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Relative CEO Underpayment and CEO BehaviourTowards R&D Spendingjoms_861 1..28

Eric A. FongUniversity of Alabama in Huntsville

abstract Arguments based on labour market theory suggest that there may be CEObehavioural issues related to pay deviations from the labour market rate for CEO pay;however, few studies examine this phenomenon. This study attempts to address suchbehavioural issues by examining the influence of relative CEO underpayment on reductionsin R&D spending, the differences in this relationship between firms in high R&D intensiveversus low R&D intensive industries, and the moderating affect of ownership structure onthe CEO underpayment and R&D spending relationship. Results suggest that relative CEOunderpayment is associated with reductions in R&D spending in low R&D intensive industriesand increases in R&D spending in high R&D intensive industries. Also, greater relativeCEO underpayment leads to greater reductions in R&D spending in manager-controlledorganizations as compared to owner-controlled organizations. This study provides evidencethat pay deviations may, in fact, affect certain CEO behaviours, specifically relating toinnovation.

INTRODUCTION

Given the expectation that chief executive officers (CEOs) play a major role in firmperformance ( Jensen and Murphy, 1990), a large stream of literature has been devotedto the motivational effects of CEO compensation relating to firm performance. Inter-estingly, most of these studies focus on the relationship between CEO pay and perfor-mance and assume that CEO behaviour will adhere to such alignment (i.e. CEO payindirectly affects firm performance through CEO behaviour; Devers et al., 2007).However, despite the multitude of studies on CEO pay, little is known about CEObehaviour based on their compensation. This may be, in part, because it is difficult topinpoint the many forces acting on both CEO behaviour and the CEO pay settingprocess. For example, compensation committees must balance opposing social andpolitical forces that affect the pay setting process and thus both CEO pay and CEObehaviour. However, Ezzamel and Watson (1998, 2002) and Miller (1995) suggest that

Address for reprints: Eric A. Fong, Department of Management & Marketing, College of Business Adminis-tration, 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, UKand 350 Main Street, Malden, MA 02148, USA.

Journal of Management Studies ••:•• 2009doi: 10.1111/j.1467-6486.2009.00861.x

CEO pay equity (i.e. fairness), or pay deviations, may be one particular social force thatmay 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 thanabsolute, 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 provideinsight into CEO pay deviations and CEO behavioural issues given that R&D spendingis 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 creatingfirm value and a sustainable competitive advantage (Lev and Sougiannis, 1996), researchshows that CEOs will opportunistically target R&D spending because R&D projects areassociated 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 lightof this research, this paper examines opportunistic CEO behaviour concerning R&Dspending when CEOs are underpaid relative to their labour market wage rate. In doingso, this study attempts to contribute to two areas: (1) the study attempts to advance thesocial comparison research by showing that CEO pay deviations, specifically CEOunderpayment relative to the labour market, is associated with CEO behaviour that mayimpact firm performance through R&D spending; (2) this study attempts to extend theagency theory research on the alignment between CEO pay and performance to showthat there may be value in aligning CEO pay with CEO behaviour (e.g. CEO actionstowards R&D spending) and thus compensation committees may benefit by making agreater 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 oflarge publicly-traded corporations in the United States, I examine whether relative CEOunderpayment affects R&D spending. Also, given the differences between CEO com-pensation contracts in high versus low technology firms (Balkin et al., 2000), I examinethe possibility that industry type (high versus low R&D intensity) moderates the relation-ship such that the effect of CEO underpayment on R&D spending will be weaker in highthan in low R&D intensive industries. Finally, because reducing R&D spending can hurtlong-term profitability, CEOs facing less monitoring from firm owners may be morelikely to influence R&D without punishment and thus I examine the possible moderatingeffect of ownership structure on the relationship between relative CEO underpaymentand reductions in R&D spending. Prior to these examinations I review the R&Dspending, CEO labour market comparisons, and ownership structure literatures. I con-clude with the implications for the literatures on CEO pay and innovation, as well as theimplications 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 relationshipbetween pay and performance; however, compensation researchers suggest these equivo-

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© Blackwell Publishing Ltd 2009

cal results are not surprising given firm performance is a function of both CEO behav-iours 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 beyondfocusing on the relationship between pay and performance and to examining the directbehavioural outcomes of aligning CEO pay with firm performance. The proposition thatthe alignment of pay with performance should motivate CEOs to engage in actions thatmaximize long-term firm performance is grounded in agency theory. Similarly, theresearch examining CEO pay and more specific CEO behaviours, such as accountingmanipulations and fraudulent financial reporting, when CEO pay is aligned with firmperformance, is also grounded in agency theory (e.g. Burns and Kedia, 2006; Donoheret al., 2007; O’Conner et al., 2006).

Agency theory ( Jensen and Meckling, 1976) focuses on control issues resulting fromconflicts of interest between shareholders and managers and conceptualizes controls inthe form of optimal contracts designed to correct these conflicts (see Eisenhardt, 1989, foran overview of agency theory). Because CEOs control organizational resources and arelikely to have firm specific information difficult for owners to obtain (i.e. informationasymmetry), the possibility for moral hazard (CEO behaviours that reduce shareholdervalue for the CEO’s self-interests) exists (Rutherford et al., 2007). Agency researchrecognizes that CEOs’ and shareholders’ interests diverge with respect to firm risk, withCEOs’ 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 CEOsare less diversified than shareholders and both the CEO’s pay and employment is tiedto the firm; thus CEOs prefer short-term outcomes that have inherently less risk thanlong-term outcomes. Fama (1980) suggests that managerial time horizons influence thedegree to which a manager will ‘over consume’ from their present position. The ten-dency is towards immediate gain; long-term incentives should reduce this tendency giventhat long-term incentives impose an ex-post settlement such that current over consump-tion leads to future losses.

However, the results surrounding the line of research examining CEO pay and CEObehaviours when pay is aligned with long-term performance (i.e. a situation with ex-postsettlement) 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 andfraudulent financial reporting under certain power conditions even though CEO pay wasaligned with long-term performance. In essence, CEO behaviours were towards short-term outcomes through manipulating short-term firm performance to receive highershort-term pay despite having their pay aligned with long-term performance, meaningthe 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 whereanticipated future wage changes (i.e. long-term incentives) may not be sufficient toreduce short-term overconsumption. Thus, the research on opportunism suggests thatsome CEOs will pursue their own preferences, which tend to be short-term, whetherthose preferences are aligned with shareholders or not.

Reductions in R&D spending, as a form of opportunism, merits considerable attentionbecause R&D spending is a primary input into innovation (Heeley et al., 2007) and thusa firm’s competitive advantage (Makri et al., 2006). Furthermore, innovation is an

Relative CEO Underpayment and R&D Spending 3


inherently risky endeavour (Kothari et al., 2002) and reductions in R&D can quicklyincrease a firm’s short-term market performance at the expense of innovation andlong-term returns. R&D investments also inherently involve information asymmetrybetween principals and agents (Clinch, 1991), even in high technology firms (Aboodyand Lev, 2000). Jensen and Meckling (1976) suggest that CEOs should possess the mostknowledge about the firm, which implies that CEOs should have a better understandingthan 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 makeopportunistic reductions in R&D spending, which Knight (2002) and O’Conner et al.(2006) note is problematic because decisions that benefit short-term performance oftendo not lead to long-term benefits for shareholders. These consequences make reductionsin 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 andtheir interests in long-term firm performance.

More importantly, R&D spending has been found to be negatively associated withCEO 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&Dspending increases short-term performance through increases in current market andaccounting performance. Similar to the research on accounting manipulations toincrease 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 ofincreasing short-term performance to increase their short-term pay through bonuses andstock 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 finan-cially 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&Dbased on GAAP requirements (Dechow and Skinner, 2000). Second, if firm performancedecreases, the CEO could face termination, which again reduces the CEO’s opportunityto gain from current R&D spending. Given the strategic importance of R&D spendingon long-term firm performance, Cheng (2004) shows that compensation committees willadjust CEO compensation contracts to reduce opportunistic manipulations of R&Dspending when the firm encounters the horizon problem or the myopia problem, con-ditions under which R&D manipulation is likely to occur. However, the argumentsprovided by agency theory suggest that CEOs may be encouraged to behave opportu-nistically towards R&D spending outside of the specific conditions presented by thehorizon and myopia problems, which may be when the CEO’s pay deviates from thelabour market rate.

CEO Labour Markets and Relative CEO Pay

The weak relationship between CEO pay and firm performance may also be partiallyexplained by research suggesting that firm performance is only one of many factors,

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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 inthe CEO pay setting process. For example, Finkelstein and Hambrick (1988, 1989)suggest that CEO pay depends on political processes related to power differencesbetween CEOs and compensation committees. It may be that more powerful CEOs canoverride compensation committee recommendations concerning the CEO’s pay, whichmay decouple pay and performance. O’Reilly et al. (1988) suggest that a social compari-son process occurs when setting CEO compensation contracts such that compensationcommittee members use their own pay to determine the focal CEO’s pay. Such socialcomparisons may lead to a possible misalignment of pay and performance.

With respect to the social influences on CEO compensation, researchers have begunto examine CEO reactions to their pay relative to the CEO labour market (e.g. Wadeet al., 2006a; Watson et al., 1996). For instance, Watson et al. (1996) found that amanager’s level of job satisfaction was related to their relative over- and under-paymentcompared to the labour market and not their absolute pay. Wade et al. (2006a) examinedwhether relative over- and underpayment compared to the CEO labour market wagerate (measured using the residuals of a ‘CEO wage equation’) affected lower levelemployee 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 creatingcompensation policies for subordinates that reflect the CEO’s own over- or under-payment relative to the CEO’s labour market. In turn, firm effectiveness may be influ-enced through high wages for all employees relative to the employees’ labour market rateor through employee turnover when employee pay was low relative to the employee’slabour market.

Porac et al. (1999) suggest that the complex causes of organizational outcomes canmotivate, or even necessitate, social comparisons by CEOs and thus they could recognizethe going labour market rate for their services and possible deviations from such rates.Goodman (1974) suggests that individuals will make comparisons with others who havesimilar abilities, which suggests that when CEOs assess their own managerial ability,performance, and pay, they must make comparisons with other CEOs. These explana-tions provide some insight into Watson et al.’s (1996) findings that job satisfaction andrelative CEO pay are related as well as Wade et al.’s (2006a) suggestion that CEOs createcompensation policies for subordinates that reflect the CEO’s own relative pay. In spiteof this research showing that CEO pay can deviate from the labour market rate and thatCEOs can recognize such deviations, very little research has examined the potentialnegative effects of deviations from the CEO labour market rate.

Through social comparisons, CEOs can recognize that their pay lies above or belowthe prevailing labour market rate of pay; however, an underpaid CEO may take actionto remedy the situation. Research using theories based on norms of fairness, such asequity theory (Adams, 1965) and social comparison theory (Festinger, 1954), show thatrelative underpayment leads to actions that may lead to a fairer situation; such actionscan 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 underpaymentinequity led to increased turnover (i.e. reduced inputs). According to Wade et al. (2006a),



all fairness theories share two assumptions: (1) social comparisons are required to deter-mine fairness; and (2) fairness, or lack of fairness, influences people’s responses to thesecomparisons. Thus, it is an individual’s relative evaluation of the situation that maymotivate a response to make such an evaluation fair. According to organizationaltheorists, 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 viewexecutives’ pay as a direct reflection of these values; thus, relatively low pay may reflectrelatively low prestige. March (1984, p. 60) notes that ‘compensation schemes reassuremanagers that they are important, respected, competent people’. If a CEO receivesrelatively low pay, the CEO may have a greater incentive to behave in ways that can leadto 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 inCEO pay deviations. The emphasis in equity theory rests on the notion that individualscan feel either underpayment inequity or overpayment inequity. With regard to under-payment, 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 CEOsmay attempt to reduce inputs to create a fairer situation, if pay reflects prestige, as isargued above, then CEO preferences would be towards increasing their outcomes whenunderpaid rather than reducing their inputs. Furthermore, the reduction of inputs mayhave negative consequences for the CEO, such as dismissal. The information asymmetrybetween CEOs and shareholders inherent in R&D spending provides CEOs the oppor-tunity for behaviour towards reducing R&D, which increases outcomes throughincreased 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 gainsand that situations may exist where long-term incentives may not be enough to encour-age the CEO to forgo these immediate gains, CEOs may have the motivation to behaveopportunistically towards R&D spending when underpaid (i.e. current underpaymentmay be one condition where ex-post settlement through long-term incentives does notdiscourage immediate gains through R&D manipulation). Cheng (2004) shows thatcompensation committees must, and do, account for such possible R&D manipulationswhen the firm faces the horizon and myopia problems. However, when the horizon andmyopia problems do not exist, the motivation, or incentive, may be the CEO’s relativeunderpayment. Thus, underpayment may encourage CEOs to reduce R&D spending.

Hypothesis 1: Relative CEO underpayment will be associated with decreases in R&Dspending.

For the overpaid CEO, although reactions to overpayment may exist, Adams (1965)suggests that individuals will be less sensitive to overpayment than underpayment situ-ations. One such reason for this lower sensitivity to overpayment is that overpaidindividuals are likely to re-evaluate the situation to make it equitable (i.e. change theirperceptions of the situation to make it fairer). However, even though a change inperceptions is a likely outcome, if reactions to overpayment do occur then they will be inthe form of increased inputs rather than decreased outcomes (Adams, 1965), whichsuggests that overpaid CEOs would appropriately invest in R&D spending. Appropriate

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investment could lead the CEO to increase, decrease, or leave R&D spendingunchanged depending upon the organization’s particular circumstance. As such, itwould 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 tech-nology industries. Balkin et al. (2000) note that innovation is more critical for success inhigh technology firms than in low technology firms. Thus, the benefits CEOs gainthrough information asymmetry in less technology oriented industries may not be thesame in high technology industries given that reductions in R&D spending may signalthat a high technology firm is unsuccessful. Barth et al. (2001) show that high R&Dintensive firms have significantly more analyst coverage than less R&D intensive firms,which suggests that opportunistic downward adjustments in high R&D intensive firmsare more likely to be noticed. Thus, the market is more likely to catch and punishdownward adjustments in R&D spending in high R&D intensive industries than in lowR&D intensive industries. Aboody and Lev (2000), for example, show that CEOs in hightechnology firms are likely to financially benefit from information asymmetry stemmingfrom the complexity of R&D projects and not necessarily from reductions in R&D. Assuch, CEOs may be provided less opportunity in high versus low R&D intensive indus-tries to manipulate R&D for their own self-interests because high R&D intensive indus-tries face greater market oversight and have less information asymmetry related toreductions in R&D.

Furthermore, given that innovation is a primary requisite for survival in high tech-nology industries (Hamel and Prahalad, 1994), Balkin et al. (2000) show that compen-sation committees in high technology industries are more likely to align short-term CEOpay, specifically CEO cash pay (cash and bonus), with R&D spending than compensa-tion committees in low technology industries. Makri et al. (2006) similarly show thatCEO total pay was associated with innovation behaviour in high technology firms. Inessence, both Balkin et al. (2000) and Makri et al. (2006) suggest that compensationcommittees are more likely to align CEO pay with behaviours towards R&D in high thanlow R&D intensive firms and thus reductions in R&D in high R&D intensive firms maynot lead to short-term pay increases for underpaid CEOs.

However, this does not suggest that R&D spending is not important in low technologyindustries. Cohen and Leventhal (1990) suggest innovation improves the quality, cost,speed, and/or features provided by products and services, which are beneficial improve-ments in any industry. Low R&D intensive industries still have firms that invest in R&Dgiven that some firms in these industries may attempt to differentiate their productsand/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 thatR&D investments may be important in low R&D intensive industries, it is clear thatCEO 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 willbe less likely than CEOs in low R&D intensive firms to decrease R&D spending whenunderpaid because such decreases are less likely to lead to short-term pay increases.



Hypothesis 2: The association between CEO underpayment and decreases in R&D willbe 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 necessarilybenefit shareholders in the form of long-term performance (Knight, 1998; O’Conneret al., 2006), CEO power is likely to moderate the relationship between CEO underpay-ment 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 interestsof owners. Finkelstein (1992) suggests that a CEO’s power will influence a CEO’s abilityto affect firm outcomes.

Prior research on ownership structure suggests that certain ownership conditionsenable CEOs to pursue self-interests (Marris, 1964; Williamson, 1964) and influence theCEO’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 com-pared to CEOs in manager-controlled firms. Thus, CEOs in owner-controlled firmswould not be afforded opportunities to adjust R&D spending specifically for their ownbenefit. On the other hand, CEOs in manager-controlled firms who are paid below thelabour market rate, accounting for their power (i.e. compared to other CEOs in similarmonitoring conditions), may attempt to indirectly influence their pay through opportu-nistic changes in R&D spending given that their direct influence has still left themunderpaid compared to other CEOs in similar conditions.

Hypothesis 3: The association between relative CEO underpayment and decreases inR&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 USpublicly traded corporations from 26 industries (see Appendix for a list of industries byfour-digit SIC code included in the study) randomly selected from the Compustatdatabase. The archival data were obtained from Compustat, Execucomp, and CompactDisclosure databases and CEO human capital data, which were hand collected, weregathered from proxy statements, 10-Ks, annual reports, and the Dun and BradstreetReference Book of Corporate Management for the time period 1991–97. The number ofobservations for each CEO varied between 3 and 7 years. The panel is unbalancedbecause the number of years of data per CEO varies. After lagging the data one year andaccounting for missing data, the final sample used to test the hypotheses included a totalof 621 observations from 227 CEOs. As with prior research examining CEO pay andR&D spending (e.g. Cheng, 2004; Dechow and Sloan, 1991), a one year lag is used giventhe expectation that prior pay influences current R&D spending. An independent

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samples t test was performed on the residual of the CEO wage equation, based on totalCEO pay (described below), to test the differences between the final sample of CEOs andthose that were dropped due to missing data and no differences were found between thedropped CEOs and those in the final sample. All financial data are adjusted to 1990dollars using the consumer price index.

Variables

Dependent variable. R&D expenditures are collected from the Compustat database, whichincludes both internal R&D spending and acquired in-progress R&D spending in mil-lions. I calculate R&D spending as log of R&D expenditures, to account for extremevalues, 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 CEOcompensation structure, relative cash pay (cash and bonus) and relative options pay (allforms of pay are measured in thousands), may provide insight into whether short- orlong-term incentives influence CEO behaviours towards R&D spending when under-paid. Similar to Wade et al. (2006a), to determine whether a CEO was under- or overpaidrelative 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 (thedependent variable) is measured given prior pay is likely to affect current R&D spending:

Ln CEO Total Pay Experience CEO tenure Inside CE1 2 3( ) = ∗ + ∗ + ∗β β β OOLn no. of employees Return on assetsOutsider

4 5

6

+∗ ( ) + ∗ +∗

β ββ ratio + Duality7β ∗ .

Year dummies were included for 1992, 1993, 1994, 1995, 1996, and 1997 (1991 wasthe omitted reference year). These variables were used to estimate fixed-effects regres-sion models. In this study, the use of fixed effects models is equivalent to adding adummy variable for each industry, which controls for unmeasured differences acrossindustries that may explain pay differences. More importantly, Porac et al. (1999)suggest that CEOs will likely make within-industry comparisons and propose the use ofa fixed effects model to control for industry in the estimation accounts for these indus-try comparisons.

CEO under- or overpayment was measured by taking the residuals from the CEOwage equations. Residuals have been used as independent variables in previous CEOpay 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 animportant element regarding equity theory and social comparisons (Adams, 1965). Thusresiduals from the wage equation may be more appropriate than using deviations fromthe mean CEO pay in the industry, which does not account for CEO inputs. A negativeresidual suggested that the CEO was underpaid because the CEO’s actual pay was lessthan their predicted pay. A positive residual means that the CEO was overpaid becausethe CEO’s actual pay was greater than their predicted pay.



Similar to Wade et al. (2006a), the residuals from the total, cash, and options wageequations were split to develop variables representing CEO underpayment and CEOoverpayment. CEO underpayment for total, cash, and options was developed by setting themeasures equal to the negative residual values from the wage equations and zerootherwise. Thus, three CEO underpayment variables, total, cash, and options, weredeveloped from the three CEO wage equations. The sign was reversed to make theinterpretation of the CEO underpayment variables more clear-cut (i.e. larger positivevalues indicated greater underpayment). CEO overpayment, entered as a control, was setequal to the positive residual values and zero otherwise. Similar to underpayment, threeCEO overpayment variables were developed.

CEO total pay consists of salary, annual bonus, stock options, stock grants, deferredpay, fringe benefits, and pension accruals. Similar to Murphy (1985), stock options arevalued 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 theyear they were granted. Cash pay consists of salary and annual bonus, consistent withBalkin et al. (2000) who show that R&D spending may be aligned with short-termincentives. 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 minimizeheteroscedasticity.

Outsider ratio and duality were included in the wage equations because CEO influ-ence over the compensation committee, a subset of the board, would determine relativepay, and duality states that the CEO holds multiple positions (i.e. CEO and chairman ofthe 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 CEOis 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, isthe most commonly used indicator of governance provided by the board of directors. Asin prior studies (e.g. O’Conner et al., 2006; Wade et al., 2006a), CEO duality is capturedusing a dummy variable equal to 1 if the CEO is also the chairman of the board and zerootherwise. 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 numberof years since being appointed to the position of CEO) were included in the wageequation as research suggests that these factors may influence compensation (Buchholtzet al., 2003).

Industry type was measured using a dummy variable where industry type = 1 ifthe firm is in a high R&D intensive industry and zero otherwise. Similar to Dechowand Sloan (1991), high R&D intensive industries were identified based on the averageindustry ratio of R&D spending to sales. Firms in four-digit SIC code industrieswith the average industry R&D/Sales > 5 per cent were coded as in a high R&Dintensive industry. The Appendix shows the list of the industries in this study andtheir inclusion as high R&D intensive or not. Industry type serves as a proxy for CEOpay 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 CEOpay with behaviours towards R&D in high technology firms than in low technologyfirms.

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As with previous studies, ownership structure is assessed using a 5 per cent equity-holding threshold (e.g. Hambrick and Finkelstein, 1995; Tosi and Gomez-Mejia, 1989)and organizations are sorted into three categories: (1) manager-controlled firms, where nosingle 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 5per cent or more of the common stock. Using dummy variables, I define manager-controlled = 1 if the organization is manager-controlled and zero otherwise, and owner-managed = 1 if the organization is owner-managed and zero otherwise. Owner-controlledfirms become the omitted reference category in the tests of the hypotheses. The inclusionof owner-managed as a control is important because research has shown that managerialownership reduces opportunism towards R&D spending (Dechow and Sloan, 1991).

Control variables. Rediker and Seth (1995) note that there are many governance mecha-nisms that may influence the level of control afforded to CEOs and thus institutionalownership and director ownership are added as controls. Davis and Thompson (1994)suggest that institutional ownership acts as a governance mechanism. Given the importanceof R&D spending in organizations, institutional ownership may impact the CEO’sinfluence over R&D spending. To measure the variable, I used the residuals of aregression of the average percentage of a firm’s common voting shares held by institu-tions on the average percentage of 5 per cent block-holding. This eliminates overlapbetween the SEC’s 13(f ) reporting, which contains the average percentage of a firm’scommon voting shares held by institutions, and the institutional holdings captured inthe CEO ownership categories. Director ownership represents a governance mechanism(Dalton et al., 2003; Fama, 1980) and thus may influence R&D spending. Directorownership is measured here as the residuals from a regression of the average percentageof a firm’s common voting shares held by the board of directors on the average percent-age of CEO stock holdings and the average percentage of 5 per cent block-holdings.Similar to institutional ownership, this procedure removes potential overlap with theCEO ownership categories.

Prior R&D spending is measured as the log of R&D expenditures at year t - 1 and wasentered as a control. Balkin et al. (2000) note that R&D spending and number of patentsare 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 unre-lated 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 increasingR&D. However, diversification strategies may take more than one year to becomerealized, and thus increases or decreases in R&D based on diversification decisions maynot be compensation dependent (i.e. prior diversification strategies may have becomerealized in the current period of analysis). Thus both related diversification and unrelated

diversification are added as controls. Diversification variables are operationalized using theentropy measure ( Jacquemin and Berry, 1979).

Firm performance was measured using shareholder return and change in shareholderreturn (Change in SR). According to Baber et al. (1991), opportunistic reductions in R&D



spending are more likely to occur when the firm faces an earnings decline and thus bothmarket performance and changes in market performance were added as controls.Change in SR was operationalized as (t - [t - 1]), where t represents firm performance inany given year and t - 1 represents firm performance the prior year.

Dechow and Sloan (1991) suggest that as CEOs approach retirement age they tend toreduce 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 furtherexplanation).

Data Analysis

The study consists of a panel design in the form of repeated observations hierarchicallynested within firms that are hierarchically nested within industries, which requires anestimation technique able to deal with three levels of analysis. Therefore, this studyincorporates hierarchical linear modelling (HLM; Raudenbush and Bryk, 2002) as thestatistical analytic technique. To analyse changes in R&D spending, the model mustaccount 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 Mean S.D. 1 2 3 4 5 6

1. R&D spending 3.31 2.08 1.002. Total CEO underpayment 0.30 0.48 -0.11* 1.003. Total CEO overpayment 0.32 0.58 0.08* -0.35* 1.004. Cash CEO underpayment 0.29 0.44 -0.10* 0.63* -0.27* 1.005. Cash CEO overpayment 0.31 0.48 0.16* -0.37* 0.50* -0.43* 1.006. Options CEO underpayment 0.34 0.63 -0.17* 0.73* -0.30* 0.23* -0.14* 1.007. Options CEO overpayment 0.38 0.51 -0.01 -0.46* 0.85* -0.18* 0.25* -0.40*8. Industry type 0.40 0.49 0.20* -0.03 -0.06 -0.04 -0.04 0.009. Manager-controlled 0.06 0.24 0.37* -0.04 -0.01 -0.04 0.06 -0.074

10. Owner-managed 0.26 0.44 -0.32* 0.10* 0.08 0.04 0.00 0.10*11. Unrelated diversification 0.09 0.24 0.11* -0.06 -0.01 -0.07 0.03 -0.12*12. Related diversification 0.03 0.12 0.23* -0.05 -0.03 -0.05 -0.06 -0.0713. Shareholder return 0.26 0.66 0.07 -0.05 0.14* -0.02 0.01 -0.0314. Change in SR -0.04 0.86 -0.03 0.07 -0.12* 0.07 -0.02 0.0115. CEO age 54.33 8.68 -0.09* -0.05 -0.04 -0.08 0.09* 0.0216. Institutional ownership 0.05 0.22 0.37* -0.14* 0.10* -0.11* 0.09* -0.13*17. Director ownership 0.00 0.10 0.09* -0.07 0.06 -0.08 0.06 -0.13*18. Prior R&D spending 3.18 2.07 0.98* -0.11* 0.07 -0.11* 0.17* -0.17*19. Real GDP 8252.16 592.17 -0.09* 0.01 -0.03 0.00 -0.01 0.02

Notes: a Correlations are based upon pooled data. n = 621.* p < 0.05; two-tailed tests.

E. A. Fong12


firm-level factors (manager-controlled, owner-managed, etc), and industry-level differ-ences (the variance in industry differences is explicitly modelled). The partitioning out ofthe variance across industries into its own level of analysis in the estimation, as is done inHLM, effectively controls for industry effects (Bloom and Milkovich, 1998). Also, HLMallows for the modelling of the within- and between-firm components as well as thewithin- and between-industry components simultaneously, which minimizes potentialbiases imposed by the violation of independence presented by such nesting (Raudenbushand Bryk, 2002). The violation of independence may make the use of standard regressiontechniques, such as ordinary least squares, inappropriate for the tests of the hypothesesusing this data. Bryk and Raudenbush (1989) state that HLM provides unbiased andefficient estimates of the regression coefficients and their standard errors, irrespective ofthe dependence among individual responses due to the nested nature of the data. Inaddition, since the interactions are cross-level interactions (underpayment is a time-levelvariable and both industry type and ownership structure are firm-level variables), the useof HLM is particularly relevant given that HLM appropriately investigates cross-levelinteractions (Gavin and Hofmann, 2002; Raudenbush and Bryk, 2002).

RESULTS

Table I displays the descriptive statistics and correlations for the variables in the tests ofthe 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 1.00-0.03 0.14* 1.00

0.13* -0.20* -0.15* 1.000.01 -0.03 0.01 -0.15* 1.00

-0.02 0.12* 0.32* -0.11* 0.24* 1.000.11* 0.02 -0.03 0.03 -0.05 -0.05 1.00

-0.10* -0.01 0.01 0.03 0.01 0.02 -0.67* 1.00-0.04 -0.02 0.09* -0.02 0.14* 0.09* -0.08* 0.00 1.00

0.01 0.03 -0.02 -0.26* 0.09* 0.05 0.10* -0.03 -0.14* 1.000.02 -0.03 0.02 0.06 -0.08* 0.04 0.16* 0.00 0.00 -0.04 1.00

-0.02 0.19* 0.37* -0.33* 0.13* 0.24* 0.03 -0.01 -0.07 0.36* 0.07 1.00-0.02 -0.09* -0.06 0.05 -0.09* -0.11* -0.11* 0.03 0.02 -0.01 -0.06 -0.10*



Table II shows the generalized least squares with fixed effects regression coefficients andstandard errors for the CEO wage equations used to determine the CEO under- andoverpayment variables. In general, the findings are consistent with previous research onCEO pay, which suggests a strong relationship between firm size and CEO pay (e.g. Tosiet 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. Iestimate 13 models: (1) Model 1, which includes the control variables as well as industrytype and the ownership structure variables; (2) Models 2, 6, and 10, which include thecontrol variables and adds CEO underpayment in the form of total, cash, and optionspay (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 underpay-ment (total, cash, and options) and industry type; (4) Models 4, 8, and 12, which testHypothesis 3 by including the interactions between CEO underpayment and both

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*** 4.96*** 4.27***(0.30) (0.22) (0.69)

Experience 0.08 0.07† 0.19(0.06) (0.04) (0.13)

CEO tenure -0.01 0.01** -0.04***(0.00) (0.00) (0.01)

Inside CEO -0.18* -0.03 -0.38*(0.08) (0.06) (0.18)

Ln(no. of employees) 0.38*** 0.33*** 0.52***(0.02) (0.02) (0.05)

Return on assets 0.02 -0.03 -0.24(0.23) (0.17) (0.52)

Outsider ratio 0.66* 0.54** 0.74(0.28) (0.20) (0.64)

Duality -0.02 0.13* -0.23(0.08) (0.06) (0.19)

1992 -0.26† -0.10 -0.70*(0.14) (0.10) (0.33)

1993 -0.34** -0.08 -0.91**(0.13) (0.09) (0.30)

1994 -0.23* -0.06 -0.67**(0.11) (0.08) (0.26)

1995 -0.23* -0.08 -0.42†

(0.11) (0.08) (0.25)1996 -0.03 -0.05 -0.19

(0.11) (0.08) (0.24)1997 0.05 -0.09 0.12

(0.10) (0.07) (0.23)R-squared 0.45 0.54 0.33

Notes: † p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001; two-tailed tests. Standard errors are shown in parentheses.

E. A. Fong14


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. Consistentwith HLM guidelines (Raudenbush and Bryk, 2002), the measure of model fit is reportedin the form of a likelihood ratio (LR) test comparing the more complex models to theirrespective fully unconditional models with no predictors. The LR test statistic has achi-square distribution with degrees of freedom equal to the difference in the numberof parameters between the models (Raudenbush and Bryk, 2002) and, as noted inTable III, the models are significant. Coefficients are shown as individual gammaweights, which are analogous to beta weights in traditional regression analysis. However,given the logarithmic transformation of CEO pay and the splitting of the residuals fromthe CEO wage equations to develop CEO under- and over-payment for total, cash, andoptions pay, the sizes of the effects are not readily amenable to interpretation. Similar toWade et al. (2006a), the focus is on the significance and direction of the coefficients whendetermining the support, or lack of support, for the hypotheses. The robust standarderrors automatically generated by the HLM statistical package were used because thesecorrect for departures from the assumptions of the variance–covariance matrix (i.e.heteroscedasticity; Raudenbush and Bryk, 2002; Raudenbush et al., 2000). No evidenceof auto-correlation was found using standard tests for auto-correlation (Durbin–Watsontest; see Greene, 2000).

Model 1 provides the effects of the control variables on R&D spending. It is interestingto 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 significantlyincreased 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 onR&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 spendingand it is interesting to note that there is no relationship between CEO overpayment andR&D spending.

Models 3, 7, and 11 include the interaction of industry type on the relationshipbetween CEO underpayment and R&D spending. The main effect term for CEOunderpayment, which tests the relationship between underpayment and R&D spendingin low R&D industries, is negative and significant for both total (g = -0.07; p < 0.05) andcash (g = -0.11; p < 0.05) underpayment, Models 3 and 7 respectively. To reiterate, thesign was reversed for CEO underpayment and thus the negative relationship suggeststhat greater relative underpayment leads to greater reductions in R&D spending. Theinteraction term for industry type and CEO underpayment is positive and significant forModels 3 and 7. The positive coefficients suggest that the negative relationship betweenCEO underpayment and R&D spending found in low R&D intensive industries isweaker 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 arerelatively underpaid based on both total and cash pay increase R&D spending whileunderpaid CEOs in low R&D intensive industries decrease R&D spending. As notedearlier, given the size of the effects are not amenable to interpretation, the Figures reflectthe direction of the tests of the interactions and not the size of their effects.



Table III. Results of the HLM analysis of R&D spendinga,b

Variables Controls Relative total pay

Model 1 Model 2 Model 3 Model 4 Model 5

Intercept 3.27*** 3.22*** 3.23*** 3.22*** 3.22***(0.04) (0.03) (0.03) (0.03) (0.03)

Unrelated diversification -0.03 -0.02 -0.04 -0.01 -0.01(0.05) (0.05) (0.06) (0.05) (0.05)

Related diversification -0.03 -0.07 -0.07 -0.08 -0.09(0.05) (0.08) (0.09) (0.07) (0.07)

Shareholder return 0.17** 0.18*** 0.18*** 0.17*** 0.17***(0.05) (0.03) (0.04) (0.03) (0.03)

Change in SR 0.06* 0.03 0.04 0.02 0.02(0.03) (0.05) (0.03) (0.04) (0.04)

Real GDP 0.00*** 0.00* 0.00† 0.00† 0.00(0.00) (0.00) (0.00) (0.00) (0.00)

CEO age 0.01 0.00 0.00 -0.01 -0.01(0.00) (0.01) (0.01) (0.02) (0.02)

Industry type 0.10*** 0.14*** 0.13*** 0.14*** 0.15***(0.02) (0.03) (0.03) (0.03) (0.03)

Prior R&D spending 0.94*** 0.97*** 0.97*** 0.97*** 0.97***(0.04) (0.01) (0.01) (0.01) (0.01)

Institutional ownership 0.44† 0.24** 0.24** 0.25** 0.25**(0.24) (0.08) (0.08) (0.08) (0.08)

Director ownership 0.87† 0.42** 0.39* 0.40* 0.41*(0.49) (0.15) (0.17) (0.17) (0.17)

Manager-controlled 0.06† 0.09** 0.09** 0.10** 0.10**(0.03) (0.03) (0.03) (0.03) (0.03)

Owner-managed 0.00 -0.02 -0.01 0.00 0.00(0.04) (0.03) (0.03) (0.03) (0.03)

CEO overpayment 0.11 0.12 0.14 0.12(0.10) (0.12) (0.10) (0.08)

CEO underpayment 0.07 -0.07* 0.08† -0.03(0.05) (0.04) (0.05) (0.04)

CEO underpayment ¥ industry type 0.16** 0.13*(0.06) (0.07)

CEO underpayment ¥ manager-controlled -0.16* -0.18*(0.08) (0.09)

CEO underpayment ¥ owner-managed 0.02 0.03(0.10) (0.09)

Dc2 1075.44* 1056.70* 1068.59* 1064.45* 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 thehypotheses.† p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001; two-tailed tests.

E. A. Fong16


Models 4, 8, and 12 include the interactions of manager-controlled and owner-managed firms versus owner-controlled firms on the relationship between CEO under-payment and change in R&D spending. The main effect term in Model 4, the relativetotal pay model, is significant, which suggests a positive relationship between totalunderpayment and R&D spending in owner-controlled firms. However, the main effectterms are not significant in Models 8 and 12, which suggests no relationship between

Relative cash pay Relative options pay

Model 6 Model 7 Model 8 Model 9 Model 10 Model 11 Model 12 Model 13

3.24*** 3.29*** 3.26*** 3.29*** 3.34*** 3.36*** 3.40*** 3.33***(0.02) (0.02) (0.02) (0.03) (0.03) (0.04) (0.06) (0.03)

-0.01 -0.04 -0.03 -0.05 -0.02 -0.06 -0.06 -0.02(0.05) (0.04) (0.04) (0.04) (0.06) (0.07) (0.07) (0.06)

-0.08 -0.03 -0.15* -0.01 -0.11 -0.10 -0.11 -0.09(0.10) (0.09) (0.08) (0.09) (0.10) (0.08) (0.07) (0.08)0.14*** 0.15** 0.14*** 0.15** 0.16*** 0.16*** 0.16*** 0.16***(0.03) (0.04) (0.04) (0.05) (0.03) (0.03) (0.03) (0.03)0.03 0.04 0.05 0.04 0.04† 0.04* 0.05* 0.05*(0.03) (0.04) (0.03) (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) (0.00) (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) (0.00) (0.00) (0.00) (0.01) (0.00) (0.01) (0.00)0.13*** 0.07* 0.10*** 0.06* 0.07† 0.02 0.02 0.08*(0.03) (0.03) (0.03) (0.03) (0.04) (0.05) (0.05) (0.04)0.98*** 0.97*** 0.98*** 0.97*** 0.98*** 0.93*** 0.93*** 0.98***(0.01) (0.02) (0.01) (0.02) (0.01) (0.07) (0.06) (0.01)0.19** 0.19† 0.21* 0.25† 0.23** 0.75 0.76 0.25**(0.06) (0.10) (0.07) (0.13) (0.08) (0.58) (0.54) (0.08)0.37* 0.22† 0.23† 0.19 0.30† 0.28 0.29* 0.29†

(0.16) (0.12) (0.14) (0.13) (0.16) (0.18) (0.19) (0.17)0.06 -0.02 0.01 -0.05 0.06 0.11 0.10 0.08†

(0.04) (0.04) (0.03) (0.04) (0.04) (0.09) (0.10) (0.04)-0.02 0.04 -0.02 0.02 -0.03 0.00 -0.01 -0.02(0.03) (0.04) (0.04) (0.04) (0.05) (0.05) (0.05) (0.05)0.23 0.00 0.07 0.02 0.03 0.02 -0.03 0.04(0.19) (0.10) (0.10) (0.11) (0.04) (0.06) (0.08) (0.04)0.04 -0.11* 0.03 -0.17* 0.01 0.14 0.04 0.06(0.05) (0.04) (0.06) (0.09) (0.02) (0.12) (0.04) (0.07)

0.13† 0.19† -0.09 -0.05(0.08) (0.10) (0.13) (0.07)

-0.18* -0.14* 0.07 0.21(0.08) (0.07) (0.10) (0.17)0.05 0.13 -0.10 -0.12(0.09) (0.14) (0.09) (0.09)

1208.41* 1292.71* 1236.53* 1290.06* 1125.17* 1194.42* 1170.88* 1129.69*



cash and options underpayment and R&D spending in owner-controlled firms. Theinteraction 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 spendingrelated to total and cash underpayment differ for CEOs in manager-controlled versusowner-controlled firms, but do not differ for owner-managed versus owner-controlledfirms. The negative relationships between total and cash underpayment and R&Dspending in manager-controlled firms as compared to owner-controlled firms suggest

3

3.05

3.1

3.15

3.2

3.25

3.3

3.35

3.4

No underpayment Underpayment

Relative pay

R&

D s

pend

ing

Low R&D

High R&D

Figure 1. Interaction of CEO total underpayment and industry type (R&D intensity) on R&D spending(Model 3)

3

3.05

3.1

3.15

3.2

3.25

3.3

3.35

3.4


Relative pay

R&

D s

pend

ing

Low R&D

High R&D

Figure 2. Interaction of CEO cash underpayment and industry type (R&D intensity) on R&D spending(Model 7)

E. A. Fong18


that manager-controlled firms reduce R&D spending when relatively underpaid basedon total and cash pay, which supports Hypothesis 3. Figures 3 and 4 show that when aCEO is relatively underpaid based on both total and cash pay in a manager-controlledsituation, R&D spending decreases. Interestingly, Figure 3 also shows that underpaidCEOs in owner-controlled firms increase R&D spending.

Models 5, 9, and 13 include the full models with all the interactions. The results showthat 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

3.05

3.1

3.15

3.2

3.25

3.3

3.35

3.4


Relative pay

R&

D s

pend

ing

Owner-controlled

Manager-controlled

Figure 3. Interaction of CEO total underpayment and ownership structure on R&D spending (Model 4)

3.05

3.1

3.15

3.2

3.25

3.3

3.35

3.4


Relative pay

R&

D s

pend

ing

Owner-controlled

Manager-controlled

Figure 4. Interaction of CEO cash underpayment and ownership structure on R&D spending (Model 8)



consistent with Hypothesis 2. Also, Models 5 and 9 show that the manager-controlledinteraction is negative and significant for the relative total pay (g = -0.18; p < 0.05) andrelative cash pay (g = -0.14; p < 0.05), consistent with Hypothesis 3. The non-significantmain effect for underpayment in the relative total pay model (Model 5), which representsrelative underpayment in owner-controlled firms in low R&D intensity industries, sug-gests that ownership dominates this relationship. Note that Model 3 provides a significantmain effect at p < 0.05 for underpayment associated with the industry type interactionand Model 4 provides a significant main effect at p < 0.10 for underpayment associatedwith ownership interactions; Model 5 more closely reflects Model 4, the ownershipmodel. However, Model 9, the relative cash pay full model, reflects a significant negativerelationship 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 moreclosely reflect the results in Model 7, which suggests that industry type dominates therelationship when underpayment is based on cash compensation.

DISCUSSION

The results show that CEO total, cash, and options underpayment does not directlyaffect R&D spending; however, in less R&D intensive industries both total and cashunderpayment is associated with R&D spending decreases. The results also show that inmanager-controlled firms both total and cash underpayment is associated with R&Dspending decreases. Interestingly, the results show that when CEOs face total and cashunderpayment in high R&D industries and when CEOs face total underpayment inowner-controlled firms, R&D spending is more likely to increase (see Figures 1–3), whichsuggests that CEO underpayment may actually lead to increases in R&D spending underthese specific conditions. However, Figure 4 shows that CEOs who face cash under-payment in owner-controlled firms do not seem to react any differently than their morefairly paid (i.e. less underpaid) counterparts. Finally, the results suggest that optionsunderpayment is not associated with R&D spending under any circumstances.

These findings complement and extend the previous research on CEO pay in generaland in relation to innovation as well as extend the research on CEO labour marketcomparisons. First, prior R&D manipulation studies using an agency theory perspectiveshow that innovation provides CEOs the opportunity to manipulation R&D spending toboost 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 atodds with agency theory or this prior R&D research. Using a microeconomic utilitymaximization viewpoint, agency theory suggests that individuals are self-interestedopportunists ( Jensen and Meckling, 1976); thus, CEOs may place value on higher payand use reductions in R&D spending to obtain higher pay. It may be that all CEOs wantto increase their own pay and are willing to use legitimate means to increase performanceand pay. However, the results here suggest that compared to CEOs paid closer to thelabour 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 asymmetryassociated with R&D spending in a way that could lead to pay increases in low R&Dintensive industries (i.e. when CEO pay is less likely to be aligned with R&D spending).

E. A. Fong20


Moreover, consistent with prior research that suggests that compensation committeesin high technology industries are more likely to align CEO pay with R&D spending thancompensation committees in low technology industries (e.g. Balkin et al., 2000; Makriet al., 2006), the results show that such opportunistic reductions conditioned on under-payment are mitigated in high R&D intensive industries. In fact, Figures 1 and 2 suggestthat CEOs who face underpayment based on total and cash pay increase R&D spendingwhen in high R&D intensive industries. Unlike prior research that suggests CEO payalignment with firm performance may motivate greater opportunistic behaviour byCEOs (see Devers et al., 2007), the current study’s results suggest that if alignmentbetween CEO pay and R&D spending exists, as is the case in high R&D intensiveindustries, then it mitigates the opportunistic reduction of R&D spending and may evenlead to increases in R&D spending. However, the results relate to cash and totalunderpayment and not to options underpayment, which suggests that CEOs may bereacting to cash and bonus pay alignment, a form of short-term alignment and thus moreclosely related to CEO behaviours. This may be consistent with the view that there arecertain situations where ‘anticipated future wage changes’ (i.e. long-term incentives) donot discourage behaviours towards immediate gains (Fama, 1980, p. 306). In other words,conditions may exist where immediate gains outweigh anticipated future wages deter-mined through ex-post settlement (i.e. long-term incentives). Prior research examiningCEO opportunistic behaviours using the agency theory literature has examined thosebehaviours when CEO pay is aligned with long-term performance and not when CEOpay is aligned with specific behaviours. It may be that when incentives are tied to a specificbehaviour, which in this case is R&D expenditures, it is more difficult for CEOs tomanipulate the situation in a way that benefits only the CEO. Therefore, prior researchmay 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 behav-iour towards short-term outcomes and the anticipated future wage changes related to thelong-term alignment were insufficient to deter short-term overconsumption.

Also, Gomez-Mejia and Wiseman (1997) question the effectiveness of aligning CEOpay with long-term performance given that performance is dependent upon factorsoutside of the CEO’s control. The current study suggests that it may be beneficial to linka portion of CEO pay to CEO behaviour rather than relying completely on makingCEO pay contingent on long-term performance to control CEO behaviour (i.e. CEOpay alignment may be more effective when aligning pay with factors under the CEO’scontrol, specifically CEO behaviours). Future research should examine the alignment ofCEO pay with other behaviours that have long-term performance implications. Forexample, marketing research suggests that having a strong marketing or customer serviceorientation 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 thatcompensation committees react to deviations from the CEO labour market rate(Ezzamel and Watson, 1998, 2002); this study examines the CEO’s reaction to suchdeviations. The results suggest that CEOs who receive relatively low total and cash payreduce R&D spending in low R&D intensive firms and in manager-controlled firms andthus CEOs may recognize that their pay is low relative to others and react accordingly.



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 withother CEOs. In equity theory, Adams (1965) posits that individuals make comparisons tosimilar others based on input to outcome ratios. If the ratios differ, the individual willreact in a way to make the ratios equivalent. The results of this study complement theconnection between CEO pay and equity comparisons made by Miller (1995) and Wadeet al. (2006a) for those CEOs who are underpaid. However, consistent with the view thatindividuals 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 betweenboth total and cash underpayment and R&D spending such that the relationship isstronger for underpaid CEOs in manager-controlled firms compared to CEOs in owner-controlled firms. This is consistent with the prior literature on ownership structure whichsuggests that CEOs in manager-controlled firms face less monitoring than their owner-controlled counterparts (e.g. Hambrick and Finkelstein, 1987; Tosi and Gomez-Mejia,1989). Powerful CEOs can still be left underpaid relative to other powerful CEOs evenafter exerting their power over the compensation committee; however, their power mayallow them to take action to increase their pay in other ways, which in this study takesthe form of R&D adjustments. It is also interesting to note that in Models 5 and 9 thesignificant ownership structure interactions taken with the significant industry type (R&Dintensity) interactions suggest that underpaid CEOs in owner-controlled firms in highR&D intensity industries will increase R&D spending. This is both consistent with theownership structure literature, which suggests CEOs in owner-controlled firms face moremonitoring, and the R&D literature, which suggests that pay alignment is more likely tooccur in high R&D intensity firms. It may be that strong owners recognize the importanceof R&D investments in high R&D environments and put pressure on the compensationcommittee 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 nega-tive 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&Dintensive industries and in situations where CEOs face reduced monitoring from owners.Although Ezzamel and Watson (1998) suggest that compensation committees may besensitive to relative CEO pay and attempt to make adjustments to CEO pay when paydeviations occur, this study suggests that those compensation committees that do makethose adjustments (i.e. leave CEOs overpaid or closely paid to the labour market rate)may successfully discourage R&D manipulation. However, compensation committeesthat overlook labour market adjustments may encourage opportunism relating to R&Dspending; CEOs may recognize their own underpayment and make their own opportu-nistic adjustments in less R&D intensive industries or when they face less monitoringfrom owners. Future research may attempt to examine the effects of underpayment onother CEO behaviours that may have negative consequences for the firm given that theopportunistic adjustment of R&D spending is not the only means of influencing perfor-mance and pay; for example, CEO behaviour towards more fraudulent activities such asfinancial misreporting through the manipulation of accounting numbers or the misuse ofdiscretionary accruals.

E. A. Fong22


Concerning compensation alignment, Cheng (2004) shows that through the effectivealignment of long-term incentive pay in the form of CEO option grants, compensationcommittees effectively control opportunistic reductions in R&D spending that stem fromthe horizon problem and the myopia problem. This study suggests that such long-termalignment 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 maydiscourage R&D manipulation based on underpayment. Interestingly, enough compen-sation committees implemented compensation alignment strategies in high R&D inten-sive 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 alignmentwith 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 relyon building a competitive advantage on innovation, firms in low R&D intensive indus-tries 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 administrativestructures or new services. Thus, firms in low R&D intensive industries may invest toimprove their administrative structures or service capabilities. The mean R&D spendingfor firms in low R&D intensive industries in this data were $55 million, with some firmsspending 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 inR&D. It is clear that many firms in low R&D intensive industries invest in R&D and thuscompensation committees should be concerned with the opportunistic manipulation ofR&D even in low R&D intensive industries.

Limitations

There are limitations to be kept in mind when evaluating these results. First, similarto 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 developthe relative pay equations, I cannot conclude that CEOs used this same information. Thedetermination of any given CEO’s comparison group can only be made by directlysurveying that CEO. Such data are difficult to obtain. March (1994) suggests thatbounded rationality limits decision-makers’ information gathering capability and capac-ity. Antle and Smith (1986) suggest firms in the same industry face similar economicconditions and risk. Thus, CEOs are likely to make within-industry comparisons on fairlytransparent variables (e.g. firm size, firm performance, human capital, and power) whenmaking decisions for the organization, so it would not be unrealistic to believe they wouldmake the same comparisons for their own pay and performance. The wage equationsaccount for many of these transparent variables as well as accounts for industry in theestimation technique (i.e. the wage equation accounts for making within industry com-parisons).[2] However, although the relative total, cash, and options pay equations explain45, 54, and 33 per cent of the variance in pay, respectively, there are other unmeasuredvariables that may explain variance in pay; for example, CEO specific variables such asCEO risk aversion. Future research that can gather data relating to CEO specificvariables not included in this study is warranted.



Second, as noted earlier, Ezzamel and Watson (1998) suggest that some compensationcommittees continually adjust CEO pay upward to account for the labour market, whichBebchuk and Fried (2004) contend may lead to a ‘ratchet effect’ on CEO pay. Thus,active compensation committees may recognize that their CEOs are underpaid relativeto the labour market and make adjustments, which should preclude CEOs in these casesfrom taking action into their own hands. Although the study includes controls for power,such controls may not account for compensation committee activism; however, activecompensation committees should only reduce the influence of CEO underpayment onR&D spending and thus reduce the chances of finding this relationship. Future researchshould examine the possibility that differences exist between the actions of CEOs withand without active compensation committees.

Third, although a time lag was used in the tests of the hypotheses, I cannot concludecausality. It is possible that CEOs who are less able to establish advantages using R&Dreceive less compensation and thus the expectation would be a decrease in future R&Dspending contingent on the CEOs current underpayment. Furthermore, it may be thatthe firm is attempting to reduce costs, which may lead to CEO underpayment andreductions of R&D in separate time periods.

Finally, care should be taken with the generalizability of the results. The data weretaken from publically traded firms in the United States and thus it is unclear whetherthese results generalize to executives in private, non-profit, or international firms as wellas 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, thisstudy 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, butit may be possible that equity theory oriented reactions differ across time periods.Furthermore, compensation alignment with R&D spending should be important in anytime 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 frommore recent time periods is warranted.

Conclusion

Prior research proposes the importance of accounting for social comparisons (Ezzameland Watson, 1998; Miller, 1995; Porac et al., 1999) when using compensation to moti-vate CEO actions. For example, Ezzamel and Watson (1998) suggest that compensationcommittees should pay close attention to the design of CEO compensation contractsbecause relatively under- or over-paying CEOs may create motivational problems. Thisstudy examines such motivational and behavioural issues by focusing on relative CEOpay and CEO behaviour towards firm level outcomes that may significantly impactlong-term shareholder maximization, specifically CEO behaviour towards R&D spend-ing. This study’s results support the proposition that relative underpayment may createmotivational and behavioural issues. Specifically, this study shows that social compari-sons may be motivating CEO behaviour such that underpaid CEOs engage in oppor-tunistic changes in R&D spending in response to their pay when they face lessmonitoring from owners or when they are in low R&D intensive industries, which is asituation where their short-term compensation is less likely to be tied to R&D spending.

E. A. Fong24


ACKNOWLEDGMENTS

The author thanks W. David Allen, Mary Gregory, Jatinder N. D. Gupta, and Allen Wilhite for theirsupport, comments, and suggestions.

NOTES

[1] To save space only the relative total pay equation is shown; however, the relative cash and relativeoptions pay equations follow the same format.

[2] In supplementary analyses not reported here, using only deviations from the mean CEO pay in theindustry to test the hypotheses provided substantively different results (marginal support for Hypothesis1 and no support for Hypotheses 2 and 3) from the analyses using the CEO wage equation. Suchsubstantive differences are expected given that the CEO wage equation accounts for CEO inputs whiledeviations from the mean CEO pay in the industry do not account for CEO inputs, an important aspectof 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 Crude petroleum & natural gas 7.42 2.912621 Paper mills 6.57 2.512670 Converted paper & paperboard products (no containers/boxes) 7.40 3.352711 Newspapers: publishing or publishing & printing 7.60 4.242834* Pharmaceutical preparations 7.83 5.362835* In vitro & in vivo diagnostic substances 6.26 2.002836* Biological products (no diagnostic substances) 6.52 2.912911 Petroleum refining 6.80 4.993312 Steel works, blast furnaces & rolling mills (coke ovens) 6.97 2.723571* Electronic computers 7.21 4.333576* Computer communications equipment 7.11 3.623661* Telephone & telegraph apparatus 6.80 2.983663* Radio & TV broadcasting & communications equipment 6.94 3.183674* Semiconductors & related devices 7.53 4.353714 Motor vehicle parts & accessories 7.02 2.223841* Surgical & medical instruments & apparatus 6.79 2.753845* Electromedical & electrotherapeutic apparatus 7.29 2.824813 Telephone communications (no radiotelephone) 7.38 3.764833* Television broadcasting stations 7.50 0.245411 Retail – grocery stores 6.48 0.755812 Retail – eating places 6.86 1.737011 Hotels & motels 6.86 1.007370* Services – computer programming, data processing, etc 7.48 4.257372* Services – prepackaged software 7.84 4.677373* Services – computer integrated systems design 6.13 2.647990 Services – miscellaneous amusement & recreation 7.33 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. highR&D intensive in the ‘industry type’ variable).



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