the relation between corporate governance and ceos’ equity grants

J. Account. Public Policy 29 (2010) 533–558

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J. Account. Public Policy

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The relation between corporate governance and CEOs’equity grants

Lawrence D. Brown a,⇑, Yen-Jung Lee b

a School of Accountancy, Accounting Department, Georgia State University, P.O. Box 4050, Atlanta, GA 30302-4050, USAb Department of Accounting, National Taiwan University, Roosevelt Road, Sec. 4, Taipai, Taiwan 10617, Taiwan

a r t i c l e i n f o a b s t r a c t

Article history:

0278-4254/$ - see front matter � 2010 Elsevier Indoi:10.1016/j.jaccpubpol.2010.09.008

⇑ Corresponding author. Tel.: +1 404 413 7205;E-mail addresses: [email protected] (L.D. Brown), yle

We investigate whether the firm’s corporate governance affects thevalue of equity grants for its CEO. Consistent with the managerialpower view, we find that more poorly-governed firms grant highervalues of stock options and restricted stock to their CEOs after con-trolling for the economic determinants of these grants. We showthat the negative relation between governance strength and equitygrants is not likely to be attributable to omitted economic factorsor substitution effects between governance strength and equityincentives. As further evidence consistent with the managerialpower view, we show that firms with poorer governance in thepre-Enron era cut back more on using employee stock options(ESOs) for their CEOs in the post-Enron era, a period when theaccounting and outrage costs of ESOs increased, consistent withpoorly-governed firms taking more advantage of opaque ESOaccounting rules than better-governed firms. We show that theassociation between governance strength and abnormal equitygrants is less negative in the post-Enron period than it was in thepre-Enron period, consistent with firms making more efficientequity-granting decisions after the corporate governance changesmandated by the Sarbanes–Oxley Act of 2002 and the major USstock exchanges took effect.

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1. Introduction

We investigate the effect of corporate governance on a firm’s CEO’s equity grants, defined as thesum of employee stock options (ESOs) and restricted stock. Corporate governance is a set of

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534 L.D. Brown, Y.-J. Lee / J. Account. Public Policy 29 (2010) 533–558

mechanisms that helps mitigate agency problems between managers and shareholders. Theoretically,CEO equity grants are an aspect of corporate governance because they tie the CEO’s personal wealth tohis firms’ stock price performance (Shleifer and Vishny, 1997; Core et al., 2003), reducing the possibil-ity the CEO takes suboptimal actions to harm shareholders. However, many practitioners, institutionalinvestors, shareholder activists, and academic researchers contend that, rather than being an effectivegovernance mechanism, equity grants are a manifestation of poor corporate governance (e.g., Biggs,2002; Gillan, 2001; Guay et al., 2003; Coombes, 2005).1

While there is evidence that poor governance is associated with excessive cash compensation (Coreet al., 1999), empirical evidence on the relation between corporate governance and employee equitygrants is limited. Prior research’s cash compensation results might not be generalizable to equitygrants because unlike cash compensation, employees are provided with stock options and restrictedstock for reasons besides conveying compensation. Indeed, survey and archival evidence suggest thatconveying compensation is not the primary reason for providing equity to employees.2 Himmelberget al. (1999) and Core and Guay (1999) show that equity grants are awarded to optimize employees’incentive levels and to maximize firm value, casting further doubt on whether the negative associationbetween governance strength and excess cash compensation pertains to the equity grant setting. We fillthis gap in the literature by examining how CEOs’ equity grants relate to firms’ board and ownershipstructure and exploring alternative explanations for the observed relation.

The extant executive compensation literature offers two distinct views on the relation betweencorporate governance and CEO equity awards: efficient contracting and managerial power. The effi-cient contracting view contends that boards grant optimal equity incentives that maximize firm value(e.g., Himmelberg et al., 1999; Core and Guay, 1999; Lambert and Larcker, 1987).3 If this view isdescriptively valid, there should be no systematic relation between corporate governance and the valueof CEO equity grants after controlling for their economic determinants. The managerial power view con-tends that CEOs exert substantial influence over corporate boards and structure compensation contractsto benefit themselves (e.g., Shleifer and Vishny, 1997; Murphy, 1999; Bebchuk and Fried, 2003). As such,weaker governance gives CEOs relatively more power vis-à-vis the board, allowing them to receive morecompensation than is economically justifiable. This second view predicts a negative association betweengovernance strength and the value of CEO equity grants.

To determine which view is more descriptive of reality, we use 8084 observations representing1719 firms from 1998 to 2006 with necessary compensation data from ExecuComp and governancedata from RiskMetrics to examine the relation between firms’ governance and grant-day fair valuesof new equity grants for their CEOs. Because governance mechanisms do not operate independentlyto resolve agency problems (Brown and Caylor, 2006), we consider jointly the structuring of internaland external governance. We use Core et al.’s (1999) 12 board and ownership structure variables tomeasure internal monitoring and Gompers et al.’s (2003) G-index to capture external monitoring.We use two methods, an equally weighted sum of the standardized governance variables and a factoranalysis on all governance measures, to collapse the 13 governance variables into one parsimoniousmeasure of overall governance strength.

Consistent with the managerial power view, we find a negative relation between governancestrength and the value of equity grants. The observed relation, however, is consistent with two alter-native explanations: (1) omitted economic factors affecting equilibrium equity compensation (omit-ted economic factors explanation); and (2) substitution effects between governance mechanisms

1 Although the use of restricted stock increased during our sample period, it accounted for a much smaller percent of totalcompensation as defined by ExecuComp than stock options, increasing from less than 4% in early 1990s to 6% in 2002 and 14% in2006.

2 Ittner et al. (2003) and Oyer and Schaefer (2005) report that retaining existing employees and attracting new employees arethe most important reasons for implementing equity grant programs. Lambert et al. (1991), Meulbroek (2001), and Hall andMurphy (2002) demonstrate that stock options and restricted stock are less efficient ways of conveying compensation than cashbecause equity grants impose incentive risk on employees.

3 Himmelberg et al. (1999) find that managerial ownership varies systematically in ways consistent with value maximization.Core and Guay (1999) demonstrate that firms use annual grants of options and restricted stock to achieve the optimal level ofequity incentives for their CEOs. Lambert and Larcker (1987) find that firms increase acquisition-related compensation for topexecutives only when the acquisition enhances shareholder value.

L.D. Brown, Y.-J. Lee / J. Account. Public Policy 29 (2010) 533–558 535

and equity incentives (substitution explanation). To ascertain the validity of the omitted economicfactors explanation, we examine how the portion of CEO equity grants explained by governance vari-ables affects future firm performance. Under the managerial power view, governance-motivated equi-ty grants reflect unresolved agency conflicts, which should not have a favorable effect on future firmperformance. In contrast, the omitted economic factors explanation suggests that the portion of equitygrants explained by governance variables proxies for demand for greater equilibrium equity compen-sation, which should not impair future firm performance. Regressing accounting earnings and abnor-mal stock returns over the three subsequent years on governance- and economic-explained equitygrant values, we find that governance-explained (economic-explained) equity grant value is nega-tively (positively) associated with future accounting and stock return performance, inconsistent withthe omitted economic factors explanation.

If equity grants are used to align managers’ and shareholders’ interests, firms should substituteequity incentives for active monitoring when direct monitoring by corporate boards is less cost-ben-eficial. To explore the substitution explanation, we sort all our observations into 2 � 2 = 4 portfoliosbased on overall governance strength and abnormal equity grants, which we define as the componentof equity grants not explained by economic determinants of these grants.4 If the substitution explana-tion is valid, firms with weaker governance and higher abnormal equity grants should outperform firmswith weaker governance and lower abnormal equity grants. We examine future accounting and stock re-turn performance for each of the four portfolios and do not obtain evidence consistent with the substi-tution explanation.

One obstacle hindering interpretation of our results is that both corporate governance and equitygrants are endogenously determined by such factors as monitoring costs, firm performance, andgrowth opportunities. Comparing compensation decisions between firms with different corporategovernance may capture effects of differences in firms’ operating environments. However, findinggood instruments for corporate governance to use in an instrumental variables approach that arestrongly correlated with the endogenous governance variable yet exogenous to the equity grant deci-sion is extremely difficult because both equity compensation and governance structure arise to ad-dress agency problems.5 We mitigate endogeneity concerns using two approaches.

Our first approach follows Bebchuk et al. (2008) and Dittmar and Mahrt-Smith (2007) wherein werepeat our analysis retaining firms from the second half of our sample period (2003–2006) and replacethe governance variables by their beginning-of-the-sample-period (i.e., 1998) values. Our rationale isthat since governance structure changes slowly over time, initial value of governance structure is lessaffected by future business and operating environments, making it more exogenous to future compen-sation decisions than contemporaneous governance structure.6 Consistent with our primary analysis,our results reveal that past corporate governance has a significantly negative effect on future abnormalequity grants.

As a second way to address endogeneity concerns, we examine changes in CEOs’ ESO grant valuesbetween the pre- and post-Enron eras, a period characterized by increased public attention to execu-tive compensation, many regulatory actions such as the Sarbanes–Oxley Act of 2002 and listingrequirements of the US stock exchanges, and issuance of Statement of Financial Accounting Standards123R (SFAS 123R) – Share-Based Payment (FASB, 2004) requiring ESOs to be expensed. Prior to SFAS123R, firms were not required to record any ESO expense as long as the ESO exercise price was notbelow the grant day market price of the underlying stock. Not surprisingly, virtually all ESOs weregranted ‘‘at-the-money,” i.e., their exercise price was set to the grant-date market price (Murphy,1999). ESOs’ zero accounting cost provided firms with both opportunities and incentives to extractexcessive compensation via ESOs. Under the managerial power view, CEOs of more poorly-governed

4 See Section 4.2 for further discussion.5 See Larcker and Rusticus (2010) for an excellent discussion of endogeneity problems and how the use of instrumental variables

in 2SLS models in accounting research are more problematic than simply using OLS.6 If the governance structure does not change at all, the initial governance structure is as endogenous as the contemporaneous

governance structure. All of our sample firms experience some changes in at least one of the 13 corporate governance variablesduring the 1998–2006 periods.


firms are more likely to take advantage of the lack of ESO expensing and award themselves more ESOsthan is justified by economic factors.

The mandatory expensing requirement along with the increased public scrutiny of executive com-pensation increased the accounting and outrage costs of ESOs (Bebchuk and Fried, 2003), forcing firmsusing ‘‘too many” ESOs in the pre-Enron period to scale back ESO use in the post-Enron era.7 Our find-ings suggest that controlling for the change in governance strength from the pre- to the post-Enronperiods, firms with weaker governance in the pre-Enron period cut back more on their ESO use in thepost-Enron period. Our evidence is consistent with CEOs of more poorly-governed firms granting them-selves more excessive ESOs in the pre-Enron period, adding support to the managerial power view. Wealso find the relation between governance strength and abnormal equity compensation became less neg-ative in the post-Enron period, consistent with firms moving toward more efficient contracting after thegovernance reforms initiated by the Sarbanes–Oxley Act of 2002 (SOX) and major stock exchanges tookeffect in the post-Enron period.8

We contribute to the literature in several ways. First, we add to the literature examining the rela-tion between governance and agency problems. While prior studies show that managers exercisepower to their own benefit (e.g., expropriating funds; empire building; consuming perquisites), directevidence relating corporate governance to equity grants is limited. Using proprietary data for 205firms from 1982–1984, Core et al. (1999) find that poorly-governed firms award their CEOs with morecash and total compensation.9 We complement and extend Core et al. (1999) for three reasons; theirresults may: (1) not pertain to equity compensation; (2) be sample specific; and (3) suffer from endoge-neity. To deal with these issues, we focus on equity compensation; we examine a more recent sample,including the post-Enron period that experienced significant governance reforms; and we use two pro-cedures to mitigate endogeneity concerns.

Second, we extend the literature examining substitution effects among governance mechanisms.Sundaramurthy et al. (1997) find that equity market investors react less negatively to anti-takeoverprovisions adopted by firms whose CEOs do not chair their boards than to anti-takeover provisionsadopted by firms with CEOs who chair their boards, consistent with capital markets perceiving stron-ger board monitoring substitutes for weak monitoring from the takeover market. Gillan et al. (2006)find firms with more independent boards have a higher G-Index, suggesting that the market for cor-porate control plays a less important monitoring role when firms have more powerful boards. We ex-tend the literature by showing that firms do not use incentive compensation to substitute for weakgovernance.

Third, we add to the literature linking corporate governance to financial reporting quality. Klein(2002) shows that corporate governance characteristics are associated with earnings managementby firms. Kanagaretnam et al. (2007) find better-governed firms experience less information asymme-try around quarterly earnings announcements. Eng and Mak (2003), Byard et al. (2006) and Kelton andYang (2007) demonstrate that the strength of a firm’s governance structure is positively related to thequality of the voluntary disclosures it provides to investors and financial analysts. Our findings areconsistent with weak governance allowing CEOs to take advantage of opaque ESO accounting to win-dow dress their financial statements (i.e., report higher accounting earnings) to their own benefit(rather than to stockholders’ benefit) in the pre-expensing period.

7 Bebchuk and Fried (2003) argue that under the managerial power view, the ‘‘outrage” costs limit managers’ ability to extractrents. If an executive’s compensation is perceived by outsiders as excessive, they may become outraged. This ‘‘outrage” is costly todirectors and executives as it causes them embarrassment and reputational harm. Opaque ESO accounting prior to SFAS 123Rallowed managers to camouflage their favorable compensation packages to avoid outrage by the public and shareholders. OnceSFAS 123R removed the favorable accounting treatment, ESO accounting could no longer be used to camouflage excessive ESOgrants, forcing boards to cut back on their ESO use that was not cost-beneficial.

8 The efficient contracting view predicts no relation between corporate governance and excess equity grants so a less negativerelation between them is consistent with firms moving toward more efficient contracting.

9 Core et al.’s (1999) total compensation results could be driven by cash compensation because cash compensation constitutesthe majority of CEOs’ compensation packages during their sample period. According to Hall and Liebman (1998), only 30% of Forbes500 CEOs receive new option grants in 1980, with the value of ESO grants (cash compensation) accounting for 19% (81%) of thetotal direct compensation, where direct compensation is defined as salary, bonus, and the value of annual stock option grants. By2000, 85% of the S&P 500 companies received new stock option grants, with the value of ESO grants (cash compensation)accounting for about 60% (40%) of total direct compensation (source: ExecuComp).


The rest of our paper proceeds as follows. Section 2 presents our research design. Section 3 de-scribes our data and reports the descriptive statistics. We show results of our multivariate analysesin Section 4 and of additional analyses in Section 5. Section 6 concludes.

2. Research design

We estimate the following Tobit model on a pooled cross-sectional and time-series basis to assessthe relation between governance strength and equity grants for the CEO10:

10 A Tcluster

11 In uand Guprice. Wprovide

12 ExeMerton

13 AntThus, Gentrenc

EQUITYi;t ¼ b0 þ b1GOVSCOREi;t�1ðGOVFACTORi;t�1Þ þ b2INCENRESIDi;t�1 þ b3SALESi;t�1

þ b4BMi;t�1 þ b5NOLi;t�1 þ b6SHORTFALLi;t�1 þ b7DIV CONSTRAINi;t�1

þ b8RETi;t�1 þ b9RETi;t þ b10INVOPPi;t�1 þ b11ROAi;t�1 þ b12STDROAi;t�1

þ b13STDRETi;t�1 þ b14NONEQCOMPi;t þX47

d¼1

BdIndustryDummiesd

þX2005

k¼1998

DkYearDummiesy þ fi;t ð1Þ

EQUITY is the logarithm of (1 + new equity grants to the CEO for the year), where new equity grantsto the CEO are the sum of the grant-day fair value of new ESOs as computed by ExecuComp and thegrant-day fair value of restricted stock.11,12 GOVSCORE and GOVFACTOR are measures of governancestrength. Corporate governance mechanisms used to mitigate agency conflicts between shareholdersand managers can be either internal (i.e., board of directors, insiders, and blockholders) or external(e.g., market for corporate control). We use takeover vulnerability, measured as a transformation ofthe Gompers et al. (2003) G-Index, to proxy for external governance strength, and we use board moni-toring and ownership structure, measured as do Core et al. (1999), to proxy for internal governancestrength. G-Index is based on 24 anti-takeover provisions from RiskMetrics and is determined by addingone point for each anti-takeover provision the firm has in place and zero otherwise. A higher G-indeximposes higher costs on takeover activities. We transform G-Index to takeover vulnerability using a lin-ear transformation, denoted VULNERABILITY = 24 � G-Index so that a larger value of VULNERABILITYindicates stronger external governance.13

Core et al. (1999) used 12 variables to measure internal governance strength: (1) CEOCHAIR, anindicator variable equal to one if the board chair is the firm’s CEO and zero otherwise; (2) BOARDSIZE,total number of board directors; (3) INSIDEDIR, percent of the board who are managers, retiredmanagers, or relatives of current managers; (4) HIREDBYCEO, number of outside directors appointedby the CEO, scaled by board size; (5) GRAYDIR, number of outside directors who are former employeesor whose employers have a financial relationship with the company, scaled by board size; (6)INTERLOCKDIR, number of outside directors who are interlocked (a director is interlocked if an insideofficer of the firm serves on the board of an outside director’s company), scaled by board size; (7)OLDDIR, number of outside directors over age 69, scaled by the number of outside directors; and(8) BUSYDIR, number of outside directors who serve on three or more other boards (six or more forretired outside directors), scaled by the number of outside directors. (9) CEOHOLDING, percent of

obit model is used because about 17% of our sample firm-years do not make any equity grants to their CEOs, resulting in aof zero values for EQUITY.ntabulated sensitivity analyses, we replace EQUITY with the incentives provided by new equity grants as defined by Core

ay (1999) as the change in the dollar value of the CEO’s new option and restricted stock grants for a 1% change in the stocke obtain inferentially similar results as those tabulated in the paper. The grant-date fair values of and the equity incentives

d by new option and restricted stock grants have a Pearson (Spearman) correlation of more than 95% (98%) in our sample.cuComp calculates the grant-day fair value of ESOs using the Black-Scholes (1973) option-pricing model as modified by(1973) to account for dividend payments.i-takeover provisions make it harder to replace incumbent management, giving managers more power over shareholders.-Index proxies for the extent to which managers are protected against takeovers (or the degree of managementhment).


the firm’s outstanding shares owned by the CEO; (10) NONCEOOWN5, indicator variable set equal toone if at least one inside board member other than the CEO owns 5% or more of the firm’s outstandingshares, and zero otherwise; (11) OUTDIROWN, percent of the firm’s outstanding shares owned byoutside directors divided by the number of outside directors; and (12) BLOCKHOLDER, indicatorvariable equal to one if the firm has an external blockholder who owns at least 5% of the its outstand-ing shares, and zero otherwise.

Because different governance mechanisms interact to achieve overall monitoring effectiveness(Brown and Caylor, 2006), we use an equally weighted sum of the standardized internal and externalgovernance variables, denoted GOVSCORE, to capture overall governance strength. Consistent withCore et al. (1999), we expect that higher values of internal governance variables (1)–(8) provide morepower to the CEO in its relationship with the board, and thus imply a weaker governance structure.Higher values of internal governance variables (9)–(12) indicate stronger non-CEO insider or outsideshareholder monitoring, suggesting a stronger governance structure. Variables (1)–(8) are multipliedby negative one before entering into the calculation of GOVSCORE. A higher value of GOVSCORE indi-cates stronger corporate governance.

One limitation of GOVSCORE is the need to form expectations about the direction that each gover-nance variable affects governance strength. As another way to measure overall governance strength,we perform a factor analysis on VULNERABILITY and the 12 internal governance variables.14 The factoranalysis does not rely on a priori expectations about the relation between each governance variable andoverall governance strength. Two factors result naturally from the factor analysis. The first one explains16% of the total variation, with loadings for the six internal corporate governance variables, OUTDIR-OWN, CEOHOLDING, INSIDEDIR, NONCEOOWN5, VULNERABILITY, and BOARDSIZE of 0.87, 0.70, 0.56,0.48, 0.35, and �0.33, respectively. The second one explains 6% of the total variation and loads on twointernal corporate governance variables, CEOCHAIR and HIREDBYCEO, with loadings of �0.45 and�0.36, respectively. These two factors appear to capture the intensity of board monitoring and the in-verse of CEO power respectively. We add the two standardized factor scores together to create a gover-nance strength factor, denoted GOVFACTOR.15 A larger GOVFACTOR indicates stronger corporategovernance.16

To isolate the abnormal portion of total equity grants, we control for the economic determinants ofequity use in executive compensation packages in Eq. (1). Core and Guay (1999) show firms grant few-er equity incentives to their CEOs when their CEOs’ pre-existing equity incentives exceed the optimalincentive level. Accordingly, we include the deviation of the CEO’s pre-existing equity incentives fromthe optimal incentive level, denoted INCENRESID, at the beginning of the year in Eq. (1). FollowingCore and Guay (1999), INCENRESID is the residual from a regression of the CEO’s equity incentives de-rived from stock option and restricted stock holdings on firm size, monitoring difficulty, growthopportunities, CEO tenure, and the free cash flow problem (see Core and Guay (1999) for details).We expect a negative coefficient on INCENRESID.

We control for the logarithm of total sales, denoted SALES, because Smith and Watts (1992) suggestthe level of CEO compensation is positively associated with firm sales. Core and Guay (1999) show firmsuse equity incentives to mitigate agency problems when monitoring employee efforts is costly.Following Core and Guay (1999), we presume shareholders face greater monitoring costs for firms with

14 We also report results using the 13 governance measures in lieu of GOVFACTOR in Panel B of Table 4. If the optimal contractingview is descriptive of reality, there should be no association between abnormal equity grants and governance strength. However, ifthe managerial power view is descriptive of reality, CEOCHAIR, BOARDSIZE, INSIDEDIR, HIREDBYCEO, GRAYDIR, INTERLOCKDIR,OLDDIR, and BUSYDIR (CEOHOLDING, NONCEOOWN5, OUTDIROWN, and BLOCKHOLDER) should be positively (negatively)associated with equity grants because they proxy for the CEO’s influence on the board (non-CEO owners’ monitoring), with higher(lower) values indicating greater potential for rent extraction.

15 We obtain qualitatively similar results if we constrain the factor analysis to only one factor. The resulting factor explains 17% ofthe total variation and loads on OUTDIROWN, CEOHOLDING, INSIDEDIR, NONCEOOWN5, VULNERABILITY, and BOARDSIZE withloadings of 0.87, 0.63, 0.61, 0.54, 0.35, and �0.32, respectively.

16 GOVSCORE and GOVFACTOR are intended to capture the strength of monitoring or governance. Stronger governance might notalways be optimal. For example, boards dominated by independent directors are considered stronger boards. However, a boardcomprised exclusively of outsiders might make poorer decisions than one with some insiders because outside directors possessless firm-specific knowledge and expertise than inside directors. Nevertheless, stronger internal and external monitoring make itharder for CEOs to exercise power over the board to influence their own pay.


greater growth opportunities (Smith and Watts, 1992) as proxied by a lower book-to-market ratio, de-noted BM. Measured as the book value of assets divided by the market value of assets, BM is used toproxy for growth opportunities, where market value of assets is the sum of book value of debt and mar-ket value of common equity. We expect positive and negative coefficients on SALE and BM respectively.

Prior studies contend that firms bear tax costs when substituting ESOs for other forms of compen-sation because there is no tax deduction for incentive ESOs and the tax deduction for nonqualifiedESOs is deferred until options are exercised. Therefore, substituting ESOs for other forms of compen-sation is costlier for firms with higher marginal tax rates. We use NOL to proxy for firms’ marginal taxrates. NOL is an indicator variable equal to one if the firm has net operating loss carry-forwards in anyof the previous three years, and zero otherwise. A positive NOL suggests a lower effective tax rate sowe expect the coefficient on NOL to be positive. Because granting ESOs requires no cash outlays, firmsfacing liquidity problems are more likely to use options in lieu of cash compensation to conserve cash.Following Core and Guay (1999), we include SHORTFALL, calculated as the three-year average of cashflow used in investing activities plus common and preferred dividends minus cash flow from opera-tions, all deflated by total assets. The coefficient on SHORTFALL is expected to be positive.

Dechow et al. (1996) and Core and Guay (1999) suggest ESO use is positively related to the extentto which lack of retained earnings constrains a firm’s ability to pay dividends and repurchase shares.We follow Dechow et al. (1996) and Core and Guay (1999) and measure the dividend constraint usingan indicator variable, DIV_CONSTRAIN, set equal to one if [(retained earnings + cash dividends + stockrepurchases)/the prior year’s cash dividends and stock repurchases] is less than 2.0 in any of the pre-vious three years, and zero otherwise. DIV_CONSTRAIN is also set equal to one if the denominator iszero for all three years. We expect the coefficient on DIV_CONSTRAIN to be positive. Core and Guay(1999) argue that the level of executive compensation is an increasing function of the firm’s stockprice performance. We include the prior year and the current year stock returns (LAGRET and RETrespectively) to control for the link between stock performance and CEO compensation and expectthe coefficients on lagged RET and RET to be positive.

In addition to the incentive, tax, and liquidity considerations, stock options and restricted stock canbe used to convey compensation. We control for the factors shown by Core et al. (1999) to be associ-ated with total compensation, including the firm’s investment opportunities (INVOPP), defined as thefirm’s year-end book-to-market ratio averaged over the five-year period ended the current year mul-tiplied by negative one. ROA is income before extraordinary items after ESO expense divided by laggedtotal assets.17 STDROA is the standard deviation of ROA for the five-year period ending the current year.STDRET is the standard deviation of RET for the five-year period ending the current year.

We include NONEQCOMP, measured as the logarithm of the CEO’s total compensation minus thegrant-day fair value of stock options and restricted stock. We make no prediction for this variable be-cause more talented managers may receive greater total and equity grants, implying a positive asso-ciation between NONEQCOMP and EQUITY, but if different forms of compensation substitute for eachother, granting non-equity compensation could reduce the need for granting stock options and re-stricted stock implying a negative association between EQUITY and NONEQCOMP. Industry dummiesare based on the 48 Fama and French (1997) industry classifications and year dummies are created forthe years included in our sample period. We use Petersen’s (2009) double cluster procedure to allowinter-correlations of residuals across firms and across time. The expected signs of the variables arepresented in Table 4.

3. Sample and descriptive statistics

Table 1 presents our sample selection procedures. Our initial sample begins with 14,056 firm-yearsbetween 1998 and 2006 that are covered by ExecuComp under the ExecuComp 1992 reporting format.We obtain compensation data from ExecuComp, corporate governance and G-Index data from

17 Virtually all firms accounted for ESOs using the intrinsic value method and did not include any ESO expense in their operatingexpenses prior to mid-2002. The intrinsic value of an ESO is equal to the market price of the underlying stock minus the optionexercise price. SFAS 123 requires firms using the intrinsic value method to disclose unrecognized ESO expense in a financialstatement footnote. This disclosed (pro forma) ESO expense is recorded in Compustat data XINTOPT.

Table 1Sample selection.

# of firm-years

All firm-years reporting under the ExecuComp 1992 reporting format between 1998 and 2006 with non-missing CEO compensation data

14,056

Less: firm-years with missing information about the grant-day fair value of stock options or restrictedstock

(107)

Less: firm-years without sufficient data on Compustat necessary to estimate the equity grants model (3451)Less: firm-years without sufficient data on CRSP necessary to estimate the equity grant model (94)Less: firm-years without sufficient data on RiskMetrics to construct governance variables (2320)

Sample firm-years 8084


RiskMetrics, stock price data from CRSP, financial data from Compustat, and institutional ownershipdata from Thomson Reuters. Our sample period begins in 1998 because the director ownership data,which are necessary for constructing ownership structure variables, became available on RiskMetricsin 1998; and it ends in 2006 because ExecuComp changed its reporting format in the 2006 fiscal year.The new reporting format discontinues the reporting of several data items necessary to estimateEq. (1).18,19

After excluding firms without necessary data, we are left with 8084 firm-years representing 1719firms from 1998–2006. Table 2 reports descriptive statistics for selected variables of interest. Panel Aprovides an overview of the CEO’s total compensation and compensation components. On average, oursample firm-years granted 3.5 (1.6) million dollars of equity (cash) compensation to their CEOs, with amedian of 1.3 (1.1) million. The mean grant-day fair value of stock options is 2.8 million, about fourtimes as large as the grant-day fair value of restricted stock. The average (median) CEO receives 5.6(2.9) million dollars of total compensation. Equity (cash) compensation accounts for 44% (48%) of totalcompensation for our average sample firm. About 17.29% of our sample firm-years do not grant anystock options or restricted stock. For firm-years that do grant equity-based compensation, the meanequity-based (cash) compensation granted to the CEO is about 53% (39%) of his total compensation.

Panel B of Table 2 reports descriptive statistics of the corporate governance variables. About 68% ofthe CEOs in our sample firm-years serve as chair of their firms’ boards. The average board consists of9.33 directors of which 26% are insiders, 37% are hired by the CEO, 7% are gray, and 1% is interlocked.On average, 12% of outside directors are over age 69 and 12% are classified as busy. The average CEOowns 3% of the firm’s outstanding equity, with a median of 1%. The mean ownership per outside direc-tor is 2% of the firm’s outstanding shares. About 86% of the sample firm-years have at least one exter-nal shareholder and 12% have at least one internal board member other than the CEO who owns atleast 5% of the firm’s outstanding shares. The mean (median) firm-year has 9.24 (9) anti-takeoverprovisions.

Panel C of Table 2 describes variables used in the regression analyses. To mitigate the undue influ-ence of outliers, we winsorize all continuous regression variables at the 1% and 99% levels. The medianlogarithm of equity grants is 7.14, about the same size as the median logarithm of non-equity compen-sation. The distribution of incentive residuals is skewed slightly to the left, with a mean (median) va-lue of 0.11 (0.08). Although the mean of the incentive residuals from estimating Eq. (2) should be zeroby construction, the mean incentive residual reported in Panel C of Table 2 is not zero because we esti-mate the portfolio incentive equation (i.e., Eq. (2)) using all ExecuComp observations with necessarydata and lose some observations due to the sample selection procedures described in Table 1.

18 This reporting format change is a response to the SEC’s executive compensation disclosure requirements, which took effect forproxy statements for fiscal years ending on or after December 15, 2006 and filed on or after December 15, 2006. The definition oftotal compensation and several compensation components are not directly comparable before and after the reporting formatchange.

19 For example, firms no longer disclose the grant-day fair value of restricted stock for the top five executives on their proxystatements but instead report the compensation expense related to restricted stock for the top five executives under SFAS 123R.Our initial (final) sample includes 285 (173) companies still reporting under the 1992 old format for 2006 fiscal year. Excludingthese firms yield qualitatively similar results to those tabulated.


Table 3 reports Pearson and Spearman correlations for selected regression variables. Consistent withthe managerial power view, EQUITY is negatively correlated with GOVSCORE and GOVFACTOR, suggest-ing that better-governed firms provide their CEOs with smaller values of stock options and restrictedstock. Consistent with firms using new equity grants to manage optimal equity incentives, EQUITY isnegatively correlated with lagged INCENRESID. Larger firms, firms with more growth opportunities,firms with net operating loss carry-forwards, and firms with more volatile operating income grant morestock options and restricted stock to their CEOs. Inconsistent with the notion that stock-based compen-sation substitutes for other forms of compensation, EQUITY is positively correlated with NONEQCOMP,suggesting that CEOs with more equity awards also receive higher non-equity compensation.

4. Multivariate analyses

4.1. The association between governance strength and ESO grant values

Panel A of Table 4 presents results from estimating Eq. (1). Columns 2 and 3 present the expectedsigns under the efficient contracting and managerial power views respectively. Models (1) and (2) re-port results when governance strength is measured by GOVSCORE and GOVFACTOR respectively. Con-sistent with the managerial power view, the coefficients on GOVSCORE and GOVFACTOR aresignificantly negative, suggesting that firms with stronger governance grant fewer abnormal equitygrants. The coefficient on the incentive residual is significantly negative, suggesting companies grantless equity-based compensation when the CEO’s existing stock and ESO holdings provide incentivesexceeding economically-justified levels. Most control variables have their expected signs and are sig-nificant. More specifically, equity grants are significantly greater for larger firms, firms that are morecash-constrained or dividend-constrained, and firms with better growth opportunities and lower mar-ginal tax rates. Equity grants are also positively associated with stock price performance.20

To assess the economic significance of governance strength on equity-based compensation, we cal-culate the marginal effect of all continuous (indicator) independent variables as the percentage changein the dollar amount of equity-based compensation for a change in the independent variable from the25th percentile to the 75th percentile of the variable in the sample (from 0 to 1), holding other inde-pendent variables at their mean values. The marginal effects of GOVSCORE and GOVFACTOR are�0.398 and �0.544, respectively, indicating CEOs receive 39.8% (54.4%) less equity awards when GOV-SCORE (GOVFACTOR) improves from the 25th to the 75th percentile. GOVSCORE and GOVFACTOR areamong the most economically significant variables in the model. The only two more influential deter-minants of equity grants are firm size and non-equity-based compensation, with marginal effects ofaround 70% and 50%, respectively.

For completeness, we replace both GOVSCORE and GOVFACTOR with the 13 governance variablesused to construct them. We report results in Panel B of Table 4. Model (1) presents results for Eq. (1)using only internal governance mechanisms. Firms with the following governance characteristics pro-vide their CEOs with more abnormal grants: (1) more outside busy directors; (2) CEO owns a lowerpercentage of the company’s outstanding shares; (3) no non-CEO insider owns 5% of the firm’s out-standing shares, and (4) lower percentage ownership per outside director. Consistent with Coreet al. (1999), we find that CEOs of firms with a higher percentage of inside directors receive less abnor-mal equity grants. Inconsistent with our prediction that older directors are less effective monitors, wefind firms with more outside directors over age 69 grant fewer abnormal equity grants.

4.2. Alternative explanations

We interpret our results in Section 4.1 as weaker corporate governance enables managers to exer-cise influence over boards and extract rents in the form of excess equity grants. However, the negative

20 Caution should be used when interpreting this result as evidence that companies reward higher stock price performance withmore equity grants because stock price directly affects the values of restricted stock and ESOs so the association between stockreturns and equity grants could be mechanical.

Table 2Descriptive statistics on selected variables (N = 8084).

Mean Std. dev Median Q1 Q3

Penal A: CEO compensation (thousands of dollars)(ESOt + RESTRICTEDt) 3544.81 13,158.6 1254.97 271.209 3451.94ESOt 2824.36 1,0551.5 915.450 80.7060 2773.63RESTRICTEDt 720.449 7630.89 0.0000 0.0000 203.000CASHt 1579.86 1773.59 1112.51 669.787 1906.55TOTCOMPt 5649.69 13,906.9 2916.24 1373.48 6003.77(ESOt + RESTRICTEDt)/TOTCOMPt (for all sample firm-years) 0.4419 0.2896 0.4721 0.2080 0.6741CASHt/TOTCOMPt (for all sample firm-years) 0.4752 0.2737 0.4246 0.2623 0.6546(ESOt + RESTRICTEDt)/TOTCOMPt (for 6686 firm-years that grant

equity comp)0.5332 0.2284 0.5437 0.3642 0.7108

CASHt/TOTCOMPt (for 6686 firm-years that grant equity comp) 0.3940 0.2064 0.3734 0.2384 0.5330Panel B: Descriptive statistics of governance variablesCEOCHAIRt�1 0.6813 0.4660 1.0000 0.0000 1.0000BOARDSIZEt�1 9.3340 2.4881 9.0000 7.0000 11.0000INSIDEDIRt�1 0.2576 0.1313 0.2308 0.1429 0.3333HIREDBYCEOt�1 0.3695 0.2492 0.3636 0.1667 0.5714GRAYDIRt�1 0.0730 0.1021 0.0000 0.0000 0.1250INTERLOCKDIRt�1 0.0100 0.0276 0.0000 0.0000 0.0000OLDDIRt�1 0.1187 0.1541 0.0000 0.0000 0.2000BUSYDIRt�1 0.1202 0.1510 0.0000 0.0000 0.2000CEOHOLDINGt�1 0.0335 0.0623 0.0116 0.0045 0.0292NONCEOOWN5t�1 0.1241 0.3297 0.0000 0.0000 0.0000OUTDIROWNt�1 0.0163 0.0276 0.0054 0.0017 0.0171BLOCKHOLDERt�1 0.8607 0.3463 1.0000 1.0000 1.0000VULNERABILITYt�1 14.7636 2.5781 15.0000 13.0000 17.0000GOVSCOREt�1 �0.1971 3.9499 �0.1903 �2.6891 2.1828GOVFACTORt�1 �0.0097 1.2986 �0.3691 �0.8786 0.3944Penal C: Descriptive statistics on selected regression variablesEQUITYt 6.1513 3.0823 7.1357 5.6066 8.1470NONEQCOMPt 7.1848 1.0250 7.1644 6.6184 7.7655INCENRESIDt�1 0.1081 0.9773 0.0773 �0.4889 0.6707SALEt�1 7.3360 1.5027 7.2308 6.3163 8.3392BMt�1 0.6422 0.2721 0.6505 0.4321 0.8476NOLt�1 0.3289 0.4699 0.0000 0.0000 1.0000SHORTFALLt�1 0.0099 0.0806 0.0027 �0.0339 0.0434DIV_CONSTRAINt�1 0.3564 0.4790 0.0000 0.0000 1.0000RETt 0.1367 0.4968 0.0775 �0.1594 0.3312RETt�1 0.1678 0.5204 0.1046 �0.1452 0.3663INVOPPt�1 �0.6217 0.2455 �0.6280 �0.4320 �0.8159ROAt�1 0.0387 0.1592 0.0450 0.0123 0.0873STDROAt�1 0.0566 0.0848 0.0308 0.0150 0.0640STDRETt�1 0.1277 0.0584 0.1128 0.0860 0.1561FUTABROAt 0.1358 0.3230 0.1405 0.0334 0.2822FUTABRETt 0.0028 0.0291 0.0027 �0.0092 0.0145

Panel A: This panel describes components of the CEO compensation. The sample covers 8084 firm-years from 1998 to 2006 inwhich equity grants were provided in 6686 firm-years. ESO is the grant day Black–Scholes value for stock option awards ascomputed by ExecuComp. RESTRICTED is the grant-day fair value of restricted stock awards. TOTCOMP is the total compen-sation, defined as the sum of base salary, bonus, grant-date Black–Scholes value of stock option awards, grant-date fair value ofrestricted stock awards, payouts under long-term incentive plans, other annual compensation, and all other compensation.CASH is cash compensation, calculated as the sum of salary and bonus.Panel B: The sample covers 8084 firm-years from 1998 to 2006. CEOCHAIR: indicator variable set equal to one if the CEO is alsochairman of the board, and zero otherwise. BOARDSIZE: number of directors on the board. INSIDEDIR: percent of the board whoare managers, retired managers, or relatives of current managers. HIREDBYCEO: number of outside directors on the boardappointed by the CEO as a percent of the board size. GRAYDIR: number of outside directors whose employers have a financialrelationship with the company or who are former employees of the company, as a percent of board size. INTERLOCKDIR:number of outside directors who are interlocked (a director is interlocked if an inside officer of the firm serves on the board ofan outside director’s company), as a percent of board size. OLDDIR: percent of outside directors who are over age 69. BUSYDIR:percent of outside directors who serve on three or more other boards (six or more for retired outside directors). CEOHOLDING:percent of outstanding shares owned by the CEO. NONCEOOWN5: indicator variable set equal to one if the firm has an internalboard member other than the CEO who owns at least 5% of the firm’s outstanding shares, and zero otherwise. OUTDIROWN:total percentage of outstanding shares owned by outside directors divided by the number of outside directors. BLOCKHOLDER:


indicator variable set equal to one if the firm has an external blockholder who owns at least 5% of the outstanding shares, andzero otherwise. GOVSCORE: an equally weighted sum of the standardized internal and external governance variables. Sincehigher values of the first eight internal governance variables indicate a board structure that provides more power to the CEO inits relationship with the board, these governance variables are multiplied by negative one before entering into the calculation ofGOVSCORE. GOVFACTOR is the sum of the two standardized factor scores resulting naturally from a factor analysis on all 13internal and external governance variables.Panel C: The sample covers 8084 firm-years from 1998 to 2006. To mitigate undue influence from outliers, all continuousvariables are winsorized at the 1% and 99% levels. EQUITY is the logarithm of (1 + new equity grants to the CEO for the year).New equity grants to the CEO is calculated as the sum of the grant-day fair value of new ESOs for the CEO as computed byExecuComp plus the grant-day fair value of restricted stock. INCENRESID is the residual from the following regression model.

EQPORTi;t ¼ a0 þ a1MVEi;t þ a2IDRISKi;t þ a3BMi;t þ a4TENUREi;t þ a5FCFi;t

þ IndustryDummiesþ YearDummiesþ ei;t

where EQPORT is the CEO’s total portfolio incentives from stock and option holdings at the end of the year. The incentives pro-vided by the CEO’s restricted stock holdings are estimated by multiplying year-end stock value by 1%. We use the proceduresoutlined in Core and Guay (1999) to estimate the incentives provided by the CEO’s option holding. Core and Guay (1999) breakthe total option holding into those options granted in the current year and those options granted in previous years. Incentivesfrom newly granted options are estimated as the sensitivity of the Black–Scholes value of the new option grant to a 1% change inthe year-end stock price. All the inputs required to calculate the Black–Scholes value – stock price, exercise price, time-to-matu-rity, stock return volatility, dividend yield, and the risk-free rate – are obtained from ExecuComp. Incentives from optionsgranted in previous years are measured using the weighted average exercise price and weighted average time-to-maturityas described in Core and Guay (1999). MVE is logarithm of the market value of equity. IDRISK is logarithm of the idiosyncraticrisk measured as the standard deviation of the residual from a 36-month market model regression. BM is book value of assetsdivided by market value of assets, where market value of assets is the sum of book value of debt and market value of commonequity. TENURE is CEO tenure, measured as the number of years between the year that the CEO first took office and the currentyear-end. FCF is the degree of the free cash flow problem measured as the three-year average (operating cash flow – commonand preferred dividends)/total assets if the firm has a book-to-market ratio greater than one (a proxy for low growth opportu-nities), and zero otherwise. SALE is the logarithm of sales. BM is the book-to-market ratio. NOL is an indicator variable set equalto one if the firm has net operating loss carry-forwards in any of the previous three years, and zero otherwise. SHORTFALL iscash flow shortfall, measured as the three-year average of cash flow used in investing activities plus common and preferreddividends minus cash flow from operations, all deflated by total assets. DIV_CONSTRAIN is an indicator variable set equal toone if [(retained earnings + cash dividends + stock repurchases)/the prior year’s cash dividends and stock repurchases] is lessthan 2.0 in any of the previous three years, and zero otherwise. DIV_CONSTRAIN is also set equal to one if the denominatoris zero for all three years. RET is the current stock return. INVOPP is the firm’s investment opportunities, calculated as negativeone multiplied by the firm’s year-end book-to-market ratio averaged over the five-year period ending the current year, wherethe market-to-book ratio is defined as the market value of equity plus the book value of debt divided by total assets. ROA isincome before extraordinary items after ESO expense divided by lagged total assets. STDROA is the standard deviation ofROA for the five-year period ending the current year. STDRET is the standard deviation of RET for the five-year period endingthe current year. FUTABROA is industry-adjusted operating performance, calculated as income before extraordinary items afterESO expense summed over the subsequent three years scaled by total assets at the end of the current year, denoted FUTROA,minus the industry median FUTROA, where the industry assignments are based on the 48 Fama–French industry classifications.FUTABRET is the intercept coefficient, or alpha, from the firm-specific Carhart’s (1997) four factor model estimated over thethree-year period following the end of the current year:

Ri;t ¼ aþ b1RMRFt þ b2SMBt þ b3HMLt þ b4Momentumt þ fi;t ð3Þ

where R is firm return minus risk-free rate, RMRF is the value-weighted market return minus the risk-free rate, and the termsSMB (small minus big), HML (high minus low), and Momentum are the monthly returns on zero-investment factor-mimickingportfolios capturing size, book-to-market, and momentum effects, respectively.


association between governance variables and the amount of equity grants is consistent with twoalternative explanations. First, governance variables could proxy for unspecified economic determi-nants of equity grants not captured in Eq. (1), such as the CEO’s job complexity or the CEO’s quality.Second, governance variables could reflect substitution between governance structure and incentivecompensation. We next perform tests to assess the validity of these two explanations.

4.2.1. Omitted economic factorsTo test for the omitted economic factors explanation, we examine how the component of equity

grants arising from governance factors relates to future performance. Bartov and Mohanram (2004)show excessive ESOs provide perverse incentives for managers to inflate short-term earnings andstock prices to increase cash payouts of ESO exercises. Bebchuk and Fried (2003) argue the largest costarising from managers’ ability to influence the boards’ compensation decisions is firm value loss due to

Table 3Correlation matrix on selected regression variables.

EQUITYt GOVSCOREt�1 GOVFACTORt�1 INCEN-RESIDt�1

SALEt�1

BMt�1

NOLt�1

SHORT-FALL t�1

DIV_CONSTRAINt�1

RETt INVOPPt�1 ROAt�1

STDROAt�1

STDRETt�1

NONEQCOMPt

EQUITYt 1.000 �0.215 �0.258 �0.080 0.255 �0.138 0.040 �0.026 �0.015 0.047 0.117 0.028 0.011 �0.035 0.280GOVSCOREt�1 �0.240 1.000 0.576 0.118 �0.416 �0.054 0.065 0.001 0.141 0.031 0.088 �0.039 0.175 0.309 �0.326GOVFACTORt�1 �0.273 0.537 1.000 0.145 �0.286 �0.069 �0.032 0.030 0.080 0.013 0.099 0.011 0.081 0.157 �0.273INCENRESIDt�1 �0.031 0.099 0.098 1.000 0.006 0.062 �0.008 0.033 0.012 0.017 �0.012 0.007 �0.025 �0.021 �0.035

SALEt�1 0.385 �0.430 �0.378 �0.003 1.000 0.093 �0.049 �0.198 �0.270 �0.032 �0.151 0.155 �0.328 �0.444 0.543BM t�1 �0.210 �0.073 �0.093 0.075 0.105 1.000 �0.023 0.148 �0.072 0.099 �0.863 �0.194 �0.206 �0.119 0.005NOLt�1 0.051 0.066 �0.006 �0.012 �0.042 �0.026 1.000 0.033 0.131 0.021 0.038 �0.110 0.137 0.216 �0.026

SHORTFALLt�1 �0.051 �0.019 0.024 0.021 �0.127 0.235 0.011 1.000 0.211 �0.045 �0.056 �0.393 0.222 0.219 �0.158

DIV_CONSTRAINt�1 �0.006 0.146 0.116 0.017 �0.260 �0.073 0.131 0.184 1.000 0.031 0.108 �0.156 0.323 0.415 �0.169RETt 0.052 0.007 �0.016 0.028 0.030 0.108 0.006 �0.102 �0.034 1.000 �0.033 �0.019 0.016 0.051 0.115

INVOPPt�1 0.186 0.099 0.121 �0.028 �0.162 �0.867 0.039 �0.129 0.108 �0.061 1.000 0.110 0.303 0.235 �0.090ROAt�1 0.082 �0.018 0.051 0.008 0.081 �0.528 �0.134 �0.351 �0.178 0.020 0.427 1.000 �0.373 �0.270 0.127

STDROAt�1 �0.002 0.251 0.173 �0.035 �0.399 �0.271 0.193 0.020 0.341 �0.051 0.382 �0.131 1.000 0.566 �0.214

STDRETt�1 �0.021 0.340 0.248 �0.005 �0.421 �0.104 0.230 0.081 0.399 �0.001 0.205 �0.218 0.623 1.000 �0.310

NONEQCOMPt 0.429 �0.365 �0.364 �0.004 0.648 �0.006 �0.027 �0.159 �0.191 0.200 �0.091 0.130 �0.276 �0.310 1.000

All variables are as defined in Table 2. Pearson (Spearman) correlation coefficients are in the upper (lower) triangle. Bold, italic, and underlined numbers indicate significance at the 0.01,0.05, and 0.10 levels or better, respectively.

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Table 4Tobit analysis of the relation between equity grants and corporate governance

EQUITYi;t ¼ b0 þ b1GOVSCOREi;t�1ðGOVFACTORi;t�1Þ þ b2INCENRESIDi;t�1 þ b3SALESi;t�1 þ b4BMi;t�1 þ b5NOLi;t�1

þ b6SHORTFALLi;t�1 þ b7DIV CONSTRAINi;t�1 þ b8RETi;t�1 þ b9RETi;t þ b10INVOPPi;t�1 þ b11ROAi;t�1

þ b12STDROAi;t�1 þ b13STDRETi;t�1 þ b14NONEQCOMPi;t þX47

d¼1

BdIndustryDummiesd

þX2005

k¼1998

DkYearDummiesy þ fi;t : ð1Þ

Variable Expected sign Expectedsign

Model (1) Model (2)

Efficientcontracting

Managerialpower

Coefficient(standard error)

Marginaleffect


Marginaleffect

Panel A: The relation between equity grant values and corporate governanceIntercept ? ? �0.016 0.860

(0.985) (0.799)GOVSCOREt�1 0 � �0.094*** �0.398

(0.012)GOVFACTORt�1 0 � �0.499*** �0.544

(0.038)INCENRESIDt�1 – – �0.242*** �0.251 �0.184*** �0.191

(0.054) (0.052)SALEt�1 + + 0.416*** 0.727 0.403*** 0.703

(0.044) (0.041)BMt�1 � � �1.110*** �0.390 �1.130*** �0.405

(0.136) (0.143)NOLt�1 + + 0.164** 0.133 0.087 0.072

(0.076) (0.072)SHORTFALLt�1 + + 0.934** 0.062 1.171*** 0.078

(0.458) (0.446)DIV_CONSTRAINt�1 + + 0.127* 0.104 0.124* 0.095

(0.076) (0.070)RETt�1 + + 0.027 0.011 0.044 0.018

(0.104) (0.104)RETt + + 0.320*** 0.134 0.349*** 0.143

(0.031) (0.030)INVOPP t�1 + + 0.733*** �0.251 0.808*** �0.268

(0.211) (0.201)ROA t�1 + + 0.020 0.002 0.094 0.006

(0.113) (0.102)STDROA t�1 ? ? 1.421*** 0.059 1.168*** 0.049

(0.405) (0.400)STDRETt�1 ? ? 1.912 0.116 1.806 0.106

(1.340) (1.780)NONEQCOMPt ? ? 0.573*** 0.537 0.528*** 0.496

(0.079) (0.075)Industry dummies Yes YesYear dummies Yes YesN 8084 8084Pseudo R2 0.0334 0.0375


Model (1) Model (2) Model (3)

Control variables Efficientcontracting

Managerialpower




Panel B: The relation between equity grant values and corporate governance with GOVINDEX replaced by five internalgovernance variables

Intercept ? ? 1.079 �1.325 2.467***

(1.517) (1.152) (1.212)

(continued on next page)


Table 4 (continued)


Model (1) Model (2) Model (3)

Control variables Efficientcontracting

Managerialpower




CEOCHAIRt�1 0 + 0.062 0.062(0.073) (0.075)

BOARDSIZEt�1 0 + 0.009 0.011(0.018) (0.018)

INSIDEDIRt�1 0 + �1.441*** �1.471***

(0.355) (0.357)HIREDBYCEOt�1 0 + 0.035 0.011

(0.110) (0.111)GRAYDIRt�1 0 + �0.187 �0.263

(0.521) (0.524)INTERLOCKDIRt�1 0 + 0.239 0.216

(1.635) (1.618)OLDDIRt�1 0 + �0.834*** �0.834***

(0.247) (0.246)BUSYDIRt�1 0 + 0.832*** 0.851***

(0.234) (0.236)CEOHOLDINGt�1 0 � �11.532*** �11.756***

(1.373) (1.406)NONCEOOWN5t�1 0 � �0.402** �0.405***

(0.154) (0.158)OUTDIROWNt�1 0 � �9.109*** �9.268**

(3.936) (3.965)BLOCKHOLDERt�1 0 � 0.117 0.112

(0.086) (0.087)VULNERABILITYt�1 0 � �0.082*** 0.002

(0.018) (0.016)INCENRESIDt�1 � � 0.186*** �0.282 0.198***

(0.046) (0.056)*** (0.047)SALEt�1 + + 0.353*** 0.485 0.336***

(0.042) (0.043)*** (0.042)BMt�1 � � �1.280*** �1.093 �1.175***

(0.127) (0.138)*** (0.125)NOLt�1 + + 0.047 0.140* 0.073

(0.065) (0.078) (0.065)SHORTFALLt�1 + + 0.515 1.243*** 0.934**

(0.415) (0.467) (0.407)DIV_CONSTRAINt�1 + + 0.132** 0.145* 0.136**

(0.062) (0.079) (0.064)RETt�1 + + 0.169 0.020 0.169

(0.101) (0.105) (0.101)RETt + + 0.408*** 0.315*** 0.389***

(0.024) (0.031) (0.025)INVOPP t�1 + + 0.576*** 0.838*** 0.692***

(0.176) (0.222) (0.176)ROA t�1 + + 0.118*** �0.017 0.249**

(0.039) (0.117) (0.098)STDROA t�1 ? ? 1.048*** 1.460*** 0.993***

(0.284) (0.424) (0.297)STDRETt�1 ? ? 2.763*** 1.801 2.597***

(0.760) (1.390) (0.782)NONEQCOMPt ? ? 0.439*** 0.604*** 0.457***

(0.061) (0.081) (0.063)Industry dummies Yes Yes YesYear dummies Yes Yes YesN 8084 8084 8084Pseudo R2 0.0446 0.0324 0.0452

Panel A: This panel provides Tobit results from estimating Eq. (1). Standard errors are calculated based on Petersen’s (2009)double cluster procedure to allow inter-correlations of residuals across firms or across time. All variables are as defined inTable 2. Coefficients on the industry and year dummies are suppressed for expositional convenience. Industry dummies are


created based on the Fama–French 48 industry classifications and the year dummies are created for the years included in oursample period.Panel B: This panel provides Tobit results from estimating Eq. (1). Standard errors are calculated based on Petersen’s (2009)double cluster procedure to allow inter-correlations of residuals across firms and across time. Coefficients on the industry andyear dummies are suppressed for expositional convenience. GOV is one of the following 13 internal or external governancemechanisms. CEOCHAIR: indicator variable set equal to one if the CEO is also chairman of the board, and zero otherwise.BOARDSIZE: number of directors on the board. INSIDEDIR: percent of the board who are managers, retired managers, orrelatives of current managers. HIREDBYCEO: number of outside directors on the board appointed by the CEO as a percent of theboard size. GRAYDIR: number of outside directors whose employers have a financial relationship with the company or who areformer employees of the company, as a percent of board size. INTERLOCKDIR: number of outside directors who are interlocked(a director is interlocked if an inside officer of the firm serves on the board of an outside director’s company), as a percent ofboard size. OLDDIR: percent of outside directors who are over age 69. BUSYDIR: percent of outside directors who serve on threeor more other boards (six or more for retired outside directors). CEOHOLDING: percent of outstanding shares owned by the CEO.NONCEOOWN5: indicator variable set equal to one if the firm has an internal board member other than the CEO who owns atleast 5% of the firm’s outstanding shares, and zero otherwise. OUTSIDEROWN: total percentage of outstanding shares owned byoutside directors divided by the number of outside directors. BLOCKHOLDER: indicator variable set equal to one if the firm hasan external blockholder who owns at least 5% of the outstanding shares, and zero otherwise. VULNERABILITY is equal to 24minus G-Index. All other variables are as defined in Table 2.

* Significant at the 0.1 level (two-tailed).** Significant at the 0.05 level (two-tailed).

*** Significant at the 0.01 level (two-tailed).


suboptimal incentives rather than the rents captured by managers. If the association between equitygrants and governance strength reflects managerial power, one would expect an unfavorable effect ofgovernance-explained equity grants on subsequent firm performance. In contrast, if governance struc-ture captures omitted economic factors that affect the equilibrium level of equity grants, we expect anon-negative effect of governance-predicted equity grants on subsequent firm performance.

We decompose equity grants into (1) governance factors (EQUITY_GOV); (2) economic factors(EQUITY_ECO); and (3) neither governance nor economic factors (EQUITY_RESID), and we estimatethe following equation:

21 We22 Cor

operatiperformgoverna

FUTABROAi;tþkðFUTABRETi;tþkÞ ¼ c0 þ c1EQCOMP GOVi;t þ c2EQCOMP ECOi;t

þ c3EQCOMP RESIDi;t þ c4ABROAi;tðABRETi;tÞ þ c5SIZEi;t

þ c6INVOPPi;t þ c7STDROAi;t þ c8STDRETi;t þ c9LEVERAGEi;t

þ IndustryDummiesþ YearDummiesþ fi;t ð2Þ

where FUTABROA is industry-adjusted return on assets, calculated as income before extraordinary itemsafter ESO expense summed over the subsequent three years scaled by total assets at the end of the currentyear, denoted FUTROA, minus the industry median FUTROA, where the industry assignments are basedon the 48 Fama–French industry classifications.21 FUTABRET is future abnormal stock return performance,measured as the intercept coefficient, or alpha, from the firm-specific Carhart’s (1997) four factor modelestimated over the three-year period following the end of the current year as follows:


where R is firm return minus the risk-free rate, RMRF is the value-weighted market return minus therisk-free rate, and SMB (small minus big), HML (high minus low), and Momentum are the monthly re-turns on zero-investment factor-mimicking portfolios capturing size, book-to-market, and pricemomentum effects, respectively.

EQUITY_GOV and EQUITY_ECO are the predicted components of equity grants arising from gover-nance and economic factors, respectively.22 Specifically, we compute predicted equity grants due to

obtain inferentially similar results if we use pre-ESO expense income to construct FUTROA.e et al. (2006) find that firms with weaker shareholder rights as proxied by a higher G-Index exhibit poorer one-year aheadng performance, suggesting that governance strength should be included in Eq. (2) as a determinant of future operatingance. However, because EQUITY_GOV is a linear transformation of GOVSCORE or GOVFACTOR, including these twonce strength variables along with EQUITY_GOV in Eq. (3) creates the perfect linearity problem.


governance factors for each firm-year, after controlling for the economic determinants of ESO grants asfollows:

EQUITY GOVi;t ¼ b1GOVSCOREi;t�1ðor GOVFACTORi;t�1Þ ð4Þ

where b1 is the estimated coefficient on GOVSCORE or GOVFACTOR reported in model (1) or model (2)in Panel A of Table 4.

We compute the predicted component of equity grants that is related to economic determinants foreach firm-year, after controlling for the corporate governance factors as follows:

EQUITY ECOi;t ¼ b2INCENRESIDi;t�1 þ b3SALESi;t�1 þ b4BMi;t�1 þ b5NOLi;t�1

þ b6SHORTFALLi;t�1 þ b7DIV CONSTRAINi;t�1 þ b8RETi;t�1 þ b9RETi;t

þ b10INVOPPi;t�1 þ b11ROAi;t�1 þ b12STDROAi;t�1 þ b13STDRETi;t�1

þ b14NONEQCOMPi;t þX47

d¼1

BdIndustryDummiesd ð5Þ

where bj is the estimated coefficient on each economic determinant j reported in either model (1) ormodel (2) of Panel A in Table 4. The residual equity grant value explained by neither economic nor gov-ernance factors, denoted EQUITY_RESID, is calculated as EQUITY minus (EQUITY_GOV + EQUITY_ECO).Given that EQUITY_GOV, EQUITY_ECO, and EQUITY_RESID are predicted values based on Eq. (1), stan-dard errors from the regular OLS for Eq. (2) are invalid. We use the bootstrap procedure described byCameron et al. (2008) to calculate bootstrapped clustered standard errors in both the firm and timedimension.

Barber and Lyon (1996) argue the importance of controlling for past performance when testing theassociation between corporate events and future firm performance because earnings are serially corre-lated and corporate events (granting ESOs in our case) may be correlated with recent firm performance.Therefore, we include current operating and abnormal stock return performance – ABROA or ABRET –in Eq. (2), where ABROA is ROA minus the median ROA for all firms in the same Fama–French 48 indus-try group and ABRET is the intercept coefficient from the firm-specific Carhart’s (1997) four factormodel estimated over the 12-month period ending the current year-end. We control for firm size (SIZE),investment opportunities (INVOPP), earnings volatility (STDROA), stock return volatility (STDRET) andfirm leverage (LEVERAGE) in the operating performance equation, where LEVERAGE is total debt di-vided by total assets and SIZE, INVOPP, STDROA, and STDRET are as defined in Section 2.

Panel A (Panel B) of Table 5 presents results for Eq. (2) when GOVSCORE (GOVFACTOR) measuresgovernance strength. Models 1 and 2 (3) and (4) report results when future performance is measuredby FUTABROA (FUTABRET). The coefficient on EQUITY_GOV (EQUITY_ECO) is significantly negative(positive) across both panels, consistent (inconsistent) with the managerial power view (economicfactor explanation).

4.2.2. SubstitutionThe negative association between governance structure and abnormal equity grants is also consis-

tent with the substitution between governance monitoring and incentive pay. Gillan et al. (2006)show board structures and anti-takeover provisions substitute for each other. The authors contendthat boards of directors monitor less in riskier/noisier environments because it is more difficult foroutsiders to determine the appropriateness of managers’ actions in these circumstances. When activemonitoring by shareholders is costly or ineffective, firms may substitute equity incentives such asESOs for active monitoring. If this explanation is valid, firms with weaker governance structure andgreater equity incentives should outperform firms with weaker governance structure and fewer equityincentives. Similarly, firms with lower equity incentives and stronger governance structure shouldoutperform firms with lower equity incentives and weaker governance structure.

To test for the substitution explanation, we examine how overall governance strength andincentive compensation interact to affect future firm performance. We classify all firms into

Table 5The relation between future performance and components of equity grants.

FUTABROAi;tþkðFUTABRETi;tþkÞ ¼ c0 þ c1EQUITY GOVi;t þ c2EQUITY ECOi;t þ c3EQUITY RESIDi;t

þ c4ABROAi;tðABRETi;tÞ þ c5SIZEi;t þ c6INVOPPi;t þ c7STDROAi;t þ c8STDRETi;t

þ c9LEVERAGEi;t þ IndustryDummiesþ YearDummiesþ fi;t : ð2Þ

Variable Coefficient (standard error) Coefficient (standard error)Model (1) Model (2)

Panel A: OLS regression of future performance on components of equity grants when governance strength is measured byGOVSCORE

Intercept 0.050 0.000(0.241) (0.004)

EQUITY_GOVt �0.041*** �0.004***

(0.012) (0.001)EQUITY_ECOt 0.091*** 0.003***

(0.014) (0.001)EQUITY_RESIDt �0.001 0.000

(0.001) (0.000)ABROAt 1.153***

(0.065)ABRETt 0.006

(0.015)SIZEt �0.035*** �0.001***

(0.005) (0.000)INVOPPt 0.211*** 0.001

(0.027) (0.002)STDROAt 0.046 0.001

(0.081) (0.007)STDRETt �0.627*** �0.011

(0.141) (0.012)LEVERAGEt �0.011 �0.003

(0.027) (0.003)Industry dummies Yes YesYear dummies Yes YesN 7535 7522Adj. R2 0.6266 0.0514

Panel B: OLS regression of future performance on components of equity grants when governance strength is measured byGOVFACTOR

Intercept 0.047*** 0.000(0.239) (0.005)

EQUITY_GOVt �0.021*** �0.002***

(0.005) (0.001)EQUITY_ECOt 0.098*** 0.0013***

(0.015) (0.0007)EQUITY_RESIDt �0.001 0.0001

(0.001) (0.0002)ABROAt 1.156***

(0.062)ABRETt 0.007

(0.016)SIZEt �0.038*** �0.001***

(0.005) (0.000)INVOPPt 0.203*** 0.000

(0.028) (0.002)STDROAt 0.047 0.001

(0.085) (0.008)STDRETt �0.619*** �0.012

(0.135) (0.012)LEVERAGEt �0.008 �0.003

(0.027) (0.003)Industry dummies Yes Yes

(continued on next page)


Table 5 (continued)


Year dummies Yes YesN 7535 7522Adj. R2 0.6265 0.051

This table presents OLS results from estimating Eq. (2). Standard errors are calculated based on the Cameron et al.’s (2008)bootstrapped clustered standard errors in both a firm and time dimension. Coefficients on the industry and year dummies aresuppressed for expositional convenience. FUTABROA is industry-adjusted operating performance, calculated as income beforeextraordinary items after ESO expense summed over the subsequent three years scaled by total assets at the end of the currentyear, denoted FUTROA, minus the industry median FUTROA, where the industry assignments are based on the 48 Fama–Frenchindustry classifications. FUTABRET is the intercept coefficient, or alpha, from the firm-specific Carhart’s (1997) four factor modelestimated over the three-year period following the end of the current year as follows:


where R is firm return minus risk-free rate, RMRF is the value-weighted market return minus the risk-free rate, and the termsSMB (small minus big), HML (high minus low), and Momentum are the monthly returns on zero-investment factor-mimickingportfolios capturing size, book-to-market, and price momentum effects, respectively. EQUITY_GOV and EQUITY_ECO are thepredicted components of equity grants arising from governance and economic factors, respectively. EQUITY_GOV is computedas follows:

EQUITY GOVi;t ¼ b1GOVSCOREi;t�1 ð4Þ

where b1 is the estimated coefficient on GOVSCORE reported in model (1) of Panel A in Table 4.

EQUITY ECOi;t ¼ b2INCEN RESIDi;t�1 þ b3SALESi;t�1 þ b4BMi;t�1 þ b5NOLi;t�1 þ b6SHORTFALLi;t�1

þ b7DIV CONSTRAINi;t�1 þ b8RETi;t�1 þ b9RETi;t þ b10INVOPPi;t�1 þ b11ROAi;t�1 þ b12STDROAi;t�1

þ b13STDRETi;t�1 þ b14NONEQCOMPi;t þX47

d¼1

BdIndustryDummiesd ð5Þ

where bj is the estimated coefficient on each economic determinant j reported in model (1) of Panel A in Table 4. The residualequity grant value explained by neither economic nor governance factors, denoted EQUITY_RESID, is calculated as EQUITYminus the sum of EQUITY_GOV and EQUITY_ECO. Size is the logarithm of total assets. Industry dummies are based on the48 Fama–French industry classifications. All other variables are as defined in Table 2.




2 � 2 = 4 portfolios based on median values of governance strength and excessive equity grants.23 Wedefine excessive (or abnormal) equity grants, denoted EXCESS_EQUITY, as the portion of equity grantsnot explained by economic determinants and industry dummies specified in Eq. (1).24 Specifically,EXCESS_EQUITY is the residual from the following regression:

23 Forsimilarone yea

24 Sor

EQUITYi;t ¼ h0 þ h1INCENRESIDi;t�1 þ h2SALESi;t�1 þ h3BMi;t�1 þ h4NOLi;t�1

þ h5SHORTFALLi;t�1 þ h6DIV CONSTRAINi;t�1 þ h7RETi;t�1 þ h8RETi;t

þ h9INVOPPi;t�1 þ h10ROAi;t�1 þ h11STDROAi;t�1 þ h12STDRETi;t�1

þ h13NONEQCOMPi;t þX47

d¼1

/dIndustryDummiesd þ fi;t ð6Þ

Panel A of Table 6 presents the mean and median FUTABROA for each of the four portfolios. Holdinggovernance strength constant at the weak level, firms with higher EXCESS_EQUITY report a mean

brevity, we only tabulate the results when governance strength is measured by GOVSCORE but we obtain qualitativelyresults if governance strength is measured by GOVFACTOR. Measuring future income and cash flows over the subsequentr rather than three years does not alter our inferences.

ting all firms first on GOVERNANCE and then on EXCESS_EQUITY yields inferentially similar results.

Table 6Test of the substitution explanation.

Mean [median] EXCESS_EQUITY t-test Wilcoxon

GOVSCORE Low High p-value for High–Low

Panel A: Mean [median] future operating performance measured as income before extraordinary items after ESO expensecumulated over the three-year period subsequent to the grants of stock options and restricted stock (FUTABROA)

Weak 0.1828 0.1243 <0.0001[0.0834] [0.0570] [<0.0001]

Strong 0.1933 0.1532 <0.0001[0.1343] [0.1025] [<0.0001]

p-value for strong–weak 0.0417 0.0043[<0.0001] [<0.0001]

Panel B: Mean [median] abnormal return over the three-year period subsequent to the grants of stock options and restrictedstock (FUTABRET)

Weak 0.0024 0.0016 <0.0001[0.0031] [0.0025] [0.0059]

Strong 0.0040 0.0036 0.1300[0.0041] [0.0039] [0.3012]

p-value for strong–weak 0.0571 0.0053[0.040] [<0.0001]

Panel A: We sort all firm-years independently into 2 � 2 portfolios based on median values of GOVSCORE and EXCESS_EQUITY.We report the mean and median industry-adjusted future accounting earnings (FUTABROA) measured as income beforeextraordinary items after ESO expense summed over the subsequent one year (three years) scaled by total assets at the end ofthe current year, denoted FUTROA, minus industry median FUTROA, where the industry assignments are based on the 48 Fama–French industry classifications. EXCESS_EQUITY is the residual from Eq. (6). All variables are as defined in Table 2.

EQUITYi;t ¼ h0 þ h1INCENRESIDi;t�1 þ h2SALESi;t�1 þ h3BMi;t�1 þ h4NOLi;t�1 þ h5SHORTFALLi;t�1

þ h6DIV CONSTRAINi;t�1 þ h7RETi;t�1 þ h8RETi;t þ h9INVOPPi;t�1 þ h10ROAi;t�1 þ h11STDROAi;t�1

þ h12STDRETi;t�1 þ h13NONEQCOMPi;t þX48

d¼1

/dIndustryDummiesd þ fi;t : ð6Þ

Panel B: We sort all firm-years independently into 4 � 4 portfolios based on GOVSCORE and EXCESS_EQUITY. We report themean and median industry-adjusted abnormal return performance (FUTABRET). FUTABRET is the intercept coefficient, or alpha,from the firm-specific Carhart’s (1997) four factor model estimated over the three-year period following the end of the currentyear:


where R is firm return minus risk-free rate, RMRF is the value-weighted market return minus the risk-free rate, and the termsSMB (small minus big), HML (high minus low), and Momentum are the monthly returns on zero-investment factor-mimickingportfolios capturing size, book-to-market, and price momentum effects, respectively. EXCESS_EQUITY is the residual from Eq.(6). All variables are as defined in Table 2.

EQUITYi;t ¼ h0 þ h1INCENRESIDi;t�1 þ h2SALESi;t�1 þ h3BMi;t�1 þ h4NOLi;t�1 þ h5SHORTFALLi;t�1

þ h6DIV CONSTRAINi;t�1 þ h7RETi;t�1 þ h8RETi;t þ h9INVOPPi;t�1 þ h10ROAi;t�1 þ h11STDROAi;t�1

þ h12STDRETi;t�1 þ h13NONEQCOMPi;t þX48

d¼1

/dIndustryDummiesd þ fi;t : ð6Þ


(median) FUTABROA of 0.1243 (0.0570), which is significantly below the 0.1828 (0.0834) reported byfirms with lower EXCESS_EQUITY, implying that firms with larger EXCESS_EQUITY grants do not out-perform firms with smaller EXCESS_EQUITY grants, inconsistent with the substitution explanation.Keeping overall excessive compensation at the low level, the mean FUTABROA for firms with strongergovernance is significantly higher than that for firms with weaker governance. However, strongergovernance is associated with a higher future operating performance regardless of the level ofEXCESS_EQUITY. Similar results are obtained from Panel B of Table 6 when future performance ismeasured by abnormal stock return relative to the Carhart’s (1997) four factor model. In sum, our


results suggest that the substitution effect is not a valid explanation for the negative associationbetween governance strength and ESO grant values.25

5. Additional analyses

5.1. Endogeneity

The negative association between corporate governance and abnormal equity grants could bedriven by unmodeled or imperfectly measured factors affecting both governance structure and equitygrants. Ideally, we would adopt an instrumental variable approach to mitigate endogeneity effects. Butthe choice of appropriate instruments is very challenging in our context since prior studies (Fama andJensen, 1983; Demsetz and Lehn, 1985; Coles et al., 2006) show that a firm’s governance structure isaffected by its growth potential, operational complexity, recent performance, and uncertainty in itsbusiness and information environments. Virtually all of these factors also affect firms’ decisions touse equity grants (e.g., Core et al., 1999; Ittner et al., 2003), making it virtually impossible to findappropriate instruments (Larcker and Rusticus, 2010). To mitigate endogeneity concerns, we usetwo tests that do not require instrumental variables.

First, following Bebchuk et al. (2008) and Dittmar and Mahrt-Smith (2007), we repeat the analysisin Panel A of Table 4 retaining only observations from the second half of our sample period (2003–2006) and replacing GOVSCORE and GOVFACTOR by their 1998 (beginning of our sample period) val-ues, denoted GOVSCORE98 and GOVFACTOR98 respectively. The results confirm our previous findings:GOVSCORE98 and GOVFACTOR98 remain significantly negative, suggesting that governance structuresin earlier years affect the compensation decisions in later years. The control variables behave similarlyto those reported in Panel A of Table 4.

Second, we examine ESO changes post versus pre-Enron. Following Enron and other major US cor-porate scandals, public attitude turned against ESOs because excessive option grants were blamed forcreating perverse incentives for managers to commit accounting frauds. The post-Enron era featuredincreased media attention on executive compensation, institutional shareholder activism, and variouscorporate reforms, including the Sarbanes–Oxley Act of 2002 and reforms initiated by the major USstock exchanges. Moreover, the FASB passed SFAS 123R on December 16, 2004, requiring firms to rec-ognize compensation expense equal to grant-day fair value of ESOs on their income statements.

Prior to SFAS 123R, GAAP allowed firms to avoid any compensation expense if they granted ESOswith an exercise price not lower than the grant-date market price of the underlying stock (knownas the intrinsic value method) provided they disclosed information about the grant-date fair valueof ESO grants in the financial statement footnotes. ESOs bore zero accounting cost if they were notgranted in the money. Bodie et al. (2003) argued that failure to recognize ESO expense provided an‘‘accounting subsidy to stock options”, encouraging firms to use ESOs to excess because other formsof compensation required expensing. Making compensation decisions based on ESOs’ zero accountingcost rather than a more precise estimate of their true economic cost harms shareholders because itresults in compensation arrangements providing worse incentives than ones provided by arms’ lengthcontracts. Bebchuk and Fried (2003) argue that the economic loss in shareholder value resulting fromsuboptimal incentives exceeds the excess equity compensation captured by managers.

The managerial power view predicts that firms with poorer corporate governance are more likely toexercise power over weak corporate governance and extract excessive compensation in the form ofESOs. The intensified public scrutiny and the mandatory ESO expensing requirement in the post-Enronperiod increased the visibility of ESOs and drew more attention to the real cost of stock options, makingit harder for firms to justify excessive executive pay (Guay et al., 2003). If poor corporate governancefacilitated excessive ESO use, we expect a greater decrease in ESO use in the post-Enron period for firmswith poorer corporate governance, controlling for the change in governance strength from the pre- tothe post-Enron periods. To test this prediction, we estimated the following OLS regression:

25 We obtain similar results if we measure future operating performance using cumulative operating cash flows over the nextthree years and future stock return performance using size-adjusted buy-and-hold returns over the next three years.

Table 7Changes in ESO grant values pre- versus post-Enron

DIFFOPTIONi ¼ c0 þ c1GOVSCORE9801iðGOVFACTOR9801iÞ þ c2DIFFRSTKi

þ c3DIFFGOVSCOREiðor DIFFGOVFACTORiÞ þ c4DIFFINCENRESIDi þ c5DIFFSALEi þ c6DIFFBMi

þ c7DIFFNOLi þ c8DIFFSHORFALLi þ c9DIFFDIVCONSTRAINi þ c10DIFFLAGRETi þ c11DIFFRETi

þ c12DIFFINVOPPi þ c13DIFFROAi þ c14DIFFSTDROAi þ c15DIFFSTDRETi þ c16DIFFNONEQCOMPi

þ IndustryDummies þ ni: ð7Þ


Intercept 1.941*** 1.961**

(0.372) (0.376)GOVSCORE9801 0.073***

(0.026)GOVFACTOR9801 0.211***

(0.079)DIFFRSTK �0.011 �0.014

(0.040) (0.040)DIFFGOVSCORE 0.035

(0.041)DIFFGOVFACTOR 0.091

(0.128)DIFFINCENRESID �0.085 �0.052

(0.128) (0.129)DIFFSALE 0.143 0.136

(0.228) (0.225)DIFFBM 0.230 0.256

(0.929) (0.915)DIFFNOL 0.183 0.218

(0.255) (0.259)DIFFSHORTFALL �0.027 �0.026

(1.392) (1.387)DIFFDIVCONSTRAIN �0.178 �0.232

(0.261) (0.259)DIFFLAGRET 0.540* 0.537*

(0.328) (0.321)DIFFRET 0.702** 0.711**

(0.288) (0.285)DIFFINVOPP 3.732*** 3.691***

(0.980) (0.963)DIFFROA �1.463 �1.335

(1.348) (1.345)DIFFSTDROA 0.480 0.311

(1.569) (1.584)DIFFSTDRET �5.280* �4.811

(3.046) (3.073)DIFFNONEQCOMP 0.384*** 0.377***

(0.148) (0.146)

Industry dummies Yes YesN 1007 1007Adj. R2 0.0331 0.0334

This panel presents OLS results from estimating Eq. (7). t-statistics are Huber–White sandwich robust standard errors. Coef-ficients on the industry and year dummies are suppressed for expositional convenience. DIFFOPTION is the average OPTIONover the post-Enron period (2002–2006) minus the average OPTION over the pre-Enron period (1998–2001), where OPTION isdefined as the logarithm of (1 + grant-day fair value of ESOs for the CEO). GOVSCORE9801 and GOVFACTOR9801 are the meanGOVSCORE and GOVFACTOR over the pre-Enron period (1998–2001), respectively. DIFFRSTK is the average RSTK over the post-Enron period (2002–2006) minus the average RSTK over the pre-Enron period (1998–2001), where RSTK is the logarithm of(1 + grant-day fair value of restricted stock for the CEO). We include the change in the grant-day fair value of restricted stockfrom the pre- to the post-Enron period, denoted DIFFRSTK, to control for the potential substitution between ESOs and restrictedstock. DIFF_Y is average Y over 2002–2006 minus average Y over 1998–2001, where Y is one of the 14 independent variables inEq. (1).




26 Our27 To

mechanand posthe pos2006) mgoverna


DIFFOPTIONi ¼ c0 þ c1GOVSCORE9801iðGOVFACTOR9801iÞ þ c2DIFFRSTKi

þ c3DIFFGOVSCOREiðor DIFFGOVFACTORiÞ þ c4DIFFINCENRESIDi

þ c5DIFFSALEi þ c6DIFFBMi þ c7DIFFNOLi þ c8DIFFSHORFALLi

þ c9DIFFDIVCONSTRAINi þ c10DIFFLAGRETi þ c11DIFFRETi

þ c12DIFFINVOPPi þ c13DIFFROAi þ c14DIFFSTDROAi þ c15DIFFSTDRETi

þ c16DIFFNONEQCOMPi þ IndustryDummiesþ ni ð7Þ

The dependent variable, DIFFOPTION, is the average OPTION over the post-Enron period (2002–2006) minus the average OPTION over the pre-Enron period (1998–2001), where OPTION is the loga-rithm of (1 + grant-day fair value of ESOs for the CEO).26 A smaller DIFFOPTION indicates a greater de-crease in ESO grant values post-Enron. GOVSCORE9801 and GOVFACTOR9801 are the mean GOVSCOREand GOVFACTOR in the pre-Enron period (1998–2001). We include the change in grant-day fair value ofrestricted stock from the pre- to the post-Enron period, denoted DIFFRSTK, to control for the potentialsubstitution between ESOs and restricted stock. DIFFRSTK is calculated as average RSTK over the post-Enron period (2002–2006) minus average RSTK over the pre-Enron period (1998–2001), where RSTKis the logarithm of (1 + grant-day fair value of restricted stock for the CEO). DIFF_Y is average Y over2002–2006 – average Y over 1998–2001, where Y is one of the 14 independent variables in Eq. (1).

Table 7 shows the coefficients on GOVSCORE9801 and GOVFACTOR9801 are significantly positive,suggesting that firms with weaker (stronger) corporate governance cut back more (less) on ESO useafter controlling for changes in ESO determinants, including changes in governance structure. Insum, our evidence is consistent with the prediction of the managerial power view that poorly-gov-erned firms took greater advantage of ESO accounting pre SFAS 123R to award their CEOs with moreESOs than are justifiable economically.27

5.2. Does the link between corporate governance and the CEO’s equity grants change in the post-Enronperiod?

The failure of Enron and other high-profile U.S. publicly-traded companies led to a wave of regu-lation aimed at improving firms’ corporate governance. For example, the Sarbanes–Oxley Act of2002 mandated all members of publicly-traded firms’ audit committees be independent. Soon afterthe SOX enactment, the New York Stock Exchange and the NASDAQ Stock Market required all publicfirms to have a majority of independent directors (Brown and Caylor, 2009). We examine how the linkbetween poor corporate governance and excess equity compensation changed between the pre- andthe post-Enron period when corporate governance experienced significant exogenous shocks as a re-sult of governance reforms initiated by these regulations. To do so, we create an indicator variable, de-noted POST, set equal to one if the observation is from 2002–2006 and zero otherwise. We includeboth POST and the interaction between governance strength and POST into Eq. (1). We re-estimatethe resulting equation and report the results in Table 8. The coefficients on GOVSCOREt�1 � POSTand GOVFACTORt�1 � POST are both significantly positive, suggesting the relation between gover-

results in this section are robust to the exclusion of firms that voluntarily expensed stock options before 2002.ensure the negative association between the change in ESO grant values and pre-Enron governance structure is notical or documented by chance, we perform two pseudo changes analyses. Specifically, we rerun equation (6) for the pre-t-Enron periods separately. For the pre- (post-) Enron regression, we define the pre-period as 1998–1999 (2002–2003), andt-period as 2000–2001 (2004–2006). All changes variables are calculated as the average values over 2000–2001 (2004–

inus the average values over 1998–1999 (2002–2003). We do not find a significant coefficient on the pre-periodnce strength in either of the two pseudo changes regressions.

Table 8The relation between equity grant values and corporate governance pre- versus post-Enron

EQUITYi;t ¼ b00 þ b01GOVi;t�1 þ b02POST þ b03GOVi;t�1 � POST þ b04INCENRESIDi;t�1 þ b05SALESi;t�1 þ b06BMi;t�1 þ b07NOLi;t�1

þ b08SHORTFALLi;t�1 þ b09DIV CONSTRAINi;t�1 þ b010RETi;t�1 þ b011RETi;t þ b012INVOPPi;t�1 þ b013ROAi;t�1

þ b014STDROAi;t�1 þ b015STDRETt�1 þ b016NONEQCOMPi;t þX47

d¼1

BdIndustryDummiesd þX2005

k¼1998

DkYearDummiesy

þ fi;t :

Variable Model (1) Model (2)Coefficient (standard error) Coefficient (standard error)

Intercept 1.206*** 3.526***

(4.29) (2.72)GOVSCOREt�1 �0.101***

(�5.19)GOVFACTORt�1 �0.538***

(�12.62)POST �2.166*** �2.684***

(�10.27) (�11.81)GOVSCOREt�1 � POST 0.015*

(1.98)GOVFACTORt�1 � POST 0.082**

(2.11)INCENRESIDt�1 �0.241*** �0.181***

(�4.47) (�3.47)SALESt�1 0.416*** 0.403***

(9.48) (9.79)BMt�1 �1.084*** �1.096***

(�8.04) (�7.77)NOLt�1 0.165** 0.089

(2.18) (1.23)SHORTFALLt�1 0.949** 1.194***

(2.07) (2.67)DIV_CONSTRAINt�1 0.128* 0.115

(1.74) (1.64)RETt�1 0.048 0.064

(0.32) (0.51)RETt 0.320*** 0.349***

(11.96) (11.60)INVOPPt�1 �0.762 �0.845***

(�3.79) (�4.27)ROAt�1 0.022 0.102

(0.20) (0.98)STDROAt�1 1.424*** 1.173***

(3.54) (2.94)STDRETt�1 1.878* 1.801

(1.65) (0.93)NONEQCOMPt 0.574*** 0.529***

(9.15) (10.91)Industry dummies Yes YesYear dummies Yes YesN 8084 8084Pseudo R2 0.0334 0.0375

This panel provides Tobit results from estimating Eq. (1). Standard errors are calculated based on Petersen’s (2009) doublecluster procedure to allow for inter-correlations of residuals across firms or across time. POST is an indicator variable set equalto one if the observation is from 2002–2006 and zero otherwise. All other variables are as defined in Table 2. Coefficients on theindustry and year dummies are suppressed for expositional convenience. Industry dummies are created based on the Fama–French 48 industry classifications and the year dummies are created for the years included in our sample period.





nance strength and excess equity grants is less negative in the post-Enron period, consistent withfirms making more efficient equity grants decisions in the post-Enron period.28

6. Concluding remarks

We examine how corporate governance affects CEO equity grant values. It has been argued thatequity incentives are a useful component of a firm’s governance structure but empirical evidence asto whether they actually align managers’ and shareholders’ interests is lacking. We consider thetwo predominant views on the relation between governance and equity grants: efficient contractingand managerial power. The efficient contracting view maintains that boards optimize their equity-granting decisions so there should be no systematic relation between equity grants and governancestrength. In contrast, the managerial power view contends that managers in firms with weak gover-nance exercise power over boards’ compensation decisions to extract excessive compensation so thereshould be a negative relation between governance strength and abnormal equity grants.

Our evidence, covering 8048 firm-year observations from 1719 firms over the years 1998–2006,suggests that weaker governance as proxied by lower takeover vulnerability and weaker board andshareholder monitoring is associated with larger abnormal equity grants for CEOs after controllingfor economic determinants of equity grants. Although our principal finding of a negative associationbetween ESOs and corporate governance is consistent with the managerial power view, it is also con-sistent with two alternative explanations: (1) corporate governance variables proxy for unmodeled(omitted) economic factors affecting ESO use; or (2) incentive compensation substitutes for gover-nance mechanisms to mitigate agency problems. We perform additional tests to determine the valid-ity of these alternative explanations for our findings. Our tests suggest that neither one appears to bedescriptively valid.

We extend prior research examining the association between CEO compensation and corporategovernance. Although Core et al. (1999) showed that poor governance contributes to excessive cashand total compensation, empirical evidence on how governance relates to equity grants is limited.We contribute to the literature by examining alternative explanations for the negative association be-tween governance strength and abnormal equity grants. We show that incentive compensation doesnot appear to substitute for weak governance nor to be an effective governance mechanism. We add toresearch examining effects of corporate governance on financial report quality (Klein, 2002, Eng andMak, 2003, Byard et al., 2006; Kanagaretnam et al., 2007; Kelton and Yang, 2007) by providing evi-dence suggesting that weak corporate governance along with opaque ESO accounting prior to SFAS123R enabled CEOs to abuse ESO grants for their own benefit.

Acknowledgments

We thank Ashiq Ali, Eli Bartov, Dan Collins, Christi Gleason, Paul Healy, Tom Lys, Maria Nondorf,Shiva Rajgopal, Doug Skinner, Abbie Smith, Franco Wong, and workshop participants at the 2007American Accounting Association Annual Meetings, 2007 Harvard University IMO conference, 2007University of Okalahoma Accounting Research Conference, Georgia State University, National TaiwanUniversity, University of Iowa, and the University of Texas at Dallas for helpful comments.

28 Because it is difficult to interpret the economic significance of GOVSCORE_POST (GOVFACTOR_POST), an interaction between acontinuous variable and an indicator variable in a nonlinear Tobit model, we compute the marginal effect of GOVSCORE(GOVFACTOR) on EQUITY separately for the pre- and post-Enron periods. The marginal effect of GOVSCORE (GOVFACTOR) in thepre-Enron period was �0.444 (�0.571), indicating the CEO receives 44.4% (57.1%) more equity awards when GOVSCORE(GOVFACTOR) decreases from the 75th to the 25th percentile holding all other variables at their mean values. In the post-Enronperiod, the marginal effect of GOVSCORE (GOVFACTOR) decreased to �0.297 (�0.466), representing a 33.1% (18.3%) decrease in theeffect of governance strength on excess equity grants.


References

Barber, B., Lyon, J., 1996. Detecting long-run abnormal operating performance: the empirical power and specification of teststatistics. Journal of Financial Economics 41 (2), 359–399.

Bartov, E., Mohanram, P., 2004. Private information, earnings manipulations, and executive stock-option exercises. AccountingReview 79 (4), 889–920.

Bebchuk, L., Fried, J., 2003. Executive compensation as an agency problem. Journal of Economic Perspectives 17 (3), 71–92.Bebchuk, L., Cohen, A., Ferrell, A., 2008. What matters in corporate governance? Review of Financial Studies 22 (2), 783–827.Biggs, J., 2002. Testimony on stock options before the US Senate Finance Committee. <http://www.tiaa-crefinstitute.org/

research/speeches/041802.html> .Black, F., Scholes, M., 1973. The pricing of options and corporate liabilities. Journal of Political Economy 81 (3), 637–654.Bodie, Z., Kaplan, R., Merton, R., 2003. For the last time: stock options are an expense. Harvard Business Review 81 (3), 63–71.Brown, L., Caylor, M., 2006. Corporate governance and firm valuation. Journal of Accounting and Public Policy 25 (4), 409–434.Brown, L., Caylor, M., 2009. Corporate governance and firm operating performance. Review of Quantitative Finance and

Accounting 32 (2), 129–144.Byard, D., Li, Y., Weintrop, J., 2006. Corporate governance and the quality of financial analysts’ information. Journal of

Accounting and Public Policy 25 (5), 609–625.Cameron, A., Gelbach, J., Miller, D., 2008. Bootstrap-based improvements for inference with clustered errors. Review of

Economics and Statistics 90 (3), 414–427.Carhart, M., 1997. On persistence in mutual fund performance. Journal of Finance 52 (1), 57–82.Coles, J., Daniel, N., Naveen, L., 2006. Managerial incentives and risk-taking. Journal of Financial Economics 79 (2), 431–468.Coombes, A., 2005. Excess compensation: institutional investors say US execs are overpaid. MarketWatch (December 13, 2005).Core, J., Guay, W., 1999. The use of equity grants to manage optimal equity incentive levels. Journal of Accounting and

Economics 28 (2), 151–184.Core, J., Holthausen, R., Larcker, D., 1999. Corporate governance, chief executive officer compensation, and firm performance.

Journal of Financial Economics 51 (3), 371–406.Core, J., Guay, W., Larcker, D., 2003. Executive equity compensation and incentives: a survey. Economic Policy Review 9 (1),

191–212.Core, J., Guay, W., Rusticus, T., 2006. Does weak governance cause weak stock returns? An examination of firm operating

performance and investors’ expectations. Journal of Finance 61 (2), 655–681.Dechow, P., Hutton, A., Sloan, R., 1996. Economic consequences of accounting for stock-based compensation. Journal of

Accounting Research 34 (Suppl.), 1–20.Demsetz, H., Lehn, K., 1985. The structure of corporate ownership: causes and consequences. Journal of Political Economy 93 (6),

1155–1177.Dittmar, A., Mahrt-Smith, J., 2007. Corporate governance and the value of cash holdings. Journal of Financial Economics 83 (3),

599–634.Eng, L., Mak, Y., 2003. Corporate governance and voluntary disclosure. Journal of Accounting and Public Policy 22 (4), 325–345.Fama, E., French, K., 1997. Industry cost of equity. Journal of Financial Economics 43 (2), 153–193.Fama, E., Jensen, M., 1983. Separation of ownership and control. Journal of Law and Economics 26 (2), 301–325.Financial Accounting Standards Board, 2004. Statement of Financial Accounting Standards No. 123R: Share-Based Payment.

FASB, Norwalk, CT.Gillan, S., 2001. Has pay for performance gone awry? Views from a corporate governance forum. Research Dialogue 68 (July), 1–

14.Gillan, S., Hartzell, J., Starks, L., 2006. Tradeoffs in corporate governance: evidence from board structures and charter provisions.

Working paper, Texas Tech University and University of Texas at Austin.Gompers, P., Ishii, J., Metrick, A., 2003. Corporate governance and equity prices. Quarterly Journal of Economics 118 (1), 107–

155.Guay, W., Kothari, S., Sloan, R., 2003. Accounting for employee stock options. American Economic Review 93 (2), 405–409.Hall, B., Liebman, J., 1998. Are CEOs really paid like bureaucrats? Quarterly Journal of Economics 103 (3), 653–691.Hall, J., Murphy, K., 2002. Stock options for undiversified executives. Journal of Accounting and Economics 33 (1), 3–42.Himmelberg, C., Hubbard, R., Palia, D., 1999. Understanding the determinants of managerial ownership and the link between

ownership and performance. Journal of Financial Economics 53 (3), 353–384.Ittner, C., Lambert, R., Larcker, D., 2003. The structure and performance consequences of equity grants to employees of new

economy firms. Journal of Accounting and Economics 34 (1–3), 89–127.Kanagaretnam, K., Lobo, G., Whalen, D., 2007. Does good corporate governance reduce information asymmetry around quarterly

earnings announcements? Journal of Accounting and Public Policy 26 (4), 497–522.Kelton, A., Yang, Y., 2007. The impact of corporate governance on internet financial reporting. Journal of Accounting and Public

Policy 27 (1), 62–87.Klein, A., 2002. Audit committee, board of director characteristics, and earnings management. Journal of Accounting and

Economics 33 (3), 375–400.Lambert, R., Larcker, D., 1987. Executive compensation effects of large corporate acquisitions. Journal of Accounting and Public

Policy 6 (4), 231–243.Lambert, R., Larcker, D., Verrecchia, R., 1991. Portfolio considerations in valuing executive compensation. Journal of Accounting

Research 29 (1), 129–149.Larcker, D., Rusticus, T., 2010. On the use of instrumental variables in accounting research. Journal of Accounting and Economics

49 (3), 186–205.Merton, R., 1973. Theory of rational option pricing. Bell Journal of Economics and Management Science 4, 141–183.Meulbroek, L., 2001. The efficiency of equity-linked compensation: understanding the full cost of awarding executive stock

options. Financial Management 30 (2), 5–44.

http://www.tiaa-crefinstitute.org/research/speeches/041802.html

http://www.tiaa-crefinstitute.org/research/speeches/041802.html


Murphy, K., 1999. Executive compensation. In: Orley, A., David, C. (Eds.), Handbook of Labor Economics. North-Holland,Amsterdam, pp. 2485–2563.

Oyer, P., Schaefer, S., 2005. Why do some firms give stock options to all employees? An empirical examination of alternativetheories. Journal of Financial Economics 76 (1), 99–133.

Petersen, M., 2009. Estimating standard errors in finance panel data sets: comparing approaches. Review of Financial Studies 22(1), 435–480.

Shleifer, A., Vishny, R., 1997. A survey of corporate governance. Journal of Finance 52 (2), 737–783.Smith, C., Watts, R., 1992. The investment opportunity set and corporate financing, dividend, and financing policies. Journal of

Financial Economics 32 (3), 262–292.Sundaramurthy, C., Mahoney, J.M., Mahoney, J.T., 1997. Board structure, antitakeover provisions, and stockholder wealth.

Strategic Management Journal 18 (3), 231–245.

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