cash underpayment is associated with R&D
spending decreases. Interestingly, the results show that when CEOs face total and cash
underpayment in high R&D industries and when CEOs face total underpayment in
owner-controlled firms, R&D spending is more likely to increase (see Figures 1–3), which
suggests that CEO underpayment may actually lead to increases in R&D spending under
these specific conditions. However, Figure 4 shows that CEOs who face cash underpayment in owner-controlled firms do not seem to react any differently than their more
fairly paid (i.e. less underpaid) counterparts. Finally, the results suggest that options
underpayment is not associated with R&D spending under any circumstances.
These findings complement and extend the previous research on CEO pay in general
and in relation to innovation as well as extend the research on CEO labour market
comparisons. First, prior R&D manipulation studies using an agency theory perspective
show that innovation provides CEOs the opportunity to manipulation R&D spending to
boost their pay, specifically as they approach retirement or when the firm faces a loss
(Clinch, 1991; Dechow and Sloan, 1991), and the results found in this study are not at
odds with agency theory or this prior R&D research. Using a microeconomic utility
maximization viewpoint, agency theory suggests that individuals are self-interested
opportunists ( Jensen and Meckling, 1976); thus, CEOs may place value on higher pay
and use reductions in R&D spending to obtain higher pay. It may be that all CEOs want
to increase their own pay and are willing to use legitimate means to increase performance
and pay. However, the results here suggest that compared to CEOs paid closer to the
labour market rate, lower paid CEOs, who need to generate larger income increases to
‘catch-up’ to the labour market, seem more likely to use the information asymmetry
associated with R&D spending in a way that could lead to pay increases in low R&D
intensive industries (i.e. when CEO pay is less likely to be aligned with R&D spending).
© Blackwell Publishing Ltd 2009
Relative CEO Underpayment and R&D Spending
21
Moreover, consistent with prior research that suggests that compensation committees
in high technology industries are more likely to align CEO pay with R&D spending than
compensation committees in low technology industries (e.g. Balkin et al., 2000; Makri
et al., 2006), the results show that such opportunistic reductions conditioned on underpayment are mitigated in high R&D intensive industries. In fact, Figures 1 and 2 suggest
that CEOs who face underpayment based on total and cash pay increase R&D spending
when in high R&D intensive industries. Unlike prior research that suggests CEO pay
alignment with firm performance may motivate greater opportunistic behaviour by
CEOs (see Devers et al., 2007), the current study’s results suggest that if alignment
between CEO pay and R&D spending exists, as is the case in high R&D intensive
industries, then it mitigates the opportunistic reduction of R&D spending and may even
lead to increases in R&D spending. However, the results relate to cash and total
underpayment and not to options underpayment, which suggests that CEOs may be
reacting to cash and bonus pay alignment, a form of short-term alignment and thus more
closely related to CEO behaviours. This may be consistent with the view that there are
certain situations where ‘anticipated future wage changes’ (i.e. long-term incentives) do
not discourage behaviours towards immediate gains (Fama, 1980, p. 306). In other words,
conditions may exist where immediate gains outweigh anticipated future wages determined through ex-post settlement (i.e. long-term incentives). Prior research examining
CEO opportunistic behaviours using the agency theory literature has examined those
behaviours when CEO pay is aligned with long-term performance and not when CEO
pay is aligned with specific behaviours. It may be that when incentives are tied to a specific
behaviour, which in this case is R&D expenditures, it is more difficult for CEOs to
manipulate the situation in a way that benefits only the CEO. Therefore, prior research
may have found weak support for the alignment of CEO pay with long-term performance
(e.g. Tosi et al., 2000) because such alignment allowed for the flexibility of CEO behaviour towards short-term outcomes and the anticipated future wage changes related to the
long-term alignment were insufficient to deter short-term overconsumption.
Also, Gomez-Mejia and Wiseman (1997) question the effectiveness of aligning CEO
pay with long-term performance given that performance is dependent upon factors
outside of the CEO’s control. The current study suggests that it may be beneficial to link
a portion of CEO pay to CEO behaviour rather than relying completely on making
CEO pay contingent on long-term performance to control CEO behaviour (i.e. CEO
pay alignment may be more effective when aligning pay with factors under the CEO’s
control, specifically CEO behaviours). Future research should examine the alignment of
CEO pay with other behaviours that have long-term performance implications. For
example, marketing research suggests that having a strong marketing or customer service
orientation has performance advantages (e.g. Bowen et al., 1989; Hurley and Hult, 1998)
and thus aligning CEO bonuses with marketing investments may be valuable.
Second, CEO labour market research, using social comparison theory, suggests that
compensation committees react to deviations from the CEO labour market rate
(Ezzamel and Watson, 1998, 2002); this study examines the CEO’s reaction to such
deviations. The results suggest that CEOs who receive relatively low total and cash pay
reduce R&D spending in low R&D intensive firms and in manager-controlled firms and
thus CEOs may recognize that their pay is low relative to others and react accordingly.
© Blackwell Publishing Ltd 2009
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E. A. Fong
Miller (1995), in studying industry boundaries for relevant labour market comparisons,
suggests that equity theory may be the next logical step if CEOs make comparisons with
other CEOs. In equity theory, Adams (1965) posits that individuals make comparisons to
similar others based on input to outcome ratios. If the ratios differ, the individual will
react in a way to make the ratios equivalent. The results of this study complement the
connection between CEO pay and equity comparisons made by Miller (1995) and Wade
et al. (2006a) for those CEOs who are underpaid. However, consistent with the view that
individuals are likely to be less sensitive to overpayment than underpayment conditions,
the results show no relationship between CEO overpayment and R&D spending.
Finally, the results show that ownership structure influences the relationship between
both total and cash underpayment and R&D spending such that the relationship is
stronger for underpaid CEOs in manager-controlled firms compared to CEOs in ownercontrolled firms. This is consistent with the prior literature on ownership structure which
suggests that CEOs in manager-controlled firms face less monitoring than their ownercontrolled counterparts (e.g. Hambrick and Finkelstein, 1987; Tosi and Gomez-Mejia,
1989). Powerful CEOs can still be left underpaid relative to other powerful CEOs even
after exerting their power over the compensation committee; however, their power may
allow them to take action to increase their pay in other ways, which in this study takes
the form of R&D adjustments. It is also interesting to note that in Models 5 and 9 the
significant ownership structure interactions taken with the significant industry type (R&D
intensity) interactions suggest that underpaid CEOs in owner-controlled firms in high
R&D intensity industries will increase R&D spending. This is both consistent with the
ownership structure literature, which suggests CEOs in owner-controlled firms face more
monitoring, and the R&D literature, which suggests that pay alignment is more likely to
occur in high R&D intensity firms. It may be that strong owners recognize the importance
of R&D investments in high R&D environments and put pressure on the compensation
committee to align CEO pay with R&D spending to a greater degree in these situations.
For practitioners, this study strongly suggests that underpaying CEOs can have negative long-term effects for the firm and, possibly, shareholders. As shown in the analyses,
relatively underpaying CEOs can lead to decreases in R&D spending in low R&D
intensive industries and in situations where CEOs face reduced monitoring from owners.
Although Ezzamel and Watson (1998) suggest that compensation committees may be
sensitive to relative CEO pay and attempt to make adjustments to CEO pay when pay
deviations occur, this study suggests that those compensation committees that do make
those adjustments (i.e. leave CEOs overpaid or closely paid to the labour market rate)
may successfully discourage R&D manipulation. However, compensation committees
that overlook labour market adjustments may encourage opportunism relating to R&D
spending; CEOs may recognize their own underpayment and make their own opportunistic adjustments in less R&D intensive industries or when they face less monitoring
from owners. Future research may attempt to examine the effects of underpayment on
other CEO behaviours that may have negative consequences for the firm given that the
opportunistic adjustment of R&D spending is not the only means of influencing performance and pay; for example, CEO behaviour towards more fraudulent activities such as
financial misreporting through the manipulation of accounting numbers or the misuse of
discretionary accruals.
© Blackwell Publishing Ltd 2009
Relative CEO Underpayment and R&D Spending
23
Concerning compensation alignment, Cheng (2004) shows that through the effective
alignment of long-term incentive pay in the form of CEO option grants, compensation
committees effectively control opportunistic reductions in R&D spending that stem from
the horizon problem and the myopia problem. This study suggests that such long-term
alignment does not stem manipulations based on underpayment. Instead, it is short-term
(i.e. more direct behavioural) alignment in the form of cash and bonus pay that may
discourage R&D manipulation based on underpayment. Interestingly, enough compensation committees implemented compensation alignment strategies in high R&D intensive industries to encourage increases in R&D spending when CEOs were underpaid,
which is consistent with findings by Balkin et al. (2000) that show a stronger alignment
with cash and bonus pay than options pay with R&D spending in high technology firms.
However, even though firms in high R&D intensive industries are more likely to rely
on building a competitive advantage on innovation, firms in low R&D intensive industries can still benefit from R&D investment. For example, Damanpour et al. (2009)
suggest that innovation does not just pertain to new products, but also administrative
structures or new services. Thus, firms in low R&D intensive industries may invest to
improve their administrative structures or service capabilities. The mean R&D spending
for firms in low R&D intensive industries in this data were $55 million, with some firms
spending into the hundreds of millions on R&D, on mean sales of over $3.6 billion.
Furthermore, over 71 per cent of the firms in low R&D intensive industries invested in
R&D. It is clear that many firms in low R&D intensive industries invest in R&D and thus
compensation committees should be concerned with the opportunistic manipulation of
R&D even in low R&D intensive industries.
Limitations
There are limitations to be kept in mind when evaluating these results. First, similar
to other labour market studies (e.g. Ezzamel and Watson, 1998; Wade et al., 2006a),
although the relevant labour market variables (tenure, firm size, etc) were used to develop
the relative pay equations, I cannot conclude that CEOs used this same information. The
determination of any given CEO’s comparison group can only be made by directly
surveying that CEO. Such data are difficult to obtain. March (1994) suggests that
bounded rationality limits decision-makers’ information gathering capability and capacity. Antle and Smith (1986) suggest firms in the same industry face similar economic
conditions and risk. Thus, CEOs are likely to make within-industry comparisons on fairly
transparent variables (e.g. firm size, firm performance, human capital, and power) when
making decisions for the organization, so it would not be unrealistic to believe they would
make the same comparisons for their own pay and performance. The wage equations
account for many of these transparent variables as well as accounts for industry in the
estimation technique (i.e. the wage equation accounts for making within industry comparisons).[2] However, although the relative total, cash, and options pay equations explain
45, 54, and 33 per cent of the variance in pay, respectively, there are other unmeasured
variables that may explain variance in pay; for example, CEO specific variables such as
CEO risk aversion. Future research that can gather data relating to CEO specific
variables not included in this study is warranted.
© Blackwell Publishing Ltd 2009
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E. A. Fong
Second, as noted earlier, Ezzamel and Watson (1998) suggest that some compensation
committees continually adjust CEO pay upward to account for the labour market, which
Bebchuk and Fried (2004) contend may lead to a ‘ratchet effect’ on CEO pay. Thus,
active compensation committees may recognize that their CEOs are underpaid relative
to the labour market and make adjustments, which should preclude CEOs in these cases
from taking action into their own hands. Although the study includes controls for power,
such controls may not account for compensation committee activism; however, active
compensation committees should only reduce the influence of CEO underpayment on
R&D spending and thus reduce the chances of finding this relationship. Future research
should examine the possibility that differences exist between the actions of CEOs with
and without active compensation committees.
Third, although a time lag was used in the tests of the hypotheses, I cannot conclude
causality. It is possible that CEOs who are less able to establish advantages using R&D
receive less compensation and thus the expectation would be a decrease in future R&D
spending contingent on the CEOs current underpayment. Furthermore, it may be that
the firm is attempting to reduce costs, which may lead to CEO underpayment and
reductions of R&D in separate time periods.
Finally, care should be taken with the generalizability of the results. The data were
taken from publically traded firms in the United States and thus it is unclear whether
these results generalize to executives in private, non-profit, or international firms as well
as government agencies. Also, the data were gathered from a particular time period,
1991–97, and they may or may not reflect the current environment. To be clear, this
study examines elements of labour markets, specifically the effects of underpayment.
Some CEOs will be underpaid relative to the labour market in any given time period, but
it may be possible that equity theory oriented reactions differ across time periods.
Furthermore, compensation alignment with R&D spending should be important in any
time period given that R&D spending is a primary input into innovation (Heeley et al.,
2007); however, time period affects may also exist here. Thus, research using data from
more recent time periods is warranted.
Conclusion
Prior research proposes the importance of accounting for social comparisons (Ezzamel
and Watson, 1998; Miller, 1995; Porac et al., 1999) when using compensation to motivate CEO actions. For example, Ezzamel and Watson (1998) suggest that compensation
committees should pay close attention to the design of CEO compensation contracts
because relatively under- or over-paying CEOs may create motivational problems. This
study examines such motivational and behavioural issues by focusing on relative CEO
pay and CEO behaviour towards firm level outcomes that may significantly impact
long-term shareholder maximization, specifically CEO behaviour towards R&D spending. This study’s results support the proposition that relative underpayment may create
motivational and behavioural issues. Specifically, this study shows that social comparisons may be motivating CEO behaviour such that underpaid CEOs engage in opportunistic changes in R&D spending in response to their pay when they face less
monitoring from owners or when they are in low R&D intensive industries, which is a
situation where their short-term compensation is less likely to be tied to R&D spending.
© Blackwell Publishing Ltd 2009
Relative CEO Underpayment and R&D Spending
25
ACKNOWLEDGMENTS
The author thanks W. David Allen, Mary Gregory, Jatinder N. D. Gupta, and Allen Wilhite for their
support, comments, and suggestions.
NOTES
[1] To save space only the relative total pay equation is shown; however, the relative cash and relative
options pay equations follow the same format.
[2] In supplementary analyses not reported here, using only deviations from the mean CEO pay in the
industry to test the hypotheses provided substantively different results (marginal support for Hypothesis
1 and no support for Hypotheses 2 and 3) from the analyses using the CEO wage equation. Such
substantive differences are expected given that the CEO wage equation accounts for CEO inputs while
deviations from the mean CEO pay in the industry do not account for CEO inputs, an important aspect
of equity theory and fairness (Adams, 1965).
APPENDIX: LIST OF INDUSTRIES IN THE DATAa,b
SIC codec
Industry label
Mean CEO
total pay
Mean R&D
spending
1311
2621
2670
2711
2834*
2835*
2836*
2911
3312
3571*
3576*
3661*
3663*
3674*
3714
3841*
3845*
4813
4833*
5411
5812
7011
7370*
7372*
7373*
7990
Crude petroleum & natural gas
Paper mills
Converted paper & paperboard products (no containers/boxes)
Newspapers: publishing or publishing & printing
Pharmaceutical preparations
In vitro & in vivo diagnostic substances
Biological products (no diagnostic substances)
Petroleum refining
Steel works, blast furnaces & rolling mills (coke ovens)
Electronic computers
Computer communications equipment
Telephone & telegraph apparatus
Radio & TV broadcasting & communications equipment
Semiconductors & related devices
Motor vehicle parts & accessories
Surgical & medical instruments & apparatus
Electromedical & electrotherapeutic apparatus
Telephone communications (no radiotelephone)
Television broadcasting stations
Retail – grocery stores
Retail – eating places
Hotels & motels
Services – computer programming, data processing, etc
Services – prepackaged software
Services – computer integrated systems design
Services – miscellaneous amusement & recreation
7.42
6.57
7.40
7.60
7.83
6.26
6.52
6.80
6.97
7.21
7.11
6.80
6.94
7.53
7.02
6.79
7.29
7.38
7.50
6.48
6.86
6.86
7.48
7.84
6.13
7.33
2.91
2.51
3.35
4.24
5.36
2.00
2.91
4.99
2.72
4.33
3.62
2.98
3.18
4.35
2.22
2.75
2.82
3.76
0.24
0.75
1.73
1.00
4.25
4.67
2.64
0.34
a
In supplementary analyses not reported here, the exclusion of service oriented industries (5411, 5812, 7011, 7370, 7372,
7373, and 7990) led to results that were consistent with those including all industries regarding support for Hypothesis 2;
however, Hypothesis 3 was not supported.
b
Logarithmic transformations were used for both CEO total pay and R&D spending to account for extreme values.
c
‘*’ denotes this industry as high R&D intensive in the analysis based on average industry R&D/Sales > 5% (i.e. high
R&D intensive in the ‘industry type’ variable).
© Blackwell Publishing Ltd 2009
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E. A. Fong
REFERENCES
Aboody, D. and Lev, B. (2000). ‘Information asymmetry, R&D, and insider gains’. Journal of Finance, 55,
2747–66.
Adams, J. (1965). ‘Inequity in social exchange’. In Berckowitz, L. (Ed.), Advances in Experimental Social
Psychology. New York: Academic Press, 267–99.
Antle, R. and Smith, A. (1986). ‘An empirical investigation of the relative performance evaluation of
corporate executives’. Journal of Accounting Research, 24, 1–39.
Baber, W., Fairfield, P. and Haggard, J. (1991). ‘The effect of concern about reported income on discretionary spending decision’. The Accounting Review, 66, 818–29.
Balkin, D., Markman, G. and Gomez-Mejia, L. (2000). ‘Is CEO pay in high-technology firms related to
innovation?’. Academy of Management Journal, 43, 1118–29.
Barth, M., Kasznik, R. and McNichols, M. (2001). ‘Analyst coverage and intangible assets’. Journal of
Accounting Research, 39, 1–34.
Baysinger, B. and Hoskisson, R. (1989). ‘Diversification strategy and R&D intensity in multiproduct firms’.
Academy of Management Journal, 32, 310–32.
Beatty, R. and Zajac, E. (1994). ‘Managerial incentives, monitoring, and risk bearing: a study of executive
compensation, ownership, and board structure in initial public offerings’. Administrative Science Quarterly,
39, 313–35.
Bebchuk, L. and Fried, J. (2004). Pay Without Performance: The Unfulfilled Promise of Executive Compensation.
Cambridge, MA: Harvard University Press.
Bizjak, J., Brickley, J. and Coles, J. (1993). ‘Stock-based incentive compensation and investment behavior’.
Journal of Accounting and Economics, 16, 349–72.
Black, F. and Scholes, M. (1973). ‘Pricing of options and corporate liabilities’. Journal of Political Economy, 81,
637–54.
Bloom, M. and Milkovich, G. (1998). ‘Relationships among risk, incentive pay, and organizational performance’. Academy of Management Journal, 41, 283–97.
Bowen, D., Siehl, C. and Schneider, B. (1989). ‘A framework for analyzing customer service orientations in
manufacturing’. Academy of Management Review, 14, 75–95.
Bryk, A. and Raudenbush, S. (1989). ‘Methodology for cross-level organizational research’. Research in the
Sociology of Organizations, 7, 233–73.
Buchholtz, A., Ribbens, B. and Houle, I. (2003). ‘The role of human capital in postacquisition CEO
departure’. Academy of Management Journal, 46, 506–14.
Burns, N. and Kedia, S. (2006). ‘The impact of performance-based compensation on misreporting’. Journal
of Financial Economics, 79, 35–67.
Carpenter, M. and Sanders, W. (2002). ‘Top management team compensation: the missing link between
CEO pay and firm performance?’. Strategic Management Journal, 23, 367–75.
Cheng, S. (2004). ‘R&D expenditures and CEO compensation’. Accounting Review, 79, 305–28.
Clinch, G. (1991). ‘Employee compensation and firms’ research and development activity’. Journal of
Accounting Research, 29, 59–78.
Cohen, W. and Leventhal, D. (1990). ‘Absorptive capacity: a new perspective on learning and innovation’.
Administrative Science Quarterly, 35, 128–52.
Dalton, D., Daily, C., Certo, S. and Roengpitya, R. (2003). ‘Meta-analyses of financial performance and
equity: fusion or confusion?’. Academy of Management Journal, 46, 13–26.
Damanpour, F., Walker, R. and Avellaneda, C. (2009). ‘Combinative effects of innovation types and
organizational performance: a longitudinal study of service organizations’. Journal of Management Studies,
46, 650–75.
Davis, G. and Thompson, T. (1994). ‘A social movement perspective on corporate control’. Administrative
Science Quarterly, 39, 141–73.
Dechow, P. and Skinner, D. (2000). ‘Earnings management: reconciling the views of accounting academics,
practitioners, and regulators’. Accounting Horizons, 14, 235–50.
Dechow, P. and Sloan, R. (1991). ‘Executive incentives and the horizon problem: an empiricalinvestigation’. Journal of Accounting & Economics, 14, 51–89.
Devers, C., Cannella, A., Reilly, G. and Yoder, M. (2007). ‘Executive compensation: a multi-disciplinary
review of recent developments’. Journal of Management, 33, 1016–72.
Dittrich, J. and Carrell, M. (1979). ‘Organizational equity perceptions, employee job satisfaction, and
departmental absence and turnover rates’. Organizational Behavior and Human Performance, 24,
29–40.
© Blackwell Publishing Ltd 2009
Relative CEO Underpayment and R&D Spending
27
Donoher, W., Reed, R. and Storrud-Barnes, S. (2007). ‘Incentive alignment, control, and the issue of
misleading financial disclosures’. Journal of Management, 33, 547–69.
Eisenhardt, K. (1989). ‘Agency theory: an assessment and review’. Academy of Management Review, 14, 57–74.
Ezzamel, M. and Watson, R. (1998). ‘Market comparison earnings and the bidding-up of executive cash
compensation: evidence from the United Kingdom’. Academy of Management Journal, 41, 221–31.
Ezzamel, M. and Watson, R. (2002). ‘Pay comparability across and within UK boards: an empirical analysis
of the cash pay awards to CEOs and other board members’. Journal of Management Studies, 39, 207–32.
Fama, E. (1980). ‘Agency problems and the theory of the firm’. Journal of Political Economy, 88, 288–307.
Festinger, L. (1954). ‘A theory of social comparison process’. Human Relations, 7, 117–40.
Finkelstein, S. (1992). ‘Power in top management teams: dimensions, measurement, and validation’. Academy
of Management Journal, 35, 505–38.
Finkelstein, S. and Hambrick, D. (1988). ‘Chief executive compensation: a synthesis and reconciliation’.
Strategic Management Journal, 9, 543–58.
Finkelstein, S. and Hambrick, D. (1989). ‘Chief executive compensation: a study of the intersection of
markets and political processes’. Strategic Management Journal, 10, 121–34.
Gavin, M. and Hofmann, D. (2002). ‘Using hierarchical linear modeling to investigate the moderating
influence of leadership climate’. The Leadership Quarterly, 13, 15–33.
Gomez-Mejia, L. and Wiseman, R. (1997). ‘Reframing executive compensation: an assessment and outlook’.
Journal of Management, 23, 291–374.
Goodman, P. (1974). ‘An examination of referents used in the evaluation of pay’. Organizational Behavior &
Human Performance, 12, 170–95.
Greenberg, J. (1993). ‘Stealing in the name of justice: informational and interpersonal moderators of theft
reactions to underpayment inequity’. Organizational Behavior and Human Decision Processes, 54, 81–103.
Greene, W. (2000). Econometric Analysis, 4th edition. Upper Saddle River, NJ: Prentice Hall.
Hambrick, D. and Finkelstein, S. (1987). ‘Managerial discretion: a bridge between polar views of organizational outcomes’. In Staw, B. and Cummings, L. (Eds), Research in Organizational Behavior. Greenwich: JAI
Press, 9, 369–406.
Hambrick, D. and Finkelstein, S. (1995). ‘The effects of ownership structure on conditions at the top: the case
of CEO pay raises’. Strategic Management Journal, 16, 175–93.
Hamel, G. and Prahalad, C. (1994). ‘Competing for the future’. Harvard Business Review, 72, 122–8.
Healy, P. (1985). ‘The effects of bonus schemes on accounting decisions’. Journal of Accounting and Economics,
7, 85–107.
Heeley, M., Matusik, S. and Jain, N. (2007). ‘Innovation, appropriability, and the underpricing of initial
public offerings’. Academy of Management Journal, 50, 209–25.
Hoskisson, R. and Hitt, M. (1988). ‘Strategic control systems and relative R&D investment in large
multiproduct firms’. Strategic Management Journal, 9, 605–21.
Hurley, R. and Hult, G. (1998). ‘Innovation, market orientation, and organizational learning: an integration
and empirical examination’. Journal of Marketing, 62, 42–54.
Jacquemin, A. and Berry, C. (1979). ‘Entropy measure of diversification and corporate-growth’. Journal of
Industrial Economics, 27, 359–69.
Jensen, M. and Meckling, W. (1976). ‘Theory of firm: managerial behavior, agency costs and ownership
structure’. Journal of Financial Economics, 3, 305–60.
Jensen, M. and Murphy, K. (1990). ‘CEO incentives: its not how much you pay, but how’. Harvard Business
Review, 68, 138–49.
Knight, J. (1998). Value Based Management: Developing a Systematic Approach to Creating Shareholder Value. New York:
McGraw-Hill.
Knight, J. (2002). ‘Performance and greed’. Journal of Business Strategy, 23, 24–7.
Kothari, S., Laguerre, T. and Leone, A. (2002). ‘Capitalization versus expensing: evidence on uncertainty
of future earnings from capital expenditures versus R&D outlays’. Review of Accounting Studies, 7, 355–82.
Lev, B. and Sougiannis, T. (1996). ‘The capitalization, amortization, and value-relevance of R&D’. Journal
of Accounting and Economics, 21, 107–38.
McGahan, A. and Porter, M. (1997). ‘How much does industry matter, really?’. Strategic Management Journal,
27, 330–9.
Makri, M., Lane, P. and Gomez-Mejia, L. (2006). ‘CEO incentives, innovation, and performance in
technology-intensive firms: a reconciliation of outcome and behavior-based incentive schemes’. Strategic
Management Journal, 27, 1057–80.
March, J. (1984). ‘Notes on ambiguity and executive compensation’. Scandinavian Journal of Management Studies,
August, 53–64.
© Blackwell Publishing Ltd 2009
28
E. A. Fong
March, J. (1994). A Primer on Decision Making: How Decisions Happen. New York: Free Press.
Marris, R. (1964). The Economic Theory of Managerial Capitalism. New York: Free Press.
Miller, D. (1995). ‘CEO salary increases may be rational after all: referents and contracts in CEO pay’.
Academy of Management Journal, 38, 1361–85.
Murphy, K. (1985). ‘Corporate performance and managerial remuneration: an empirical-analysis’. Journal
of Accounting & Economics, 7, 11–42.
O’Conner, J., Priem, R., Coombs, J. and Gilley, K. (2006). ‘Do CEO stock options prevent or promote
fraudulent financial reporting?’. Academy of Management Journal, 49, 483–500.
O’Reilly, C., Main, B. and Crystal, G. (1988). ‘CEO compensation as tournament and social-comparison:
a tale of 2 theories’. Administrative Science Quarterly, 33, 257–74.
Porac, J., Wade, J. and Pollock, T. (1999). ‘Industry categories and the politics of the comparable firm in
CEO compensation’. Administrative Science Quarterly, 44, 112–44.
Raudenbush, S. and Bryk, A. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods, 2nd
edition. Thousand Oaks, CA: Sage Publications.
Raudenbush, S., Bryk, A., Cheong, Y. and Congdon, R. (2000). HLM 5: Hierarchical Linear and Nonlinear
Modeling. Lincolnwood, IL: Scientific Software International.
Rediker, K. and Seth, A. (1995). ‘Boards of directors and substitution effects of alternative governance
mechanisms’. Strategic Management Journal, 16, 85–99.
Rutherford, M., Buchholtz, A. and Brown, J. (2007). ‘Examining the relationship between monitoring and
incentives in corporate governance’. Journal of Management Studies, 44, 414–30.
Simon, H. (1947). Administrative Behavior. New York: Free Press.
Stevenson, W. and Radin, R. (2009). ‘Social capital and social influence on the board of directors’. Journal
of Management Studies, 46, 16–44.
Tosi, H. and Gomez-Mejia, L. (1989). ‘The decoupling of CEO pay and performance: an agency theory
perspective’. Administrative Science Quarterly, 34, 169–89.
Tosi, H. and Gomez-Mejia, L. (1994). ‘CEO compensation monitoring and firm performance’. Academy of
Management Journal, 37, 1002–16.
Tosi, H., Werner, S., Katz, J. and Gomez-Mejia, L. (2000). ‘How much does performance matter? A
meta-analysis of CEO pay studies’. Journal of Management, 26, 301–39.
Wade, J., O’Reilly, C. and Pollock, T. (2006a). ‘Overpaid CEOs and underpaid managers: fairness and
executive compensation’. Organization Science, 17, 527–44.
Wade, J., Porac, J., Pollock, T. and Graffin, S. (2006b). ‘The burden of celebrity: the impact of CEO
certification contests on CEO pay and performance’. Academy of Management Journal, 49, 643–60.
Watson, R., Storey, D., Wynarczyk, P., Keasey, K. and Short, H. (1996). ‘The relationship between job
satisfaction and managerial remuneration in small and medium-sized enterprises: an empirical test of
“comparison income” and “equity theory” hypotheses’. Applied Economics, 28, 567–76.
Williamson, O. (1964). The Economics of Discretionary Behavior: Managerial Objectives in a Theory of the Firm.
Englewood Cliffs, NJ: Prentice-Hall.
Xue, Y. (2007). ‘Make or buy new technology: the role of CEO compensation contract in a firm’s route to
innovation’. Review of Accounting Studies, 12, 659–90.
Yermack, D. (1997). ‘Good timing: CEO stock option awards and company news announcements’. Journal
of Finance, 52, 449–76.
Zajac, E. and Westphal, J. (1995). ‘Accounting for the explanations of CEO compensation: substance and
symbolism’. Administrative Science Quarterly, 40, 283–308.
© Blackwell Publishing Ltd 2009