Executive Compensation: Facts. - NYUpages.stern.nyu.edu/~gclement/Papers/facts.pdf · Compensation was singled out as one of the most ... the latest survey by the United for a Fair

Executive Compensation Factslowast

Gian Luca Clementidagger Thomas CooleyDagger

This version July 22 2010[Link to the latest version]

Abstract

In this paper we describe the important features of executive compensation in the USfrom 1993 to 2008 Differently from most of the literature we follow Antle and Smith(1985) in defining compensation as the yearndashonndashyear change in the portion of the exec-utiversquos wealth tied to the firm Notable facts are that the compensation distribution ishighly skewed each year a sizeable fraction of chief executives lose money the use ofsecurity grants has increased over time the income accruing to CEOs from the sale ofstock increased regardless of the measure we adopt compensation responds strongly toinnovations in shareholder wealth measured as dollar changes in compensation incentiveshave strengthened over time measured as percentage changes in wealth they have notchanged in any appreciable way

Key words CEO PayndashPerformance Sensitivity Stock Options

JEL Codes G34 J33 M52

lowastWe are very grateful to Dave Backus Heski BarndashIsaac Kose John Laura Veldkamp Larry White andDavid Yermack as well seminar attendants at the Minneapolis Fed NYU the 2008 Midwest Macro Conferencein Philadelphia SED Meeting in Cambridge and EEA conference in Milan for their comments and suggestionsAll remaining errors are our own responsibility

daggerDepartment of Economics Stern School of Business New York University and RCEA Emailclemnyuedu Web httppagessternnyuedu˜gclement

DaggerDepartment of Economics Stern School of Business New York University and NBER Emailtcooleysternnyuedu Web httppagessternnyuedu˜tcooley

1 Introduction

In 2008 the precipitous drop in real estate prices put financial companiesrsquo riskndashtaking in the

spotlight It is not at all surprising that in such a climate executive compensation came under

increased attention Compensation was singled out as one of the most important and deeply

flawed elements of the incentive system that induced firms to accumulate enormous amounts of

risk on their balance sheets In Clementi Cooley Richardson and Walter (2009) we describe

many of the flawed practices in financial firms But executive compensation more broadly has

long been a sensitive issue and financial crises have a tendency to focus increased attention on

it In 1929 for example much attention was focused on the compensation of Eugene Grace the

president of Bethlehem Steel who faced a huge uproar when it was revealed that he received

a base salary of $12000 and a bonus of more than $16 million That amounts to $150000

salary in 2009 dollars with a nearly $20 million bonus

Throughout the 1930rsquos there was much hue and cry about executive compensation and

many proposals to cap it The most important case in that era involved George Washington

Hill the President of American Tobacco and other senior executives In that case several exec-

utives of American Tobacco Co had received bonuses that plaintiffs claimed were excessive

The bonuses were paid under a plan that had been approved by shareholders in the form of

a byndashlaw adopted in 1912 The byndashlaw provided that if the net profits of American Tobacco

exceeded about $82 million in any year the president of the company would receive payment

of 25 percent of such excess and each of five vicendashpresidents would receive 15 percent an ag-

gregate of 10 percent of the annual net profit exceeding $82 million The case eventually went

to the Supreme Court and in Rogers v Hill (1933) the Court ruled that overall compensation

must be reasonable in proportion to the value of the services rendered The dissenting opinion

of Judge Swan indicates the applicable rule rdquoIf a bonus payment has no relation to the value

of services for which it is given it is in reality a gift in part and the majority stockholders

have no power to give away corporate property against the protest of the minorityrdquo

In the past two decades there has been much discussion of executive compensation many

public examples of lavish pay but no real consensus on the extent of the problem if indeed there

is one In part this is because there is a lack of clarity about what the facts are In this paper

we take a careful look at executive compensation in the United States in the period 1993ndash

2008 We investigate the crossndashsectional and timendashseries variation in compensation paying

particular attention to the role played by the various components of executives packages and

to the implications for incentive provision

Our study differs from most other contributions to the literature in that our main measure

of compensation is the yearndashonndashyear change in the portion of executiversquos wealth that is tied

to the firm In other words we define compensation as the sum of salary bonus the yearndashonndash

year change in the value of stock and option holdings the net revenue from the sale of stock

and exercise of options and the value of newly awarded securities We prefer this definition

because it aligns most closely with the concept that emerges from the analysis of multindashperiod

theoretical models of the relationship between managers and shareholders

The AFLndashCIO the federation of 56 US and international labor unions1 recently stated

that ldquoThe chief executive officers of large US companies averaged $108 million in total

compensation in 2006 more than 364 times the pay of the average US worker according to

the latest survey by the United for a Fair Economyrdquo We find that the average compensation

of CEOs of publicly traded US companies was actually much higher than $108 million but the

average is wildly misleading because the compensation distribution is always highly skewed

The median compensation in 2006 was only $476 million

CEOs of large companies tend to sit on large stock and option portfolios Accordingly

rapid rises in their companiesrsquo stock prices lead to handsome financial rewards But it also

means that they suffer significant wealth losses when those prices fall Every year a substantial

fraction of CEOs actually lose money

Contrary to the claim of Bebchuk and Fried (2004) salary and bonus payments account for

a very small fraction of compensation and their crossndashsectional dispersion is rather limited

In light of this finding the policy debate on capping these two components of compensation

appears to be misplaced

Looking at the characteristics of compensation over time we find that the dollar value of

stock and option grants increased at a brisk pace for most of the 1990s At the same time

however the median value of stock holdings declined This is consistent with the finding that

during those years executives relinquished much of the stock they acquired through their

compensation packages

We estimate the sensitivity of pay to firm performance using three of the many indicators

proposed in the literature No matter the measure considered we find that executivesrsquo financial

rewards respond strongly to innovations in shareholder wealth However whether incentives

strengthened over the sample period depends on the choice of sensitivity measure

When using the methodology due to Aggarwal and Samwick (1999) we estimate that a

$1000 increase in shareholder wealth is associated with a $34 rise in CEOs wealth for the

lowestndashvolatility companies This is higher than the $28 estimated by Aggarwal and Samwick

(1999) for the 1993ndash1996 period According to this measure incentives have strengthened

1httpwwwaflcioorgcorporatewatchpaywatchpayindexcfm

However the elasticity of CEO wealth with respect to shareholder wealth is shown to be

timendashinvariant at about 115 In light of the increase in shareholder wealth that occurred

after 1996 these findings are not inconsistent

The remainder of the paper is organized as follows In Section 2 we describe the data

and define our measurement conventions In Section 3 we document the extent of separation

between ownership and control in the population of US public corporations Section 4 char-

acterizes the most salient features of the distribution of compensation across executives In

Section 5 we study how compensation varies with firm size and across sectors Section 6 is

dedicated to the analysis of the time variation The estimates of payndashperformance sensitivity

are illustrated in Section 7 Finally Section 8 concludes

2 Data and Measurement

We draw our data from the EXECUCOMP database maintained by Standard amp Poorrsquos

EXECUCOMP gathers data from 1992 to the present on the compensation of up to nine

executives of all US companies whose stocks are traded on an organized exchange The source

for the database are companiesrsquo filings with the Securities and Exchange Commission The

information about executivesrsquo securities holdings and their compensation packages is contained

in the DEF14A forms (or Schedule 14A) filed annually by corporations pursuant Section 14(a)

of the Securities Exchange Act of 1934

We confine our attention to the years 1992 through 2008 the last (fiscal) year for which

we have comprehensive information Our sample consists of information on 36279 executives

employed by 3042 companies for a total of 33896 companyndashexecutive matches and 166762

executivendashyear observations

21 Measuring Compensation

It is well known that executives are compensated in a wide variety of ways Murphy (1999)

provides a detailed description of the main components of compensation packages Among

them are salary bonus stock and options grants severance payments 401K contributions

and lifendashinsurance premia

Because of the complexity that characterizes compensation packages defining summary

measures of compensation is far from straightforward In this paper we adopt a definition

suggested by Antle and Smith (1985) and later adopted in studies of payndashperformance sen-

sitivity by Hall and Liebman (1998) and Aggarwal and Samwick (1999) We will refer to it

as Total Yearly Compensation Roughly speaking it is defined as the yearndashonndashyear change in

Executiversquos Wealth which in turn consists of the expected discounted value of the portion of

executiversquos wealth whose value is tied to his or her companyrsquos performance In the words of

Antle and Smith (1985) Total Yearly Compensation is meant to measure ldquothe annual change

in executiversquos total wealth associated with employmentrdquo

Our ideal measure of wealth consists of the value of stock and options in the executiversquos

portfolio plus the expected discounted value of all future handouts in form of cash and secu-

rities Operationally we define it as the market value of securities holdings plus the expected

discounted value of future salaries and bonuses Total yearly compensation consists of the

sum of salary bonus the yearndashonndashyear change in the value of stock and option holdings the

net revenue from the sale of stock and exercise of options and the value of newly awarded

securities

Throughout the paper we will also consider the partition of compensation into Current

and Deferred Current compensation includes all claims that can be instantaneously traded for

consumption goods Deferred compensation the residual part consists of the current expected

value of all claims over future consumption This partition is of particular interest because

the theoretical analysis of executive compensation in dynamic moral hazard models implies

restrictions on the relative role the two portions play in incentive provision

Operationally we define Current compensation as the sum of salary bonus dividends and

net revenues from trade in stock Deferred compensation is the sum of the yearly changes in

the value of stock and options in portfolio retirement benefits expected future salaries and

other deferred payments

The precise definition of all variables can be found in Appendix A For our purposes the

EXECUCOMP database presents two major shortcomings To start with EXECUCOMP only

includes the value of options that are in-the-money This greatly complicates the estimation of

the yearndashonndashyear change in the value of option holdings Furthermore the database provides

no information on purchases and sales of stock by the executives This makes it hard to come

up with an accurate measure of the net revenue from trade in stock

We consider two alternative definitions of option holdings The first which is used by

Aggarwal and Samwick (1999) is simply the sum of two EXECUCOMP variables namely the

value of the un-exercisable inndashthendashmoney options and that of the exercisable inndashthendashmoney

options both computed at the money at the end of the fiscal year2 Since it does not take into

account the value of outndashofndashthe money options this definition introduces an upwards bias in

the absolute value of the fluctuations in options values The alternative definition estimates

the value of out-of-the-money options by means of a simple algorithm due to Himmelberg and

2In the latest version of the database the two variables are labeled OPT UNEX UNEX UNEXER EST VALand OPT UNEX UNEX EXER EST VAL respectively In the previous version their names were INMOUNand INMONEX

Hubbard (2000) The details of the procedure are illustrated in Appendix A13

By net revenue from trade in stock we mean the difference between the revenues from sales

of stock and the expense incurred in acquiring shares (either by purchase or option exercise)

Executives may (i) purchase and sell common stock on the open market (ii) purchase common

stock directly from the company at prices much lower than the marketrsquos (iv) inherit stock4 (iii)

donate stock5 Unfortunately we do not have information on either the prices or quantities of

these transactions Furthermore we do not know whether the shares obtained by exercising

options are kept or sold For this reason we resort to a simple algorithm that allows us to

estimate the net revenue from trade using other variables provided by EXECUCOMP The

algorithm is described in Appendix A2

22 The Theoretical Underpinnings of the Total Yearly Compensation Measure

Our choice of compensation measure is not arbitrary Rather it is motivated by the recent

literature on multindashperiod models of executive compensation inspired by the work of Spear

and Srivastava (1987) In models in this class ndash see for example Wang (1997) and Clementi

Cooley and Wang (2006) ndash the reward an executive receives from her association with the

company in a given period depends on the change in her wealth that takes place during that

period because of such association

Think of riskndashneutral shareholders that make a takendashitndashorndashleavendashit offer to a CEO with

outside value v For simplicity assume that the companyrsquos cash flows are given by a random

variable zt distributed on the positive orthant according to the timendashinvariant distribution

F (zt|at) The notation at ge 0 indicates the effort exerted by the executive The greater

the effort the larger the probability of more favorable outcomes The CEOrsquos utility function

u(wt at) is increasing in the wage wt and decreasing in effort at

The contract offered to the CEO consists of a sequence of wages

wt(ht)T

t=1 together

with effort recommendations

at(htminus1)

t=1 The notation reflects the fact that the contract

provisions at time t depend on ht = zsts=1 the history of revenue realizations up to that

time If we let F(ht|alowastt(htminus1)) denote the probability distribution over the histories of length

t along the path of play generated by the strategy alowastt(htminus1) =

as(hsminus1)

s=1 the contract

offered by the shareholders will solve the following optimization problem

maxwt(ht)alowast

t(htminus1)T

βtint

[zt minus wt(ht)]dF(ht|alowast

t(htminus1))

3For the sake of brevity this draft does not include the results obtained with this second method They areavailable from the authors upon request

4For example in 1999 Carnival CEO Mickey Arison inherited stock from his father5Mr Warren Buffett the larger shareholder and CEO Berkshire Hathaway made several donations in stock

subject to

βtint

u[wt(ht) alowast(htminus1)]dF(ht|alowast

t(htminus1)) ge

βtint

u[wt(ht) a(htminus1)]dF(ht|at(htminus1))

βtint

t(htminus1)) ge v (2)

Constraint (1) is the incentive compatibility constraint It requires that the CEO is better

off by following the recommended sequence of actions rather than any other Condition (2)

simply requires that the value of the contract to the CEO is larger than her outside value

Under mild regularity conditions6 the problem can be written in recursive form The only

state variable is the continuation value for the CEO vt That is the expected discounted

utility offered by the contract to the CEO from time t onwards The shareholdersrsquo problem

becomes that of choosing a level of effort a contingent wage schedule wt(zt) and continuation

values vt+1(zt) At all times t ge 1 their value Vt(vt) solves the following problem

Vt(vt) = maxwt(zt)alowastt vt+1(zt)

[zt minus wt(zt) + βtVt+1(vt+1(zt))]dF (zt|alowastt )

subject to

u[wt(zt) alowastt )] + βtvt+1(zt)

dF (zt|alowastt ) geTsum

βtint

u[wt(zt) at)] + βtvt+1(zt)

dF (zt|at)

dF (zt|alowastt ) (4)

Constraint (3) is the temporary incentive compatibility constraint Condition (4) is known

in the literature as promisendashkeeping constraint It simply imposes that promised utility vt must

be delivered either by means of current or future utility

Under standard functional form assumptions the contract is such that working harder

increases the CEOrsquos expected lifendashtime utility by affecting all of components of her wealth

wages and deferred payments Our Total Yearly Compensation measure is designed to proxy

for this effect

6For T lt infin the transversality condition would be Vt+1 = 0 For T = infin the recursive representation isvalid only under boundedness conditions

In several other studies among which Frydman and Saks (2006) and Bebchuk and Grin-

stein (2005) compensation is defined as the sum of salary bonuses longndashterm incentive plans

and grantndashdate value of securities awards7 In the remainder of the paper we will refer to

this as the classical definition of compensation Unfortunately the classical definition provides

little information about the change in wealth that accrues to an executive from his or her rela-

tionship with the company in a given year In fact as will be clear below the change in wealth

is mostly the result of factors ndash such as the change in the value of stock and option holdings

and the net revenues from trade in stock ndash that are not accounted for in this measure

According to the dynamicndashcontract approach we have briefly illustrated current and fu-

ture compensation policies depend on past compensation This is consistent with observed

corporate policies8 Since most securities awards are restricted the design of current and

future compensation packages must depend on past compensation Everything else equal

different stock and options holdings will call for different contractual provisions both in the

present and in the future It follows that looking at these provisions in isolation as dictated

by the classical measure would be misleading That is it would give an inaccurate picture

of the change in current and future consumption possibilities that derive from employment at

the company

3 Separation Between Ownership and Control

In the last thirty years or so thousands of pages have been written on executive compensation

both in the academic and popular press Among the reasons for this intense interest is that

executive compensation is thought of as the most powerful tool to align the goals of owners and

managers of modern corporations That these goals are misaligned because of the separation

between ownership and control is taken to be one of the defining characteristics of public

corporations

Since the appearance of the influential work by Berle and Means (1932) the standard

characterization conceives of executives and CEOs in particular as professionals hired by

shareholders to run their companies This view takes the separation between ownership and

control intended in its most extreme version as a fact However even to the distracted

observer it should be obvious that in reality there is an enormous variation in the degree of

separation Figure 1 substantiates this claim by showing the cumulative distribution of CEO

7See page 9 of Frydman and Saks (2006) and page 284 of Bebchuk and Grinstein (2005) for their respectivedefinitions

8According to 2006 Oracle Corporationrsquos DEF14A the factors considered by that company in determiningthe size of option grants include ldquothe intrinsic value of outstanding unndashvested equity awards and the degree to

which such values supports our retention goals for each executiverdquo

equity stakes among US public corporations in 2006

0 1 2 3 4 5 10 15 20

Stake in Percentage Points

Cumulative Distribution in 2006CEO Equity Stake

Figure 1 CEO Equity Stake in 2006

Our data shows that in 2006 about 25 of CEOs held more than 1 of their companiesrsquo

common stock and about 10 held more than 59 CEOs with relatively low stock holding

fit the Berle and Meansrsquo stereotype in the sense that they are likely to have been hired only

to manage the company This is the case for example of Mr John W Thompson who

spent most of his career at IBM before being hired as Symantecrsquos CEO in 1999 In 2006 Mr

Thompson held about 016 of the companyrsquos common stock The CEOs with the largest

equity stakes are far from the Berle and Meansrsquo ideal and are likely to be either the companiesrsquo

founders or to have family ties to them This is the case of Micky Arison CEO of Carnival

Corporation ndash the worldrsquos largest cruise operator ndash and son of Ted Arison the companyrsquos

founder In 2006 Mr Arison held about 238 of Carnivalrsquos common stock

As will be clear below stocks have a primary role in incentive provision In the case

of professional CEOs such as Symantecrsquos Mr Thompson the observed equity stake is the

result of the companyrsquos compensation policy Therefore the incentives that result can be

used to assess the disciplining role of boards of directors This is decidedly not the case for

company founders and for other executives such as Mr Arison whose large equity holdings

have nothing to do with the companyrsquos compensation policy These individuals although

disciplined by the requirements of public companies essentially have absolute control over the

source of their pecuniary incentives Compensation committees can have very little impact

on them

In light of this simple argument in the remainder of this paper we will report certain

9Since we donrsquot account for stock held by the executiversquos family members This will introduce a downwardbias

statistics for Professional CEOs only arbitrarily defined as those that hold less than 1 of

their companiesrsquo common stock Our goal is discern the differences if any in the way in which

professional CEOs are compensated and in the incentives they face

4 The Distribution of Compensation across Executives

Figure 2 depicts the crossndashsectional distributions of wealth and total compensation for the

population of CEOs in 2006 The striking feature of both histograms is the right skewness

Median CEO pay in 2006 was only 476 million dollars The exorbitant average pay of 434

million was mostly the result of skyndashhigh compensation at the very top of the distribution

Table 8 (refer to the rows labeled rdquoGrossrdquo) reports a series of statistics of the compensation

distribution for all sample years The skewness index of 2813 10 for 2006 was not an outlier

Skewness has been a feature of the CEOsrsquo total compensation distribution throughout the

sample period Notice however that the distribution is not always rightndashskewed In the three

(fiscal) years following the stock market peak of January 2000 the mean CEO compensation

was largely negative while the median values were positive The reason is that as illustrated

in Section 5 CEOs of large companies have relatively high stock and option holdings In turn

this implies that their compensation is particularly sensitive to stock market fluctuations of

either sign

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Quantiles of Compensation Distribution

Millions of 2005 dollarsCEO wealth in 2006

minus50

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Millions of 2005 dollarsTotal CEO Yearly Compensation in 2006

Figure 2 CEO Compensation in 2006

This leads us to another salient feature of the data Contrary to what has become common

wisdom CEOs do lose money Sometimes they lose a lot In 2006 with the SampP 500 index

rising by more than 9 our measure of compensation was negative for as many as 264 CEOs

10By skewness index we mean the ratio of third moment about to the mean to the standard deviation

As expected the big losers were those at the helm of companies whose stock dropped the most

in value during the year Among them Yahoo (ndash33) Amazon (ndash20) and Ebay (ndash30)

Conversely the winners were the chief executives of the companies whose shareholders gained

the most such as McndashGraw Hill (+30) Marriott (+38) and Comcast (+65) Table

8 shows that a sizeable fraction of CEOs lost money in every year In 2002 that fraction

exceeded 40

If executives hedge systematic risk actual median gains and losses will be much smaller

(in absolute value) than our figures suggest For this reason we also report statistics for

Total Yearly Compensation net of the return executives would have earned by investing their

wealth in the market portfolio See the rows labeled ldquoNet of Marketrdquo in Table 8

The Net definition yields the actual compensation under the assumption that executives

hedge systematic risk by selling short the market portfolio or by building a similar position

via trade on derivatives11

Hedging systematic risk has a large effect on the tails of the compensation distribution It

moderates losses in bad years for the stock market and moderates gains in good years As a

result median net compensation tends to be smaller than gross compensation in a good year

for the stock market and larger in bad years Table 8 shows that median net compensation

ranged between ndash$10000 (in 1998) and $591 million (in 2003) The main message we draw

from these data however is the same as above In every single year both dispersion and

skewness were remarkably large

Since the SEC does not require executives to disclose trades in securities not issued by their

companies we do not know whether executives indeed hedge market risk or not However

Garvey and Milbourn (2003) provides indirect evidence that this may be the case12

Refer once more to Table 8 For every year the third row illustrates the results that obtain

with the classical definition of compensation The picture it conveys is rather different In

2006 mean and median CEO pay were $517 and $308 million respectively Interestingly

the dispersion across executives is much lower than it is with our measure According to

the classical definition the mean compensation of the top 10 in the distribution was about

20 million dollars in 2006 (against our estimate of $42115 million) The mean compensation

among the bottom 10 in 2002 was about $450000 against a $33667 million loss that obtains

according to our definition

11An example of such a position is a zerondashcost collar which involves selling an outndashofndashthendashmoney call optionand buying an outndashofndashthendashmoney put option

12Garvey and Milbourn (2003) argue that if companies recognize that they should use relative performanceevaluation (RPE) only for those executives that are unable to diversify systematic risk estimates of payndashperformance sensitivity should depend on market volatility only in the case of younger and poorer executiveswhose chances of diversification are slimmer This is exactly what they found in their study

Table 9 provides detailed information about the partition of total yearly compensation

between Current and Deferred A clear fact better illustrated in Figure 3 in the case of 2006

1 2 3 4 5 6 7 8 9 10

Deciles of Wealth Distribution

Millions of 2005 dollarsCEO Wealth in 2006

Wealth (a) Stock (b)Options (c)

minus20

1 2 3 4 5 6 7 8 9 10

Deciles of Compensation Distribution

Total (a) Deferred (b)Current (c)

Figure 3 Split of Compensation in the CrossndashSection

is the crossndashsectional dispersion in the deferred component Both big winners and big losers

have large stock and option portfolios To appreciate this consider that the median equity

stake among CEOs in the top and bottom deciles of the compensation distribution are 115

and 077 respectively against a 024 median for the remainder

The crossndashsectional dispersion of Current compensation is much lower In 2006 the ratio

of median absolute deviation to the median is 071 for Current compensation against 562 for

Deferred compensation Another interesting finding illustrated in Figure 4 is that most of the

variation in Current compensation comes from the proceeds from trade in stock In fact the

median absolute deviation for salary and bonus was only $270000 (the median was $829000)

In light of this finding the policy debate on the possibility of capping salary andor bonuses

Bebchuk and Fried (2004) argued that ldquo much executive compensation comes in forms

other than equity such as salary and bonusrdquo and that ldquoThe evidence indicates that cash

compensation ndash including bonuses ndash has been at best weakly correlated with firmsrsquo industry

adjusted performancerdquo13 The evidence presented in Section 7 is definitely in agreement with

the latter statement But our data do not confirm the first part of this claim For most CEOs

salary and bonus account for a rather small portion of total compensation See Figures 3 and

Table 10 illustrates compensation across professional CEOs The distribution of Current

compensation is remarkably similar to that for the entire population of CEOs At the same

13See page 7 lines 1 through 4

1 2 3 4 5 6 7 8 9 10

Millions of 2005 dollarsCurrent Compensation in 2006 minus All CEOs

Current (a) From Trade in Stock (b)Salary + Bonus (c)

Figure 4 Current Compensation in the CrossndashSection

time both the median and the median absolute deviation of total compensation are smaller in

every single year The main differences however are in the means This should not come as

a surprise We defined nonndashprofessional CEOs as those who own large equity stakes in their

companies In turn this implies that their total compensation will be particularly high in

good times and particularly low in bad times This immediately leads us to wonder whether

the incentives faced by professional CEOs are as strong as previous analysis led us to believe

We will address this question in Section 7

Finally Table 11 illustrates the distribution of compensation across all nonndashCEO exec-

utives in our data-set Both median and median absolute deviation are considerably lower

This is the result of lower levels of compensation in all categories and in particular in those

that are more sensitive to fluctuations in stock prices At the margin notice that all measures

of compensation are particularly high in the top and bottom 5 of executives because most

company founders with no executive roles fall in these bins

5 Compensation Variation in The CrossndashSection of Firms

In this section we are interested in documenting how the various measures of compensation

vary with firm size and across sectors

Beginning with Kostiuk (1990) many have investigated the relationship between firm

size and executive compensation Kostiuk himself Murphy (1999) Bebchuk and Grinstein

(2005) and Gabaix and Landier (2008) among others found evidence of a positive correlation

between the two variables Even in our dataset the classical definition of compensation is

unconditionally positively correlated with proxies for size such as sales and book value of

assets The question is whether a similar pattern holds for total compensation

1 2 3 4 5 6 7 8 9 10

Deciles of Book Value Distribution

Total (a) Stock (b)Options (c)

minus5

minus3

minus101

1 2 3 4 5 6 7 8 9 10

Millions of 2005 dollarsYearly Compensation in 2002 minus All CEOs

Total (a) Deferred (b)Current (c) Salary (d)

Figure 5 CEO Compensation and Firm Size

Figure 5 depicts median CEO Wealth and Total Yearly Compensation for each decile in

the distribution of book value of assets in 2002 We have chosen 2002 because in that year

mean compensation was largely negative

The left panel tells us that even in a year of relatively low stock prices CEOs of larger

firms had substantially larger wealth tied to the firms they led In particular they had larger

stock and option holdings This is why as suggested by the right panel the same CEOs

suffered substantial losses

Current compensation is also monotonically increasing in the size of the firm Executivesrsquo

salaries tend to be higher in larger firms but the crossndashsectional variation is minimal Most

of the variation in Current compensation is accounted for by differences in the net revenues

from trade in stock

The patterns just described do not change substantially when we adopt sales rather than

book value as a measure of size

Figure 6 illustrates the variation of CEO wealth and compensation across sectors Inter-

estingly CEOs in the Mining and Finance Insurance and Real Estate (FIRE) sectors stand

out as holding larger wealth Table 13 shows that for the FIRE sector this has been the case

throughout the sample period It is not clear whether this is due to the fact that CEOs in the

FIRE sector manage larger firms In fact firms in the FIRE sectors tend to be larger when

size is proxied by book value of assets but not when we use either employment or sales

lesale

Servic

Retail

Servic

lesale

Millions of 2005 dollarsTotal Compensation in 2006

Figure 6 CEO Compensation across Sectors

6 Compensation Over Time

Echoing the popular and business press a number of recent papers have argued that the

level of executive compensation has increased dramatically over time For example Frydman

and Saks (2006) state that ldquoThe compensation of top executives increased by 68 per year

from 1980 to 2003rdquo Bebchuk and Grinstein (2005) find that ldquoAmong SampP 500 firms average

CEO compensation climbed from $37 million in 1993 to $91 million in 2003 (an increase of

146)rdquo

When considering the classical definition of compensation our study delivers a similar

message Once again given the skewness of the distribution we will look at median values

rather than means The left panel of Figure 7 shows that the median compensation has

doubled over the 16 samplendashyears On average this amounts to a growth rate which is about

5 times that of average nonndashfarm hourly wages Interestingly median compensation has

also increased in years in which most companies had rather poor financial results This is

the evidence invoked by those observers that argue that CEOs never lose even when their

companiesrsquo results are negative

When we turn to our definition of compensation the message is different The right panel

of Figure 7 illustrates the dynamics of real median compensation both gross and net of the

return on the market portfolio Compensation has been quite variable over the sample years

As expected the gross measure tracked aggregate stock market returns Median gross

compensation was at its minimum of about 410000 dollars in 2002 when the SampP500 index

lost about 30 of its value In that year 656 out of the 1457 continuing CEOs lost money It

reached its maximum of 887 millions in 2003 when the SampP500 gained about 21 What is

clear is that there is no discernible trend In fact in 2005 median gross compensation turned

out to be about the same as ten years earlier

Our net definition displays less timendashseries variation than gross compensation Once again

however we cannot discern any particular trend

93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08

Salary CurrentAvg NonminusFarm Hourly Wages Classical Definition

Medians minus 1993=100Growth in Compensation minus Selected Components

93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08

Millions of 2005 dollarsCEO Compensation

Gross Definition (a) Net Definition (b)Classical Definition (c)

Figure 7 CEO Compensation over Time

Letrsquos now turn to the growth pattern of the various components of compensation The

left panel of Figure 7 shows that the Current portion has increased over most of the sample

period at a mean pace much faster than average nonndashfarm hourly wages The same graph

suggests that the growth in salaries accounts for a small portion of the increase Indeed the

salary of the median CEO has increased less than average wages in the nonndashfarm sector

It turns out that most of the postndash1999 increase in Current compensation is accounted for

by net proceeds from trade in stock ie by options exercise and stock sale This piece of

evidence is consistent with other findings

The right panel in Figure 8 shows that the median dollar value of securities grants has

increased over pretty much the whole sample period However (see left panel) median stock

holdings actually declined from 1998 to 2003 (and picked up later on)

Letrsquos assemble the various pieces of the puzzle At the end of 1990s we had increasing

stock prices and security grants but declines in the median value of both stock and option

holdings It appears that companies stepped up the grant of securities perhaps with the

purpose of sharpening incentives but it looks like executives sold shares whenever they could

Our confidence in this rationalization of the facts is enhanced by the evidence provided

by Ofek and Yermack (2000) that (i) executives tend to immediately relinquish the shares

obtained via optionsrsquo exercise and that (ii) those among them that have higher equity stakes

sell stock whenever they are granted new restricted shares or new options

The right panel in Figure 8 points to a further change in compensation practices The

relative importance of stock and options has changed Since 2001 stock grants have become

more prominent as companies scaled down the volume of option awards

Hall and Murphy (2003) argued that the increase in option grants over the 1995ndash2001

period was prompted by revisions to the tax code enacted in 1994 According to the new rules

companies were allowed to deduct compensation expenses in excess of 1 million dollars only

when the compensation was performancendashbased It would be interesting to understand what

prompted companies to change their compensation practices after 2001 from using options to

stock grants

93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08

Stock OptionsSampP 500 CEO Wealth

1993=100Growth in Median CEO Wealth minus Selected Components

93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08

Millions of 2005 dollarsSecurity Grants minus All CEOs

Stock + Options (a) Options (b)

Figure 8 Dynamics of Wealth and Securities Grants

Changes in sectoral composition donrsquot appear to be among the causes of this phenomenon

In fact the dynamics just described applies to both sectors whose relative importance shrank

during the sample period ndash Paper and Allied Products (SIC 26) and Depository Institutions

(60) ndash and those whose importance grew over time such as Electronic Equipment (SIC 36)

and Business Services (73)14

7 The Sensitivity of Compensation

Another important aspect of executive compensation is its sensitivity to changes in shareholder

wealth Scholars have assessed it in a variety of ways Here we will consider three of them

14The twondashdigit SIC sectors that shrank the most in term of relative importance also include Printing andPublishing (27) Chemicals and Allied Products (28) Petroleum Refining (29) Leather and Leather Products(30) Primary Metal Industries (33) Transportation Equipment (37) Communications (48) Electric Gas andSanitary Services (49) Food Stores (54) and Depository Institutions (60) Among the sectors that gained themost are Photographic Medical and Optical Goods (38) Insurance Carriers (63) and Holding And OtherInvestment Offices (67)

The first which we identify as JMndashAS measures the dollar increase in executiversquos wealth per

$1000 increase in shareholder wealth The other two are the semindashelasticity and the elasticity

of executiversquos wealth with respect to shareholder wealth respectively

The three definitions reflect different hypotheses about how shareholders and executives

value risky prospects For example the first two definitions are valid only under the assump-

tion that the prospect of losing a given dollar amount has the same impact on executives no

matter their wealth The third is based on the postulate that what matters to executives is

the percentage change in wealth

71 The JMndashAS Sensitivity Measure

The acronym JMndashAS refers to the contributions by Jensen and Murphy (1990) and Aggarwal

and Samwick (1999) Having found that in their sample CEO wealth increased by only $325

for 1000 dollar increase in shareholder wealth Jensen and Murphy (1990) claimed that CEOs

were paid like bureaucrats Or in other words that they faced rather weak incentives

Schaefer (1998) and Hall and Liebman (1998) showed that Jensen and Murphy (1990)rsquos

estimate was low because their sample was biased towards large firms Stock market capital-

ization fluctuates more for large firms than it does for small firms This implies that the risk

imposed on a CEO by a given payndashperformance sensitivity tends to be larger the larger the

This motivates us to follow the lead of Aggarwal and Samwick (1999) and compute esti-

mates of sensitivity at different levels of volatility

minus150

minus100

minus50

minus15 minus10 minus5 0 5 10 15

Net Shareholder Gain (Billions)

2005 dollarsTotal Yearly Compensation and Shareholder Gain

Figure 9 Compensation and Shareholder Gain

The scatter plot in Figure 9 shows the association of changes in shareholder and executiversquos

wealth over the sample period While the unconditional correlation between the two variables

is positive there are many instances in which CEOs end up making money at the time in

which their companiesrsquo market values drop by billions of dollars These are the cases in the

upper left quadrant and they are the ones that attract a lot of media attention

As an example consider the case of Douglas Ivester the CEO of CocandashCola Co from

October 1997 to February 2000 During the 1999 fiscal year CocandashColarsquos shareholders lost

about 14 or about 225 billion dollars According to our calculations15 in the same year

Mr Ivester made about 74 million dollars As a result of the fall in the companyrsquos stock

price the value of his stock holding dropped This explains why his Deferred compensation

was negative (about ndash6065 millions) However his Current compensation was roughly $135

million 91 of which came from the sale of companyrsquos stock16

Following Aggarwal and Samwick (1999) we estimate the following equation

wijt = γ0 + γ1∆MKT CAPjt + γ2∆MKT CAPjt times F (σj) + γ3F (σj) + λt + εit (5)

where i j t index the executive the firm and time respectively The letter w denotes com-

pensation MKT CAPjt is total market capitalization ∆ is the onendashperiod lag operator and

λt is a year dummy whose purpose is to control for aggregate shocks Finally σjt denotes

the standard deviation in shareholdersrsquo dollar return (ie the change in market capital-

ization) F (middot) is the cumulative distribution of standard deviations The interaction term

∆MKT CAPjt times F (σj) was introduced because the impact on compensation of a 1 000 dol-

lar change in shareholder wealth is expected to be larger the smaller the average change in

capitalization The measure of sensitivity for company j in year t will be γ1 + γ2 times F (σjt)

Our estimates are reported in Table 1

Table 1 Median Regression Estimates of PayndashPerformance Sensitivities

All Executives All CEOs Professional CEOs

Dependent Variables Total Current Deferred Total Current Deferred Total Current Deferred

Shareholder Gain 6511 0825 4844 34220 2344 28386 21100 1607 17572( 0019) ( 0009) ( 0014) ( 0178) ( 0057) ( 0150) ( 0128) ( 0062) ( 0092)

Sh Gain times Variance distrib -6073 -0817 -4456 -32124 -2273 -26619 -19584 -1527 -16263( 0019) ( 0009) ( 0014) ( 0180) ( 0058) ( 0152) ( 0130) ( 0063) ( 0093)

Variance distrib 1704421 1270835 26392 3101647 3813709 -1941001 3770358 3510885 -865444( 17794) ( 8148) ( 13154) ( 164353) ( 52793) ( 139121) ( 120371) ( 58435) ( 86368)

Number of observations 97288 97460 97288 15923 15942 15923 10660 10667 10660Pseudo R

2 0047 0022 0031 0073 0025 0060 0219 0072 0174

Note Standard errors in parenthesis

In the case of CEOs a 1 000 dollar increase in capitalization induces a $3422 dollar

increase in compensation for the firm with the lowest volatility and a $210 dollar increase

15We reiterate that we do not have information about the actual stock sales by the executive Our calculationsare simply approximations based on the information included in the Schedule 14A

16The remainder of Mr Ivesterrsquos Current compensation in 1999 consisted of 15 millions in salary and inabout 20 millions in both the EXECUCOMP variables ALLOTHPD and OTHANN

for the firm with the highest These estimates are substantially larger than those obtained

by Aggarwal and Samwick (1999) for the period 1993ndash1996 When we restrict attention to

that period we find that the sensitivity of the lowestndashvariance firm is $2310 smaller than the

value reported by Aggarwal and Samwick (1999) ($27596)

What explains the increase in the JMndashAS measure Can it simply be the result of a

decrease in the volatility of shareholder value

Letrsquos think first of systematic volatility Garvey and Milbourn (2003) argue that if execu-

tives hedge systematic risk then the magnitude of the JMndashAS measure should only vary with

the idiosyncratic portion of the volatility of shareholderrsquos wealth They provide evidence that

this is indeed the case between 1992 and 1998 We followed their methodology and retrieved

measures of systematic and idiosyncratic volatility by means of simple CAPM regressions

Then we modified equation (5) by replacing the cdf of firm volatility with the distributions

of systematic and idiosyncratic volatility

Our results are reported in Table 14 The bottom line is that the relationship between

the sensitivity measure and volatility is accounted for almost completely by the idiosyncratic

portion of the latter This also means that changes in systematic volatility are not likely to

rationalize the increase in the sensitivity measure we have documented

How about changes in idiosyncratic risk Brandt Brav and Kumar (2009) found that

the idiosyncratic volatility of percent returns declined over the 1997ndash2007 period Obviously

this may matter There are at least two reasons however why this may not be the whole

story First of all the volatility of shareholder wealth also depends on market valuation which

has increased over the period in exam Furthermore Brandt Brav and Kumar (2009) argue

that most of the decline in volatility applied to a subset of stocks (low price stocks held

proportionally more by retail investors) This means that the decline in volatility may have a

sizeable impact on OLS estimates but should have a more limited effect on median estimates

The results reported so far suggest that the increase in performancendashbased compensation

may have led to stronger incentives The next two sections will tell us whether our other

measures of payndashperformance sensitivity yield a consistent picture

Table 2 Sensitivity at different levels of volatility ndash Professional CEOs

Total Current Deferred

Lowest Variance 21100 1607 17572Median Variance 11308 0843 944Largest Variance 1516 008 1309

Table 1 also reports our sensitivity estimates for all the executives and for the group of

professional CEOs respectively As expected the estimates for nonndashCEO executives are much

lower than reported above for CEOs The picture that emerges for professional CEOs is more

interesting On the one hand the sensitivity of Current compensation is about the same as for

the totality of CEOs On the other hand we find that the deferred component responds much

less to fluctuations in shareholder value This is obviously due to the lower stockholding

To determine whether the JMndashAS sensitivity varies across sectors we interact the variable

∆MKT CAPjt with sectorndashspecific dummies We estimate the equation

wijt = γ0 +sum

ηs times ψs times∆MKT CAPjt times+γ1∆MKT CAPjt times F (σj) + γ2F (σj) + εit

where ψs equals 1 if the firm j belongs to sector s and equals 0 otherwise The parameter γ1

is estimated to be -17937 The estimates of the parameters ηs ie the estimated sensitivities

for the lowest volatility firms are reported in Table 3 There appears to be limited variation

across sectors

Table 3 JMndashAS Sensitivity Coefficients by Sector ndash Professional CEOs

Mining Construction Manufacturing Transportation Wholesale Retail FIRE Services

20633 22612 19303 18422 19329 19711 20370 22076

Next we follow Core and Guay (2002) and Cichello (2005) among others and investigate

whether firm size perndashse has any effect on payndashperformance sensitivity To this end we

augment equation (5) by interacting the gain in shareholder wealth with the cdf of sales

(lagged one period) Our estimates are displayed in Table 15 As in the previous literature

we find that firm size does matter That is even conditioning on the standard deviation of

shareholdersrsquo dollar return the sensitivity is negatively associated to size Our findings do

not change qualitatively when we proxy size with book value of assets

We conclude this section by outlining a few basic issues that cast some doubts on the

reliability of these estimates and that have gone unremarked in earlier studies We start

by observing that the decision to use the cdf of the standard deviation rather than the

standard deviation itself is not innocuous It amounts to a concave transformation that

lowers the impact of relatively large observations and therefore increases the magnitude of the

estimates

A second issue has to do with the fit of the model With the exception of professional

CEOs the Pseudo R2 are very low suggesting that the linear model model accounts for a

rather small fraction of the total variance

Finally we notice that the correlation between ∆MKT CAPjt and its interaction with

F (σj) is always larger than 099 This is a even bigger issue when we include in the re-

gression the cdf of sales or other proxies for firm size In those scenarios the regressor

∆MKT CAPjttimesF (sizej) is also very highly correlated with the other two However in spite

of the multicollinearity the large size of the sample ensures that the estimates are stable and

appear to be statistically significant These are serious issues

72 The SemindashElasticity of Compensation with Respect to Shareholder

Wealth

The semindashelasticity measures the dollar increase in executiversquos wealth associated with a 1

increase in shareholder wealth We estimate the following equation

wijt = γ0 + γ1Sh Gainjt + γ2Sh Gainjt times F (σj) + γ3F (σj) + λt + εit (6)

where Sh Gainjt is the percentage gain of firm jrsquos shareholders over the fiscal year t Here

σjt represents the standard deviation of shareholder percent return F (middot) is the cdf of the

standard deviation

Our estimate of the expected dollar increase in total yearly compensation associated with

a 1 increase in shareholder return is γ1 + γ2 times F (σjt) The results are listed in Table 4

Table 4 Semindashelasticity Estimates

All CEOs Professional CEOs

Dependent Variables

Shareholder Return 394126 288944( 5725) ( 4760)

Sh Ret times Variance distrib -243433 -222095( 6973) ( 5888)

Variance distrib 353421 -605393( 256422) ( 216358)

No Observations 16356 10931Pseudo R

2 0044 0098

In the previous section we showed that our JMndashAS sensitivity estimates over the 1993ndash

2008 are larger than those obtained by Aggarwal and Samwick (1999) for the 1993ndash1996 period

Similarly the estimates reported in Table 4 are larger than those that we obtain by running

the same regression over data for the earlier period When we discard postndash1996 data the

coefficients of shareholder return are 225853 and 161535 for CEOs and professional CEOs

respectively

Hall and Liebman (1998) simply regressed dollar compensation on a constant and share-

holder return When we do the same (running robust regressions for CEOs as they did) we

obtain that a 1 increase in return was associated on average with a 130000 dollar increase

in compensation an estimate considerably larger than the 43000 dollars reported by Hall and

Liebman (1998) for the period 1980ndash1994

In order to determine whether the semindashelasticity varies across sectors we proceed to

interact the variable Sh Gainjt with sectorndashspecific dummies as we did in the previous

section The estimate of γ1 (the parameter that multiplies the interaction between percent

shareholder gain and variance) is minus199298 Table 5 reports our sensitivity estimates for

lowestndashvolatility firms

Table 5 Semindashelasticities by Sector ndash Professional CEOs

238720 247051 272515 214362 216364 289873 378507 309885

The FIRE sector stands out as the one displaying the highest sensitivity However digging

a little deeper reveals that the differences are not as large as Table 5 may lead one to believe

The point very simply is that the FIRE sector has a relatively large fraction of lowndashvolatility

To see that this is indeed the case consider Figure 10 which plots the frequency distribu-

tion of estimated sensitivities by sector That is the frequency distribution of γ1+γ2timesF (σjt)The middle panel on the top row shows that the FIRE sectors has a large portion of firms

with low volatility This is in part responsible for the large estimate we obtain for that sector

73 The Elasticity of Executiversquos Wealth With Respect to Shareholder

Wealth

The elasticity measures the percentage change in the portion of executiversquos wealth tied to

the firm which is associated with a 1 increase in market capitalization Since typically

nonndashCEOs executives have little wealth invested in the companies they work for we focus on

CEOs The equation we estimate is

CEO Gainijt = γ0 + γ1Sh Gainjt + λt + εit (7)

where CEO Gainijt denotes the percentage increase in the wealth of CEO i in year t Our

results are listed in Table 6

At the median the percentage increase in CEO wealth associated with a 1 increase in

shareholder wealth is 1143 for the totality of CEOs and 1236 for professional CEOs The

0 100 200 300

0 100 200 300 0 100 200 300

Construction FIRE Manufacturing

Mining Retail Services

Transportation Wholesale

Graphs by sector_label

Figure 10 Distribution of sensitivity estimates

Table 6 Elasticity Estimates

Dependent Variables

Constant -0029 -0071( 0018) ( 0025)

2 0305 0265

likely reason for this difference is that professional CEOs tend to have less wealth invested in

their companies

Unlike the JMndashAS measure and the semindashelasticity our estimates of the elasticity are

stable over the sample period For the sake of consistency letrsquos consider the 1993ndash96 period

The point estimate for professional CEOs was the same as in Table 6 For all CEOs the

elasticity was 117 slightly higher than documented for the whole sample period

In light of the increase in shareholder wealth that occurred after 1996 the time variation

of our elasticity estimates is not inconsistent with the results obtained for the other two

sensitivity measures According to Table 13 median CEO wealth was only $1362 million in

1993 and grew to $1769 million in 1996 In 2006 it had risen to 2530 million about 43

higher These figures lead to two possible rationalizations of the evidence

It may be the case that what matters to executives is really the percentage fluctuations in

their wealth If this is the case the increase in the JMndashAS and semindashelasticity measures were

needed in order to maintain incentives (ie the elasticity) intact in the face of an increase in

shareholder wealth

Alternatively it may be dollar changes that matter If so the increase in the dollar

volatility of compensation would reflect a strengthening of incentives The increase in CEO

wealth may have been necessary in order to retain CEOs in the faceof the higher risk they are

called to bear

When we investigate the crossndashsectoral variation in elasticity we find that it varies from

about 118 for Construction and FIRE to 141 for Transportation See Table 7

Table 7 Elasticities by Sector ndash Professional CEOs

1312 1180 1258 1407 1293 1179 1182 1250

8 Conclusion

The compensation of executives of public corporations is a compelling issue with strong polit-

ical overtones It is compelling because economic theory tells us a lot about how to structure

contracts to align the goals of professional managers with those of the shareholders And yet

there is a popular perception that this is not working and that incentives are weak Much of

this perception is based on a set of ldquofactsrdquo that are not completely reflective of reality

When one looks at compensation and its components in detail a number of features stand

out To start with the distribution of total compensation is highly skewed so averages are

highly misleading The dispersion of the crossndashsectional distribution is also remarkable In

every single year a large fraction of CEOs lose money Sometimes they lose a lot

Over the sample period the use of security grants has increased However this has not led

to a one for one increase in the portion of executivesrsquo wealth that is tied to their companies

In fact revenues from the sale of stock have also increased

No matter how we measure it the sensitivity of pay to performance is substantial However

whether the sensitivity has increased or not crucially depends on the proxy we use If one

believes that what matters to executives is changes in the level of compensation then the

conclusion is that incentives are now stronger then they used to be Instead if what really

matters is percentage changes in wealth then we are led to conclude that incentives did not

change over time

A Definitions of CEO Wealth and Total Yearly Compensation

As stated in the main body of the paper our definition of Executiversquos Wealth proxyes for the

dollar value of the executiversquos wealth that is tied to the firm at the beginning of the year It

is defined as the sum of the following elements

1 Market Value of Stock ndash SHROWNtimesPRCCF where SHROWN is the number of shares

owned at the end of the previous fiscal year and PRCCF is the share price at the same

2 Market Value of Stock Options ndash INMONEX+INMONUN where INMONEX is the

value of exercisable inndashthendashmoney options and INMONUN is the value of unexercisable

inndashthendashmoney options

3 Salary

4 Bonus

5 Total value of Restricted Stock Granted ndash RSTKGRNT

6 Total value of Stock Options Granted ndash SOPTVAL

7 Expected Discounted Value of Future Cash Payments ndash See Appendix A3 below

Total Yearly Compensation is our best estimate of the net increase in executiversquos wealth

that occurred during the fiscal year due to her relation with the company It is defined as

the sum of the following elements

1 Salary

2 Bonus

3 Net revenue from Trade in Stock ndash See Appendix A2 below

4 Dividends

5 LongndashTerm Incentive Payouts (including 401K contributions and life insurance premia)

ndash ALLOTHTOT-ALLOTHPD

6 A miscellanea of items among which payouts for cancellation of stock options payment

for unused vacation tax reimbursements and signing bonuses ndash ALLOTHPD+OTHANN

7 Yearly change in the Market Value of Stock

8 Yearly change in the Market Value of Options

The first six elements define what we call Current Compensation The sum of the remaining

ones identify Deferred Compensation

A1 The Value of Option Holdings according to the HH Algorithm

The analysis carried out in the main body of the paper posits that the change in the value of

the executiversquos option holdings equals the yearndashonndashyear change in the sum of un-exercisable

and inndashthendashmoney options both computed at the money at the end of the fiscal year This is

strategy followed by most other studies among which Aggarwal and Samwick (1999)

In this section we describe the algorithm devised by Himmelberg and Hubbard (2000)

in order to estimate the value of outndashofndashthendashmoney options in executivesrsquo portfolios The

algorithm makes use of the following EXECUCOMP variables17

bull UEXNUMEX = number or un-exercised but exercisable options held by the executive

at yearndashend both inndashthendashmoney and outndashofndashthendashmoney

bull UEXNUMUN = number of un-exercisable un-exercised options held by the executive at

yearndashend both inndashthendashmoney and outndashofndashthendashmoney

bull SOPTEXSH = number of options exercised by the executive during the fiscal year

bull SOPTGRN = total number of stock options awarded during the fiscal year

bull SOPTVAL = total value of options granted during the fiscal year

Under the assumption that none of the options awarded in a given year are immediately

exercisable the total value of options at yearndashend is the sum of (i) the value of newly granted

options (SOPTVAL) (ii) the value of unndashexercisable options (in number UEXNUMUNt minusSOPTGRNt) and (iii) the value of exercisable options (in number UEXNUMEXt)

Unfortunately we lack data on strike prices and vesting horizons of the options in portfolio

Therefore we assume that (i) a stock option grant vests gradually over four years at a constant

rate and (ii) SOPTEXSH includes the options that are let expire It follows that the laws of

17Some of the variables have changed labels in the latest version of the EXECUCOMP datasetUEXNUMEX is now called OPT UNEX EXER NUM UEXNUMUN is OPT UNEX UNEXER NUM OP-TION EXER NUM SOPTEXSH is OPTION EXER NUM SOPTGRNT is OPTION AWARDS NUM Fi-nally OPTION AWARDS RPT VALUE coincides with SOPTVAL However the latest version of the datasetuses OPTION AWARDS FV for those records that follow the new FASB123 reporting requirements

motion for the stocks of unndashexercisable and exercisable options are

UEXNUMUNt = (1minus 025)UEXNUMUNtminus1 + SOPTGRNTt

UEXNUMEXt = 025 times UEXNUMUNtminus1 + UEXNUMEXtminus1 minus SOPTEXSHt

Then we compute the value of the executiversquos option portfolio to be

opvtt = SOPTV ALt+UEXNUMEXt times bsvext + [075timesUEXNUMUNtminus1]times bsvunt (8)

The second addendum is the value of the exercisable options The third addendum is the value

of un-exercisable options inherited from the past18 We need to determine UEXNUMUNtminus1

Without it we would have to discard one more observation for every executivendashfirm match

The above conditions imply that

UEXNUMUNtminus1 = [UEXNUMUNt minus SOPTGRNTt]075

UEXNUMEXtminus1 = UEXNUMEXt + SOPTEXSHt minus 025 times UEXNUMUNtminus1

Notice that implicit in this formulation is the fact that UEXNUMEXt and UEXNUMUNtminus1

are computed at some average price in spite of the fact that they have different maturities

(and therefore different riskndashfree rates) and different strike prices

A11 Option Pricing

Options awarded to executives are American options on dividendndashpaying securities Since

there is no closed form pricing formula for them we will use the BlackndashScholes formula for

European options with continuous payment of the underlying

SeminusqTN(d1)minusXeminusrTN(d2)

d1 =log S

X+ (r minus q + 1

2σ2)T

σradicT

d2 = d1minus σradicT

It is left to specify how we determine the volatility of stock returns σ the dividend yield

q the riskndashfree rate r and the strike prices

bull EXECUCOMP provides data for σ in the variable BS V OLAT Since it has many

missing observation we computed our own measure based on CRSP data If pt is stock

price and dt is dividend the return is computed as log pt+dtadjtimesptminus1

The factor adj is equal

to CFACSHRtCFACSHRtminus1

18Notice that stock splits imply a slight modification to this formula See Appendix A11 below

bull EXECUCOMP provides data for q in the variable BS Y IELD Since it has many

missing observation we computed our own measure based on CRSP data That is

q = log(1 + dp)

bull Riskndashfree rates come from FRED at the St Louis Fed We use monthly data as I

follow the convention that we evaluate everything at the end of the fiscal year ndash not

the calendar year The series are GS3 and GS5 (Monthly returns on 3ndash and 5ndashyear

Treasuries ndash Constant Maturity)

bull Following Himmelberg and Hubbard (2000) once again we assume that

ndash out of the exercisable options (UEXNUMEXt) 10 are 1ndashyear old 30 are 2ndash

year old and 60 are 3ndashyear old This implies a strike price for the representative

option of 1ptminus1 + 3ptminus2 + 6ptminus3 The average maturity is assumed to be 3 years

ndash out of the un-exercisable options (UEXNUMUNtminus1) 60 are 1ndashyear old 30 are

2ndashyear old and 10 are 3ndashyear old This implies a strike price for the representative

One last caveat about stock splits When evaluating options we need to exercise some

care in order to make sure that strike prices and current prices are comparable We decide to

use the market price for current price and adjust the strike prices and the number of options

for splits

If the split is Z shares per each owned (in terms of EXECU variables Z = AJEXtminus1AJEXt)

we need to introduce only two minor alterations (i) the strike price is by Z and (ii) the equa-

tion (8) becomes

opvtt = BLKVALUEt+UEXNUMEXttimesbsvext+[075timesZtimesUEXNUMUNtminus1]timesbsvunt

A2 Computation of the net revenue from trade in stock

In this appendix we briefly describe the algorithm we employ to estimate the net revenue

from trade in stock We start by estimating the cost of exercising options ie V EXt We

postulate that all options exercised had the same strike price and were exercised when the

stock price was the maximum for the fiscal year This amounts to assuming that the following

relationship holds

SOPTEXER = [MAX PRICE minus STRIKE]times SOPTEXSH

where MAX PRICE is the maximum price for the fiscal year and the EXECUCOMP vari-

ables SOPTEXER and SOPTEXESH are the net value realized from exercising options and

the number of options exercised respectively19STRIKE is our unknown the estimated strike

price for the options exercised during the year20 Then CEXt the cost of exercising the op-

tions is given by

CEXt = SOPTEXSHt times STRIKEt

Next we estimate the net number of shares sold EXECUCOMP provides us with the hold-

ings of restricted stock RSTKHLD The restricted stock granted GRNTt can be estimated

by dividing the value of restricted stock granted by the price at the end of the fiscal year

GRNTt = RSTKGRNTPRCCF The law of motion for restricted stock allows us to recover

the number of vested shares V ESTt

RSTKHLDt = RSTKHLDtminus1 +GRNTt minus V ESTt

Abstracting from donations the law of motion for common stock SHROWNt is given by

SHROWNt = SHROWNtminus1 + Pt + V ESTt minus St + SOPTEXSHt

where Pt and St denote the stock purchased and sold respectively Our estimate of the net

number of shares sold is

St minus Pt = SHROWNtminus1 minus SHROWNt + V ESTt + SOPTEXSHt

If PtminusSt gt 0 we assume that the net revenue from stock trade is identically zero If StminusPt gt 0

we assume that the net revenue from stock trade is max[0 AV G PRICEtimes(StminusPt)minusCEXt]

That is we assume that the executive sold St minus Pt shares at the average market price for the

year but we impose that the net revenue is always nonndashnegative

A3 Expected Discounted Value of Future Cash Payments

Estimating the expected discounted value of future cash payments is extremely challenging

as it entails (i) projecting the evolution of expected cash payments over time (ii) estimating

the conditional expectation of years left in office and (iii) conjecture a discount rate

The evidence shown in the main body of the paper indicates that the sum of salaries

and bonuses has increased very little over our sample period For this reason we do not feel

particularly uncomfortable assuming that such payments are expected to stay constant at the

current value in real terms

19Notice that from the database it is not possible to tell whether the stock the executive acquires by exercisingoptions was sold or held on to

20According to the EXECUCOMP manual SOPTEXER is computed using the price of the day of theexercise This implies that our procedure overndashestimates the strike price Alternatively we may assume thatthe option was exercised when the stock price was equal to the average for the fiscal year

We find that in our sample the hazard rate varies very little for the first ten years in office

For this reason we make the drastic choice of assuming that the hazard rate is constant at its

sample mean of 01156 This figure implies that the expected number of years in charge after

the current one is constant and equal to about 7 and a half It is clear that this assumption

is going to bias our estimates upwards Finally we assume that the discount factor is 09615

the value commonly used in the macroeconomics literature

Let ρ be the survival rate (1 minus the hazard rate) and let β be the discount factor

Given our assumptions the expected discounted value of future cash payments is estimated

to equal payments in the current year multiplied by the following factor

(1minus ρ)

infinsum

βs =ρβ

1minus ρβ

B More Details on the Data

Effects of FAS 123 The Securities and Exchange Commission (SEC) has mandated all

public companies registrants that are not small business filers to apply Statement 123R by

the Financial Accounting Standards Board (FASB) as of the start of their first annual period

beginning after June 15 2005 FAS 123R prescribes that equity based compensation has to

be expensed and be reflected in the financial statements based on fair value of the awards

This policy change had a minor effect on the definitions of EXECUCOMPrsquos variables The

conventions adopted in order to bridge variables whose definitions have changed are available

from the authors upon request

Dating Convention All compensation data refers to the date of the annual shareholder

meeting which is held within three months of the end of the fiscal year We donrsquot have

information about meetingsrsquo dates Therefore we assume that the information refers to the

last day of the fiscal year

Market Return Our proxy for market return is the variable VWRETD from CRSP

the Center for Research in Security Prices at the Booth School of Business VWRETD is the

valuendashweighted return (with dividends) on an index drawn from the combined NYSEAMEX

and NASDAQ data

Volatility of Dollar Returns When computing the JMndashAS measure of payndashperformance

sensitivity in Section 7 we include among the regressors the (cdf of the ) volatility of dollar

return to shareholders We follow Aggarwal and Samwick (1999) (see page 76 of their paper)

and define volatility in a given month as the standard deviation of the monthly total returns

to shareholders over the 60 previous months

Idiosyncratic Volatility of Dollar Returns We compute idiosyncratic and systematic

volatility following the methodology described in Garvey and Milbourn (2003) For every

month we run simple CAPM regressions over the preceding 60 month Systematic volatility

is equal to the portion of return volatility that is explained by the model multiplied by market

capitalization Idiosyncratic volatility is the portion of return volatility not explained by the

model multiplied by market capitalization

Inflation Adjustment All dollarndashdenominated variables in EXECUCOMP are reported

in current prices We transformed them in constant (2005) prices dividing them by the chainndash

weighted CPI (All Urban Consumers US City Average All Items) from the Bureau of Labor

Statistics

Wages Average nonndashfarm hourly wages is the series produced by the Bureau of Labor

Statistics bearing the same name deflated by the CPI

References

Aggarwal R K and A A Samwick (1999) ldquoThe Other Side of the Trade-off The

Impact of Risk on Executive Compensationrdquo Journal of Political Economy 107(1) 65ndash105

Antle R and A Smith (1985) ldquoMeasuring Executive Compensation Methods and An

Applicationrdquo Journal of Accounting Research 23(1) 296ndash325

Bebchuk L and J Fried (2004) Pay Without Performance The Unfulfilled Promise of

Executive Compensation Harvard University Press Cambridge MA

Bebchuk L and Y Grinstein (2005) ldquoThe Growth of Executive Payrdquo Oxford Review

of Economic Policy 21(2) 283ndash303

Berle A A and G C Means (1932) The Modern Corporation and Private Property

MacMillan Publishing Corportation New York NY

Brandt M W A Brav and A Kumar (2009) ldquoThe Idiosyncratic Volatility Puzzle

Time Trend of Speculative Episodesrdquo Forthcoming on the Review of Financial Studies

Cichello M S (2005) ldquoThe Impact of Firm Size on PayndashPerformance Sensitivitiesrdquo

Journal of Corporate Finance 11 609ndash627

Clementi G L T Cooley M Richardson and I Walter (2009) ldquoRethinking

Compensation in Financial Firmsrdquo in Restoring Financial Stability ed by V Acharya and

M Richardson John Wiley and Sons

Clementi G L T Cooley and C Wang (2006) ldquoStock Grants as a Commitment

Devicerdquo Journal of Economic Dynamics and Control 30(11) 2191ndash2216

Core J and W Guay (2002) ldquoThe Other Side of the TradendashOff The Impact of Risk on

Executive Compensation ndash A Revised Commentrdquo The Wharton School

Frydman C and R Saks (2006) ldquoHistorical Trends in Executive Compensationrdquo MIT

Sloan School of Management MIT

Gabaix X and A Landier (2008) ldquoWhy Has CEO Pay Increased So Muchrdquo Forthcom-

ing Quarterly Journal of Economics

Garvey G and T Milbourn (2003) ldquoIncentive Compensation When Executives Can

Hedge the Market Evidence of Relative Performance Evaluation in the Cross Sectionrdquo

Journal of Finance 58(4) 1557ndash1581

Hall B and J Liebman (1998) ldquoAre CEOs Really Paid Like Bureaucratsrdquo Quarterly

Journal of Economics 102 653ndash691

Hall B and K Murphy (2003) ldquoThe Trouble with Stock Optionsrdquo Journal of Economic

Perspectives 17(3) 49ndash70

Himmelberg C P and G Hubbard (2000) ldquoIncentive Pay and the Market for CEOs

An Analysis of PayndashforndashPerformance Sensitivityrdquo Columbia GSB

Jensen M C and K J Murphy (1990) ldquoPerformance Pay and TopndashManagement In-

centivesrdquo Journal of Political Economy 98(2) 225264

Kostiuk P F (1990) ldquoFirm Size and Executive Compensationrdquo Journal of Human Re-

sources 25 90ndash105

Murphy K (1999) ldquoExecutive Compensationrdquo in Handbook of Labor Economics ed by

O Ashenfelter and D Card pp 2485ndash2563 Elsevier Science

Ofek E and D Yermack (2000) ldquoTaking stock EquityndashBased Compensation and the

Evolution of Managerial Ownershiprdquo Journal of Finance 55(3) 1367ndash1384

Schaefer S (1998) ldquoThe Dependence of PayndashPerformance Sensitivity on The Size of The

Firmrdquo Review of Economics and Statistics 80 436ndash443

Spear S and S Srivastava (1987) ldquoOn Repeated Moral Hazard with Discountingrdquo

Review of Economic Studies 54 599ndash617

Wang C (1997) ldquoIncentives CEO Compensation and Shareholder Wealth in a Dynamic

Agency Modelrdquo Journal of Economic Theory 76 72ndash105

Table 8 Distribution of Total Compensation ndash Millions of 2005 dollars ndash All CEOs

Year Obs Mean Median MAD Skewness Means by Decile

1 2 3 4 5 6 7 8 9 10

1993 882 Gross 1922 295 292 1261 -5107 -010 084 145 226 381 584 974 1990 19992Net of Mkt 1357 228 286 1100 -6925 -120 055 110 179 304 499 843 1716 16907Classical 255 160 082 522 042 072 094 119 144 181 226 291 408 976

1994 1339 Gross 604 110 232 1782 -4295 -385 -056 038 083 149 246 423 875 9004Net of Mkt 517 104 235 1933 -4427 -416 -071 033 077 139 235 408 820 8394Classical 267 157 087 469 038 064 085 113 141 178 225 305 439 1090

1995 1402 Gross 3094 393 376 2094 -1389 -002 094 179 308 499 789 1362 2535 26604Net of Mkt 1452 187 366 1980 -4762 -488 -036 064 134 253 445 800 1534 16644Classical 279 163 088 850 039 068 090 114 145 184 233 318 468 1133

1996 1441 Gross 2420 363 396 1973 -2462 -056 075 156 282 458 770 1222 2361 21412Net of Mkt 784 170 411 -092 -7912 -511 -064 056 126 240 458 803 1546 13114Classical 370 189 110 1663 041 072 101 130 170 216 282 391 592 1714

1997 1433 Gross 5367 680 648 2919 -4062 021 150 308 532 849 1341 2232 4116 48288Net of Mkt 2405 306 577 2616 -10946 -572 -052 091 217 412 717 1278 2404 30565Classical 450 227 138 871 045 081 115 152 197 255 333 463 691 2173

1998 1439 Gross 7002 178 645 2340 -6468 -738 -222 002 113 269 594 1314 3515 72055Net of Mkt 3405 -001 736 2337 -13299 -1882 -858 -360 -080 048 190 608 1992 47853Classical 528 230 141 2833 043 084 118 158 204 264 356 495 756 2810

1999 1494 Gross 9789 168 680 2503 -17752 -879 -231 012 109 265 657 1475 3873 110625Net of Mkt 6591 049 799 2367 -28457 -1888 -706 -208 001 105 337 963 2827 93346Classical 585 251 158 858 043 089 123 165 219 290 400 579 908 3042

2000 1437 Gross -1196 421 829 -2949 -52005 -791 -057 109 294 588 1086 2084 4559 32080Net of Mkt 236 492 874 -2342 -44308 -564 002 149 352 678 1285 2351 5065 37361Classical 746 276 184 1619 042 086 127 171 230 316 439 611 1040 4408

2001 1403 Gross -105 223 629 1447 -33401 -1209 -203 056 160 316 603 1111 2120 29402Net of Mkt 2316 368 604 2039 -21682 -540 014 146 280 502 853 1500 2900 39230Classical 693 277 193 1297 042 085 125 173 238 331 475 697 1150 3626

2002 1457 Gross -2122 041 474 -2484 -33667 -1613 -556 -165 -004 088 225 457 945 12998Net of Mkt 1202 243 474 -1103 -17194 -481 -053 071 179 324 578 1034 2009 25582Classical 525 280 183 552 045 089 130 179 243 325 441 609 942 2252

2003 1560 Gross 3521 887 734 1300 -2816 139 298 495 734 1081 1574 2485 4467 26756Net of Mkt 1317 591 548 -1464 -9478 010 147 284 477 730 1095 1743 3199 14964Classical 477 261 162 386 045 089 129 175 228 301 394 559 846 2007

2008 1318 Gross -11038 -040 461 -3572 -112532 -2479 -968 -419 -133 012 100 236 519 4660Net of Mkt 5871 299 361 3578 -6874 -283 027 117 230 365 560 911 1736 62265Classical 514 319 199 661 058 109 153 209 277 366 474 617 886 1991

Note The heading Gross denotes Total Yearly CompensationNet of Mkt denotes Total Yearly Compensation net of the return on the market portfolioMAD stands for Median Absolute DeviationSkewness is the ratio of third moment about to the mean to the standard deviation

Table 9 Distribution of Yearly Compensation ndash Millions of 2005 dollars ndash All CEOs

Year Obs Mean Median MAD Skewness Means by Decile of Total Compensation

1 2 3 4 5 6 7 8 9 10

1993 882 Total 1922 295 292 1261 -5107 -010 084 145 226 381 584 974 1990 19992Current 499 146 077 1718 1058 167 098 146 161 247 257 482 597 927Deferred 1355 086 253 1265 -6165 -177 -014 -002 066 134 328 492 1393 17528

1994 1339 Total 604 110 232 1782 -4295 -385 -056 038 083 149 246 423 875 9004Current 693 147 083 3056 3406 451 174 115 148 164 241 366 402 1183Deferred -124 -013 226 -166 -7701 -836 -230 -077 -066 -015 005 057 473 7152

1995 1402 Total 3094 393 376 2094 -1389 -002 094 179 308 499 789 1362 2535 26604Current 568 153 087 1977 359 145 090 150 177 219 289 439 968 2124Deferred 2505 187 331 2122 -1747 -147 004 029 131 281 500 923 1567 23550

1997 1433 Total 5367 680 648 2919 -4062 021 150 308 532 849 1341 2232 4116 48288Current 1191 198 125 1913 2262 098 150 193 319 382 490 679 882 4477Deferred 4112 342 526 2880 -6323 -077 -000 115 212 467 851 1552 3233 41172

1998 1439 Total 7002 178 645 2340 -6468 -738 -222 002 113 269 594 1314 3515 72055Current 1447 183 118 2109 789 408 239 136 143 385 323 587 1007 6536Deferred 5453 -000 598 2285 -7257 -1146 -461 -134 -030 -116 271 727 2508 60516

1999 1494 Total 9789 168 680 2503 -17752 -879 -231 012 109 265 657 1475 3873 110625Current 2771 182 117 3890 3295 317 276 176 195 216 483 568 1347 13407Deferred 6835 002 670 2910 -21047 -1197 -507 -164 -086 050 174 907 2526 87893

2000 1437 Total -1196 421 829 -2949 -52005 -791 -057 109 294 588 1086 2084 4559 32080Current 1210 198 133 2049 2758 390 184 158 169 343 498 790 1345 3500Deferred -2489 135 795 -2994 -54764 -1182 -241 -049 124 245 587 1294 3214 25745

2001 1403 Total -105 223 629 1447 -33401 -1209 -203 056 160 316 603 1111 2120 29402Current 1023 195 128 1541 2608 634 430 144 221 231 407 538 977 2636Deferred -1204 025 590 1414 -36009 -1843 -633 -087 -060 085 196 573 1142 24587

2002 1457 Total -2122 041 474 -2484 -33667 -1613 -556 -165 -004 088 225 457 945 12998Current 707 190 124 1156 2275 556 402 322 198 134 279 442 705 1318Deferred -2870 -162 464 -2447 -35942 -2170 -958 -487 -202 -046 -054 015 240 10808

2003 1560 Total 3521 887 734 1300 -2816 139 298 495 734 1081 1574 2485 4467 26756Current 1190 200 129 1710 2138 114 161 235 269 371 477 712 1140 4672Deferred 2285 538 539 696 -4954 026 137 260 464 709 1097 1773 3327 20012

2004 1559 Total 2832 656 649 1367 -3722 -076 136 286 506 800 1188 1836 3258 24220Current 1273 246 159 1383 831 245 228 237 325 363 624 907 1402 5402Deferred 1502 234 545 1417 -4553 -322 -092 049 182 436 564 929 1856 16035

2005 1572 Total 1825 386 529 1134 -4852 -321 013 133 288 485 797 1403 2669 17661Current 2216 249 171 3832 2561 439 147 222 323 496 480 658 1164 11663Deferred -475 045 491 -3271 -7413 -760 -135 -088 -035 -011 317 745 1505 1127

2008 1318 Total -11038 -040 461 -3572 -112532 -2479 -968 -419 -133 012 100 236 519 4660Current 6399 238 171 3690 57459 1227 783 467 249 197 270 370 774 3646Deferred -17685 -409 476 -3606 -169991 -3705 -1751 -886 -382 -185 -170 -134 -255 -382

Note MAD stands for Median Absolute DeviationSkewness is the ratio of third moment about to the mean to the standard deviation

Table 10 Distribution of Yearly Compensation ndash Millions of 2005 dollars ndash Professional CEOs

1 2 3 4 5 6 7 8 9 10

1994 833 Total 233 123 113 -009 -690 -025 036 065 099 147 212 329 552 1612Current 250 136 069 641 323 133 119 102 110 165 195 279 407 509Deferred -023 -001 097 -176 -1013 -158 -084 -037 -011 -018 016 050 145 881

1995 890 Total 839 311 251 951 -191 059 106 170 253 385 578 949 1654 4427Current 282 138 071 1002 169 069 095 126 155 197 202 364 533 693Deferred 549 135 190 1039 -360 -010 011 044 098 188 376 585 1122 3437

1998 925 Total 1196 161 366 684 -2253 -329 -057 044 118 225 438 886 2025 10909Current 554 174 100 1910 433 317 173 110 145 211 488 443 633 1652Deferred 610 003 332 403 -2686 -645 -230 -066 -027 014 -050 443 1392 7981

2000 919 Total 1166 332 523 342 -7786 -330 022 121 264 465 795 1419 2821 13934Current 1004 188 115 2478 1199 311 106 130 168 289 416 523 1077 3604Deferred 101 097 493 -438 -8986 -642 -083 -009 095 176 379 896 1743 7464

2001 931 Total 1896 192 400 3007 -7744 -584 -074 075 151 257 448 754 1347 24362Current 613 189 114 2003 1279 535 209 131 175 282 300 467 759 1287Deferred 1236 022 378 2998 -9023 -1119 -282 -056 -023 -025 149 287 587 21915

2002 1007 Total -2130 053 313 -3157 -23693 -861 -280 -073 022 091 201 367 687 2103Current 431 186 115 1807 797 424 293 225 168 148 237 338 507 831Deferred -2585 -115 296 -3157 -24491 -1286 -573 -298 -147 -057 -036 030 181 684

2003 1090 Total 1643 689 532 965 -171 137 266 408 590 822 1155 1697 2703 8826Current 643 198 123 1983 213 107 149 187 277 339 394 567 777 2477Deferred 977 401 385 -515 -384 030 118 221 313 483 761 1130 1926 5171

2004 1092 Total 1223 496 481 1588 -989 -015 135 253 397 653 953 1430 2266 7169Current 743 236 148 2915 535 209 181 213 263 326 500 673 1091 2398Deferred 447 197 408 -147 -1524 -224 -046 040 134 326 454 757 1175 3383

2005 1125 Total 870 362 386 774 -2252 -118 056 150 278 439 654 1064 1876 6566Current 835 238 157 3250 882 263 168 237 332 554 442 572 951 2875Deferred 003 042 353 -2459 -3134 -381 -111 -088 -054 -115 212 492 925 2278

2007 1063 Total 758 225 395 645 -2868 -340 -035 062 158 316 526 923 1843 7018Current 791 194 136 1950 922 692 255 160 264 384 405 603 1049 2252Deferred -072 -015 391 028 -3790 -1033 -290 -098 -107 -068 121 320 795 3435

2008 979 Total -340 006 364 1220 -6186 -1443 -628 -241 -049 039 114 237 489 4276Current 1115 230 163 2113 1839 722 549 380 243 170 303 382 795 4381Deferred -1499 -345 373 -1299 -8025 -2164 -1177 -621 -293 -131 -189 -145 -306 -1997

Note Professional CEOs are those whose equity stake is less than 1MAD stands for Median Absolute DeviationSkewness is the ratio of third moment about to the mean to the standard deviation

Table 11 Distribution of Yearly Compensation ndash Millions of 2005 dollars ndash NonndashCEOs

1 2 3 4 5 6 7 8 9 10

1994 7024 Total 121 054 041 1233 -584 002 022 033 047 063 088 133 228 1179Current 103 046 023 1500 239 052 036 040 052 070 082 107 151 128Deferred 003 001 032 883 -824 -050 -014 -007 -005 -007 006 026 077 825

1996 7391 Total 388 093 073 3794 -500 022 036 054 078 116 178 282 513 3100Current 141 051 025 5992 223 032 042 054 070 081 108 127 189 232Deferred 225 022 053 3407 -723 -010 -005 -000 008 034 070 155 324 2400

1998 7671 Total 743 072 089 4459 -771 -030 021 037 058 093 157 284 619 6967Current 262 053 027 4719 225 087 037 047 066 080 113 154 279 565Deferred 416 005 082 3896 -997 -117 -015 -010 -008 012 044 130 340 4781

1999 7886 Total 839 074 085 6116 -1255 -025 024 039 060 094 157 297 697 8305Current 267 056 029 5584 394 090 038 050 069 095 111 180 287 596Deferred 524 004 079 5729 -1649 -115 -014 -011 -009 -001 046 117 410 6474

2000 7329 Total 352 104 108 101 -4512 -009 031 052 083 133 225 408 830 6280Current 483 061 033 6599 2720 073 044 059 077 109 225 213 408 598Deferred -238 015 102 -3748 -7232 -083 -014 -007 006 024 -000 196 422 4300

2001 7201 Total -062 082 091 -5653 -4235 -054 025 044 067 102 157 255 451 2563Current 282 058 030 8882 1412 119 049 054 067 092 116 164 263 331Deferred -409 007 087 -7078 -5647 -173 -024 -011 000 010 041 091 188 1435

2002 7767 Total -195 053 069 -7991 -4109 -093 007 028 044 065 097 152 264 1592Current 241 059 030 6588 992 123 055 042 054 094 138 170 188 331Deferred -481 000 056 -8010 -5101 -216 -048 -014 -011 -029 -041 -017 076 585

2003 8091 Total 592 172 129 -1540 -450 041 067 100 145 204 291 434 761 4324Current 233 062 033 6657 410 041 057 070 096 111 132 182 280 449Deferred 320 068 073 -5569 -860 -001 010 030 049 093 159 252 481 2991

2004 8118 Total 599 140 115 5830 -602 022 048 078 117 171 252 382 658 4872Current 367 075 041 7874 1036 057 054 075 095 120 151 206 362 903Deferred 199 034 087 -1314 -1638 -035 -006 004 023 052 101 176 296 3019

2005 7019 Total 369 126 112 -2652 -1938 006 040 068 104 153 231 362 610 4063Current 404 082 047 6599 1290 074 064 088 124 542 169 221 406 769Deferred -061 016 091 -3526 -3228 -068 -024 -020 -020 -389 062 141 204 2732

2006 5744 Total 590 123 110 2374 -1369 006 039 065 099 153 233 370 659 5647Current 444 057 030 6314 989 074 060 110 118 142 193 262 438 703Deferred -056 012 101 -2664 -2358 -068 -021 -045 -019 011 039 108 222 1569

2007 5877 Total 485 077 099 4904 -1344 -053 016 037 062 098 158 268 506 5110Current 295 065 038 2694 588 144 069 066 096 112 165 230 363 538Deferred 137 -002 094 4837 -1932 -197 -053 -029 -034 -015 -006 038 143 3452

2008 5125 Total -393 036 084 -3465 -6738 -247 -064 002 027 045 070 111 198 2664Current 315 069 040 2315 941 219 146 094 053 084 104 155 268 568Deferred -760 -049 078 -3428 -7678 -466 -210 -093 -026 -039 -034 -044 -070 1055

Table 12 Compensation Across Sectors ndash Millions of 2005 dollars ndash All CEOs

Year All Mining Manuf Transp Whole Retail FIRE Services

1993 Mean 1922 597 846 3049 214 -487 1822 5631Median 295 302 309 179 252 215 303 632Obs 882 40 407 142 23 59 125 72

1994 Mean 604 002 532 -346 -276 -633 326 2822Median 110 034 175 059 075 010 151 254Obs 1339 58 594 202 40 109 186 126

1995 Mean 3094 467 2106 860 642 1280 3957 8719Median 393 247 440 178 231 122 973 700Obs 1402 62 627 208 43 120 181 135

1996 Mean 2420 905 1639 915 604 2088 3201 8275Median 363 597 349 143 161 391 1002 339Obs 1441 65 639 204 43 130 188 146

1997 Mean 5367 1211 2581 4313 886 3950 6357 17253Median 680 167 587 311 353 908 2064 765Obs 1433 63 652 186 44 131 176 156

1998 Mean 7002 -980 4221 4334 839 5841 4035 19861Median 178 -210 111 196 129 536 422 730Obs 1439 58 652 164 45 129 173 194

1999 Mean 9789 1165 3617 6804 803 2572 2465 50890Median 168 342 270 103 114 026 -094 428Obs 1494 61 663 164 50 135 180 214

2000 Mean -1196 2665 1184 -1648 1609 -4950 6588 -18738Median 421 769 253 340 240 381 1578 213Obs 1437 62 625 158 48 133 183 199

2001 Mean -105 -1469 -632 267 1807 856 7631 -7529Median 223 019 194 158 479 639 318 284Obs 1403 54 614 149 47 127 180 207

2002 Mean -2122 527 -871 -1112 -497 045 -11243 157Median 041 244 030 086 011 027 167 -084Obs 1457 57 639 149 46 118 201 220

2003 Mean 3521 1360 2777 3301 972 6424 4172 2322Median 887 541 785 681 395 1289 1629 924Obs 1560 66 661 155 46 130 231 242

2004 Mean 2832 2081 2395 3562 1532 1017 3361 3001Median 656 786 535 493 824 681 1103 588Obs 1559 64 662 158 47 136 225 236

2005 Mean 1825 4205 1107 1459 1066 1698 3189 2332Median 386 1539 256 420 525 518 457 454Obs 1572 60 663 160 48 127 248 231

2006 Mean 4342 3387 1690 6161 994 882 3360 11445Median 476 336 395 554 479 419 719 386Obs 1496 56 643 155 46 126 228 209

2007 Mean 25310 3484 1717 248 555 3605 -494 3385Median 187 799 321 329 246 -102 -060 228Obs 1444 61 607 143 41 119 254 189

2008 Mean -11038 564 -1607 -7719 -094 -5202 -2930 -7131Median -040 -348 -037 055 -089 -019 -112 -073Obs 1318 56 557 140 40 106 221 169

Note Whole stands for Wholesale TradeFIRE stands for Finance Insurance and Real Estate

Table 13 Median Wealth Across Sectors ndash Millions of 2005 dollars ndash All CEOs

1993 Wealth 1362 777 1418 774 865 2137 1938 2179Stock 444 210 471 132 479 1236 617 942

Options 131 076 134 040 051 138 310 185

1994 Wealth 1580 749 1745 755 1413 2363 1732 2258Stock 571 214 655 153 362 1325 622 775

Options 175 098 182 041 147 140 264 308

1995 Wealth 1483 839 1594 730 1051 2164 1805 2247Stock 481 270 503 137 306 1338 649 707

Options 153 096 182 021 107 104 226 313

1996 Wealth 1769 1163 1860 840 1378 2098 2512 2597Stock 555 240 577 193 452 989 908 706

Options 258 174 282 058 164 090 520 440

1997 Wealth 2181 1504 2134 971 1306 2760 3454 2672Stock 690 303 645 236 486 1011 1117 1191

Options 371 384 369 090 302 236 812 452

1998 Wealth 2583 1742 2317 1345 1823 3467 4458 3578Stock 854 538 706 360 645 1395 1465 1193

Options 499 386 469 178 327 433 1213 687

1999 Wealth 2421 1050 2129 1588 1821 3142 4622 3245Stock 788 219 637 339 727 1254 1693 1290

Options 420 087 349 239 305 392 1096 636

2000 Wealth 2433 1139 2303 1694 1841 2459 3778 4040Stock 755 183 645 313 617 926 1571 1142

Options 369 181 374 190 223 213 629 697

2001 Wealth 2586 1641 2137 1846 1874 2655 5124 3493Stock 677 500 553 457 541 823 2122 813

Options 505 518 452 354 204 465 1200 667

2002 Wealth 2485 1671 2124 1908 1888 3217 4176 3080Stock 658 388 534 378 437 1023 1818 661

Options 527 317 476 341 295 778 784 714

2003 Wealth 1925 1591 1722 1559 1374 2314 3262 1731Stock 494 394 436 324 416 454 1253 395

Options 276 304 257 212 183 354 470 222

2004 Wealth 2623 2191 2472 1942 1909 3194 3987 2521Stock 709 707 629 504 614 610 1668 619

Options 564 470 551 331 340 793 881 615

2005 Wealth 2878 2644 2439 2030 2265 3520 4375 2637Stock 742 769 573 452 631 744 1918 646

Options 637 781 539 353 787 879 896 696

2006 Wealth 2530 3993 2068 2042 1995 2708 4169 2475Stock 839 1390 643 787 589 665 2126 713

Options 585 1208 445 314 622 786 743 618

2007 Wealth 2501 3721 2045 2061 2304 2883 3705 2161Stock 964 1375 712 828 873 1039 1742 798

Options 500 929 439 273 567 725 561 447

2008 Wealth 2216 4217 2008 1953 2094 1980 2564 2407Stock 938 1909 777 773 1161 938 1413 949

Options 326 783 367 273 489 311 195 343

Sh Gain times Variance idio -2859 -1033 -5092 -34238 -3036 -28855 -21134 -2212 -15919( 0060) ( 0019) ( 0019) ( 0276) ( 0131) ( 0220) ( 0205) ( 0115) ( 0150)

Sh Gain times Variance sys -0146 0170 0562 2144 0654 2261 1216 0537 -0271( 0042) ( 0013) ( 0014) ( 0196) ( 0093) ( 0158) ( 0135) ( 0076) ( 0098)

2 0044 0008 0031 0073 0009 0060 0212 0025 0174

Sh Gain times Sales distrib -4555 -0125 -4106 -27280 -0714 -26199 -16512 -0507 -14777( 0009) ( 0004) ( 0006) ( 0070) ( 0023) ( 0048) ( 0044) ( 0025) ( 0037)

Sales distrib 410446 483086 90420 767486 696996 747138 1842650 1093735 830385( 32047) ( 14194) ( 21824) ( 278578) ( 92443) ( 223103) ( 201464) ( 113086) ( 168649)

2 0054 0023 0037 0088 0025 0075 0252 0073 0205

Introduction

Data and Measurement

Measuring Compensation

The Theoretical Underpinnings of the Total Yearly Compensation Measure

Separation Between Ownership and Control

The Distribution of Compensation across Executives

Compensation Variation in The CrossndashSection of Firms

Compensation Over Time

The Sensitivity of Compensation

The JMndashAS Sensitivity Measure

The SemindashElasticity of Compensation with Respect to Shareholder Wealth

The Elasticity of Executives Wealth With Respect to Shareholder Wealth

Conclusion

Definitions of CEO Wealth and Total Yearly Compensation

The Value of Option Holdings according to the HH Algorithm

Option Pricing

Computation of the net revenue from trade in stock

Expected Discounted Value of Future Cash Payments

More Details on the Data