Compensation Consultant Fees and CEO Pay

Jeh-Hyun Cho

Korea Institute of Public Finance

Jeong-Hoon Hyun

College of Business Administration Seoul National University

Jae Yong Shin College of Business Administration

Seoul National University

May, 2015

We thank Christo Karuna and Paul Kalyta and conference participants at the 2014 Management Accounting Section Midyear Conference and the 2012 Annual Meeting of the American Accounting Association.

 

 

Compensation Consultant Fees and CEO Pay

ABSTRACT:

While compensation consultants are known to play an important role in the design of

executive compensation contracts, prior research on the effect of compensation consultants and

their incentives on CEO pay has provided mixed findings. In December 2009, the SEC required

firms to disclose fees paid for executive compensation consulting (EC service) and other services

(non-EC service) under certain circumstances. Using 3,198 compensation consultant

engagements and 576 executive compensation consulting fee observations from S&P 1500 firms

for fiscal years 2009 to 2011, we examine whether fees paid to executive compensation

consultants (both EC and non-EC fees) are related to greater levels of CEO compensation.

Overall, we find evidence that CEO pay levels are higher when compensation consultants receive

higher EC consulting fees. Further analysis suggests that compensation consultants recommend

higher CEO pay when they receive more than expected fees for EC consulting. These results

support the “repeat business” hypothesis, in which compensation consultants make compensation

advice favoring incumbent managers in order to secure future revenue from their EC clients. We,

however, find limited evidence that consultants’ cross-selling incentives are associated with

greater levels of CEO pay.

Keywords: Compensation consultant; Consulting fee; Abnormal fees Data Availability: Data used in this study is publicly available

 

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I. INTRODUCTION

Compensation awarded to the Chief Executive Officer (CEO) has been a field of interest for

many years. Many researchers have studied the factors that determines the compensation levels,

whether they are optimal, and whether they are excessive, as asserted by many critics. While

through what process and by whom the compensation is determined is an important factor to

consider, however, the role that compensation consultants plays in the compensation-related

decision making has received relatively little attention from researchers in the past due to data

unavailability.

Over the past several years, compensation consultants have played an increasingly important

role in helping boards set and determine executive compensation (Higgins 2007). Such an

increase in the use of compensation consultants is largely due to the increased demands for

companies to align executive pay with shareholder interest. The compensation committee of the

board or the management of the company routinely engages with compensation consultants to

receive advice on executive compensation design. (Cadman et al. 2010; Murphy and Sandino

2010; Armstrong et al. 2012). Consultants are experts on compensation practice issues, such as

relevant regulations, market trends, and benchmark information. Many consultants accumulate

their own proprietary data on executive pay level and compensation practices across different

industries, allowing them to suggest the optimal pay level considering the firm and its peer group

performance (Cadman et al. 2010). With these expertise, consultants are able to effectively

consider different forms of compensation packages and advice the board or the company with

optimal pay levels (Brancato 2002).

There also exists, however, criticisms on the services provided by compensation consultants

(e.g., Waxman 2007). While consultants’ advices may seem as if they are intended to design

 

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effective executive compensation schemes, critics assert that their potential conflict of interest

may bias their advices to secure additional revenues from non-executive compensation service

(non-EC) such as advice on pension plans and executive compensation (EC) consulting service,

suggesting that CEOs could receive higher levels of compensation than warranted by

performance as a result.

Prior research has identified two types of potential conflicts of interest facing compensation

consultants, which can lead to providing biased advice. First is the incentive to secure revenue by

retaining the EC services to the clients, known as the “repeat business” incentives (Cadman et al.

2010; Murphy and Sandino 2010). Furthermore, while some compensation consultants are small

firms that focus exclusively on providing executive compensation services, many are large

consulting companies that also provide services unrelated to executive compensation, such as

actuarial and employee pension plan design. Compensation consultants’ incentive to earn

additional revenue from these non-EC services is called the “cross-selling” incentives. As the

CEO can (ultimately) decide the NEC Service provider, consultants may be inclined to

recommend excessive compensation for the incumbent CEO. This cross-selling incentive can

cause consultants to recommend higher than appropriate level of compensation to the incumbent

CEO, who retains the ultimate decision rights to award them the non-EC services.

The conflicting role of compensation consultants has increasingly caught the attention of

regulators and shareholders. In response, the Securities and Exchange Commission (SEC) in

2006 required companies to disclose whether they retain executive compensation consultants,

and whether consultants are employed directly by the board or the company. Furthermore, the

SEC strengthened the regulation in December 2009 by requiring firms to disclose fees paid for

both EC and non-EC services under certain circumstances. However, critics against the fee

 

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disclosure requirement argue that such regulations are imposed without scientific evidence and

therefore are excessive imposition on companies’ disclosure practices. Prior academic evidence

on whether conflicted compensation consultants recommend more generous executive pay

packages has also produced mixed results (Conyon et al. 2009; Cadman et al. 2010; Murphy and

Sandino 2010).

In this paper, we re-examine whether compensation consultant’s own incentives affect the

CEO pay level by utilizing consulting fee data that became available after the SEC’s 2009

regulation. We hand-collect 3,198 consultant engagement observations and 576 EC fee data from

annual proxy statements from fiscal year 2009 to 2011. While there exist a few studies on the

relationship between compensation consultant incentives and CEO pay (Conyon et al. 2009;

Cadman et al. 2010; Murphy and Sandino 2010), most of them fail to find strong evidence of

biased consultant advice due to conflict of interest. Nonetheless, prior studies have relied on the

data in 2006, thereby lacking any direct fee information and resorting to indirect proxies for

consultants’ conflict of interest. Specifically, these prior studies mostly have used a simple

indicator variable to identify conflicted consultants, which therefore fall short of capturing the

full implications of compensation consultants’ repeat business and cross-selling incentives.

Therefore, we re-visit the initial arguments made by the Waxman Report and test whether

compensation consultants’ conflict of interest, proxied by services fees paid, are positively

associated with CEO pay levels.

Unlike prior studies that find no support for repeat business hypothesis, we find strong

empirical supports for repeat business hypothesis, suggesting that consultants recommend higher

cash, equity, and total compensation when they receive higher EC fees. In contrast to Murphy

and Sandino (2010) but consistent with Conyon et al. (2009) and Cadman et al. (2010), we find

 

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limited evidence that the level of total compensation is higher when non-EC fees are higher,

providing little support for cross-selling hypothesis. These results are robust to controlling for

potential selection bias issues arising from the prior decision to retain a consultant, mandatory

fee disclosure requirement only under some circumstances, and inclusion of both mandatory and

voluntary fee disclosing firms.

In order to examine whether our results supporting repeat business hypothesis are driven by

abnormally high EC fees paid, we build on the literature on the relation between auditor

independence and audit quality (Kinney and Libby 2002; Choi et al. 2010). Specifically, we

derive the abnormal EC fees based on the determinants of EC fees, and then analyze the

relationship between CEO pay and abnormal EC fees, which would be a proxy for the economic

bond between the consultant and client. We expect the relationship between abnormal EC fees

and CEO pay to be positive when EC fees are higher than expected, since excessive EC fees can

increase consultants’ incentive to recommend more generous pay. Consistent with our

expectation, the regression results indicate that abnormally high EC fees are positively associated

with CEO’s total and cash compensation. Overall, the findings from our study challenge the

findings of prior studies such as Conyon et al. (2009), Cadman et al. (2010), and Murphy and

Sandino (2010) who find no evidence that repeat business incentive of a firm’s compensation

consultant is associated with higher level of CEO pay.

This study contributes to the executive compensation literature. First, this study extends the

compensation consultant literature and examines the role of a crucial advisor in designing the

compensation package. While vast prior research has addressed factors related to the effect of

economic, governance, and executive characteristics on executive pay, there is still scare direct

evidence on the effect of outside compensation consultants. Second, this study also contributes to

 

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the literature on whether conflicted consultants contribute to greater levels of CEO pay. Using

direct proxies for repeat business and cross-selling incentives of consultants, we re-investigate

the findings of other studies on incentives of conflicted compensation consultants (Conyon et al.

2009; Cadman et al. 2010; Murphy and Sandino 2010) and provide novel evidence that both the

level of EC fees and abnormal EC fees are positively associated with higher levels of CEO pay,

thereby lending support to “repeat business” hypothesis that prior research finds no support for.

We begin in Section II with background information, prior literature and hypotheses

development. Section III reports the sample and measures used in the study. Section IV provides

empirical models and results on the association between compensation consultant incentives and

CEO pay, and Section V concludes.

II. PRIOR LITERATURE AND HYPOTHESIS

Prior Literature

A report issued by the Corporate Library in October 2007 titled “The effect of compensation

consultants” (Higgins 2007) argues that executive pay levels are significantly higher for

companies that hire compensation consultants and such pay levels do not appear to relate to

increased shareholder return. Another report issued in December 2007 by the US House of

Representatives Committee on Oversight and Government Reform titled “Executive Pay:

Conflicts of interest among compensation consultants” (Waxman 2007), also known as the

“Waxman Report”, suggests that compensation consultants’ conflicts of interest is problematic,

especially since non-EC fees are usually significantly greater than EC fees. The report is based

on proprietary data obtained directly from six leading CCs that provide EC and non-EC services

to Fortune 250 companies between fiscal year 2002 and 2006. It documents that the average

 

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annual EC fee for the sample is $220,000 while the non-EC fee is over $ 2.3 million and that

firms with higher ratio of non-EC fees to EC fees have higher median executive pay than other

firms.

The SEC’s 2006 requirement has made data on compensation consultants accessible,

motivating several studies on the conflicting interests of compensation consultants. Using 1,046

US and 124 Canadian firms that retained compensation consultants during the fiscal year 2006,

Murphy and Sandino (2010) examine the effect of repeat business and the cross-selling

incentives of compensation consultants on CEO pay. They test the repeat business incentives by

examining whether CEO pay is related to managerial influence over the decision to appoint

compensation consultants, proxied by whether the consultant is engaged exclusively by the board

or by the management. Inconsistent with their hypothesis, the result suggests that CEO pay is

actually higher when the consultant works for the board rather than the management, rejecting

the repeat business hypothesis. To test for the effect of cross-selling incentives, they use an

indicator variable on whether the firm also receives actuarial or other services from the same

consultant for the US firms and voluntarily disclosed EC and non-EC fee information for a small

number of Canadian firms. They find that CEO pay is indeed higher when compensation

consultants provide additional services.

Cadman et al. (2010) also tests for the potential cross-selling incentives using 755 firms from

S&P 1500 for fiscal year 2006. They use three proxies for conflicts of interest, namely voluntary

non-EC service disclosures made by companies, engagement with other than Fredrick W. Cook

or Pearl Meyer, consultants that exclusively provide EC services only, and significant non-audit

services indicating a willingness to allow possible conflicts of interests among professional

service providers. Overall, inconsistent with the Waxman Report (2007) and Murphy and

 

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Sandino (2010), Cadman et al. (2010) fail to find widespread evidence of higher pay levels in

client firms hiring consultants with greater cross-selling incentives. They also find no support for

repeat business hypothesis using an indirect proxy for client importance.

In contrast, Armstrong et al. (2012) investigate the effect of governance in the relationship

between CEO pay and compensation consultant engagement. Using 2,110 firms in fiscal year

2006, they find that CEO pay is higher in firms with weaker corporate governance, and those

firms are more likely to have hired compensation consultants. Although use of compensation

consultants leads to higher CEO pay, the effects disappear when governance characteristics are

controlled, indicating that weak governance explains much of the higher pay in companies with

consultants. Furthermore, they find no evidence that CEO pay is higher when firms hire multi-

services consulting firms instead of boutique firms specializing in EC service. Using UK firms,

Conyon et al. (2009) also find little evidence that hiring consultants supplying other services to

client firms leads to higher levels of CEO pay.

Overall, these studies suggest that the repeat business incentive of compensation consultants

is not associated with the level of CEO pay, while evidence on the effect of cross-selling

incentives is mixed. In consistent with the Waxman Report (2007) and Higgins (2007), extant

evidence is consistent with compensation consultants not compromising their role as an expert

advisor despite potential conflicts of interests. This is also consistent with the auditing literature

on whether the provision of non-audit services compromise auditor independence (Ashbaugh et

al. 2003; Chung and Kallapur 2003). However, these studies are based on the SEC’s 2006 that

lacks fee information and thus employ indirect proxies for consultants’ conflict of interest.

Specifically, the aforementioned studies mostly use a simple indicator variable to identify

conflicted consultants, thus falling short of capturing the full implications of compensation

 

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consultants’ repeat business and cross-selling incentives.

Other studies examine the impact of consultant switch on level and structure of CEO pay.

Using a sample of large UK firms, Goh and Gupta (2010) document that firms switching their

main compensation consultant receive a higher yet less risky compensation, consistent with firms

successfully engaging in opinion-shopping. Chu et al. (2015) find that after 2009 fee disclosure

rules (which we will discuss below), CEO pay is higher in firms that switched to specialist EC

consultants than firms that remained with multi-service consultants.

Research Question

Although prior literature overall suggests that compensation consultants’ potential conflict of

interest is not related to CEO pay level, those results are based on indirect proxies for incentives

of conflicted compensation consultants. With the new fee disclosure requirement by the SEC, we

are able to empirically verify whether prior findings on the effect of consultants’ incentives on

CEO pay remain unchanged is largely an empirical issue.1 In the US, the only study that utilizes

the EC and non-EC consulting fees is the Waxman Report, which provides univariate evidence

of higher CEO pay when firms hire consultants with greater conflicts of interest. Therefore, we

re-visit the initial arguments made by the Waxman Report and test whether compensation

consultants’ conflicts of interests, proxied by actual fees paid for their services, are positively

associated with CEO pay levels.

H: Higher consulting fees paid to compensation consultants are positively related to the level of

CEO pay

1 For example, numerous auditing studies have started examining whether non-audit services compromises auditor independence since the SEC’s audit and non-audit fees disclosure requirements in 2001 (e.g., Frankel et al. 2002; Ashbaugh et al. 2003; Chung and Kullapur 2003).

 

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III. INSTITUTIONAL BACKGROUND AND SAMPLE

The New SEC Fee Disclosure Requirement

Until 2006, companies in US were not required to disclose any information on compensation

consultants. However, regulators and shareholders have become more aware of the CEO rent

extraction possibilities by firms employing compensation consultants. In response, the Securities

and Exchange Commission (SEC) in 2006 required companies to identify and describe the scope

of consultants that provide executive compensation services, and disclose whether the

consultants are retained and directed by board’s compensation committee or by company (SEC

2006).

In December 2009, the SEC further expanded the regulation by requiring companies to

disclose fees earned by providing both executive compensation and unrelated services under

certain circumstances. Specifically, if the board or the compensation committee is advised by

compensation consultant on the pay level or compensation package design, and if the consultant

or its integrated affiliates provide non-EC services and these non-EC fees exceed $120,000, then

the firms should disclose the total fees (both EC and non-EC fees) related to all services

provided. The rule also requires companies to disclose whether the decision to engage the

consultant or its non-EC services are made or recommended by the company’s management, and

whether the board or compensation committee approves such non-EC services. If the board and

the company’s management endorse different compensation consultants, then no fee disclosure is

required. Finally, general services involving only non-discretionary plans not specifically

customized for the company (e.g., surveys) are excluded from the scope of EC services

 

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disclosure (SEC 2009)2. Figure 1 provides a summary of the 2009 SEC fee disclosure

requirement.

[Insert Figure 1 About Here]

The Impact of the Fee Disclosure Requirement on the Compensation Consultant Industry

Murphy and Sandino (2010) predict that the 2009 SEC fee disclosure regulations will impact

the selection of compensation consultants in largely two ways. First, firms may stop using

compensation consultants for non-EC services to avoid fee disclosure. Second, firms may hire

two or more consultants, one to provide EC services to the board and the other to the

management. Chu et al. (2015) indeed document that consultant turnover and the number of

specialist firms has dramatically increased after the 2009 SEC fee disclosure regulation.

Interestingly, they also provide evidence that CEO pay is higher in firms that switched from a

multi-service consultant (e.g., Towers Perrin) to a specialist consultant (e.g., Pay Governance

LLC) than in firms that stayed with a multi-service consultant. They interpret their findings as

suggesting that ‘switchers’ are the ones who give additional services to multi-service EC

consultants in exchange for more favorable compensation packages for CEOs and executives.

The above discussion implies that mandatory disclosures requirements could alter firms’

decisions to use consultants for EC and non-EC service. To the extent that the new fee disclosure

rules affect firms’ strategic choice of consultant, firms that previously hired conflicted-

consultants for rent-seeking activities could actively switch to specialist consultants to avoid

disclosing both EC and non-EC consulting fees under the new regulation. Consequently, our

2 In June 2012, the SEC adopted additional rule directing the national securities exchanges to adopt certain listing standards related to the compensation committee as well as compensation consultants, as required by the Dodd-Frank Wall Street Reform and Consumer Protection Act. This rule modified existing rules to require disclosure by eliminating the disclosure exception for services on broad-based plans and non-customized benchmark data, but it did not make any change to the conditional fee disclosure requirements.

 

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findings based on fee information after the new rules in 2009 might understate both the extent of

consultants’ repeat business (since switchers don’t need to disclose fees) and cross-selling

incentives (firms that stayed with multi-service consultants are likely to have hired multi-service

consultants for reasons unrelated to managerial rent-seeking) in periods prior to this new

disclosure regulation.

Sample Construction

We hand-collect the compensation consultant fees for executive compensation and other

services from S&P 1500 companies’ annual proxy statements (DEF-14A) for fiscal year 2009 to

2011 and S&P 1500 firms are selected as of fiscal year 2009. With 4,500 possible firm-year

observations, 98 observations are deducted for missing data due to delisting from S&P 1500 in

2010 and 2011,3 and 588 observations are deducted due to missing variables in the process of

merging the database. From this sample of 3,814 observations, 616 observations are removed

because they do not retain any compensation consultants. There are 3,198 firm-year observations

that retain compensation consultants for executive compensation services, and among them

2,830 firm-year observations either do not engage in any non-EC service or the non-EC fees are

less than $120,000. There is a total of 368 firm-year observations utilizing both EC and non-EC

consulting services, with non-EC services fee exceeding $120,000 (subject to mandatory EC and

non-EC fee disclosure). There are additional 208 observations with voluntary EC service fee

disclosure. Our final sample is comprised of 576 observations with available EC fee disclosure

and 433 observations with available non-EC fee disclosure. Panel A of Table 1 explains the

sample selection process and Panel B of Table 1 shows the sample composition of EC and non-

EC fee disclosures.

3 List of companies that make up the S&P 1500 can change on a daily basis as the companies are listed or delisted as they grow, or are acquired, or fail.

 

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Panel C of Table1 provides a breakdown of five different types of consultant engagement.

Four percent of the total sample hire multiple consultants (Multiple Consultants), a situation

where the primary consultant is hired by the committee but an additional consultant is separately

hired by the management (Type V). We also identify the case, “consultant works exclusively for

the board” (Board Engagement, Type I and II) where the firm does not explicitly state that the

consultant works for the management or that an additional consultant is separately engaged by

management. Murphy and Sandino (2010) use a narrower scope of board engagement in which

the consultant reports only to the board. In our sample, 95 percent of the consultants are

described as “work exclusively for the compensation committee or board”.4

Appendix B illustrates an example of compensation consultant disclosure in Compensation

Disclosure and Analysis (CD&A) report. The compensation committee of Motorola Solutions

hired Compensation Advisory Partners as its independent compensation consultant for 2010.

Compensation Advisory Partners provided only EC consulting service and was paid its EC

consulting fee. The committee also engaged another EC specialized consultant, Compensia, for

the compensation matters for Motorola Mobility prior it its separation from Motorola Solutions.

On the other hand, the management of Motorola Solutions did not engage any EC consultant, but

hired non-EC service provider, Deloitte Consulting. That is, the non-EC fee of Motorola

Solutions’ EC consultant was zero. Therefore, Motorola Solutions voluntarily disclosed its EC

fee and this case can be identified as Type II (multiple consultants engaged by committee). Since

the EC service from Compensia Advisory Patners is the primary CEO compensation consulting

one, we regard the EC fee of Compensia Advisory Patners ($290,342) as EC fee in our sample.

We also take zero value of NEC fee which equals to the non-EC fee of the primary EC

4 Murphy and Sandino show that only 41 percent of the consultants work exclusively for the compensation committee or board, rather than for the management.

 

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consultant.

[Insert Table 1 About Here]

Proxies for Compensation Consultant Incentive

The key predictor variables in the regressions are the consultant incentive variables. We

employ several proxies for consultant incentives from prior literature on compensation

consultants and auditor independence. First, following Cadman et al. (2010) and Murphy and

Sandino (2010), we create an indicator variable (NEC Service) on whether compensation

consultants provide non-EC services to a client firm under the assumption that firms that do not

disclose EC or non-EC fees do not receive any additional non-EC service. (2,613 observations in

our sample). Nonetheless, we are unable to fully rule out the possibility that these firms may

have received non-EC services costing less than $120,000.

Second, in line with Kinney and Libby (2002) and Ashbaugh et al. (2003), we take advantage

of fees paid for non-EC services (NEC Fee) to test the cross-selling incentives hypothesis, where

higher non-EC fees are expected to increase consultants’ incentive to secure their revenues by

recommending excessive pay to CEOs, who retain the decision right to change non-EC service

providers. EC fees (EC Fee) are used to test the repeat business hypothesis, where higher fees

would increase consultants’ incentive to be reappointed and thereby responding with

recommending higher CEO pay. We also test the effect of total fees (Total Fee), the sum of EC

and non-EC fees, since Ashbaugh et al. (2003) argue that total fees best captures the explicit

economic bond between the consultant and client.

Third, following Frankel et al. (2002), Waxman (2007), Cadman et al. (2010), and Murphy

and Sandino (2010), we test whether the fee ratio between EC and non-EC fees have any effect

on CEO pay as a proxy for the cross-selling incentives of consultants. We define the fee ratio

 

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(Fee Ratio) as non-EC fees divided by EC fees as a proxy for capturing relative monetary value

of EC and non-EC services provided by the consulting firm to a client.

Fourth, in an attempt to test repeat business hypothesis with a more powerful measure, we

construct a measure of abnormal EC fees (Residual) by estimating the expected level of EC fees,

which we explain in section IV. In the audit literature, “abnormal fees may more accurately be

likened by attempted bribes” (Kinney and Libby 2002, 109), and therefore can better capture

economic rents arising from auditor-client relationship than actual fees (Choi et al. 2010).

Abnormal fees reflect additional revenue received beyond consideration of firms’ economic and

governance characteristics, indicating that such fees are obtained for idiosyncratic relationship

between compensation consultants and their clients. We further define positive and negative

abnormal EC fees to test how higher-than or lower-than-expected fees affect consultants’

decision to bias their executive compensation services. We expect that positive abnormal EC fees

are indicative of revenues that consultants can receive beyond their normal level of effort,

thereby increasing their incentive to secure an existing relationship with a client firm.

IV. RESEARCH DESIGN AND RESULTS

Summary Statistics

Table 2 reports the descriptive statistics for our sample. All continuous variables are

winsorized at 1 and 99 percentile. In our sample, 433 firm-year observations disclose non-EC

fees and average non-EC fees are $1,442,000. The mean disclosed EC fee for the 576 firm-years

is $164,000 which amounts to 11 percent of the average NEC fee. Thus, the average Fee Ratio

which is defined as NEC Fee divided by EC Fee is about 12. In contrast, the Waxman Report

shows the average EC Fee (NEC Fee) of $220,000 ($2,300,000) for the Fortune 250 firms

 

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between 2002 and 2006. The mean values of both EC Fee and NEC Fee differ from our sample

because our sample encompasses smaller companies during more recent periods as well as large-

sized companies. Additionally, incentives regarding the disclosure of EC Fee and NEC Fee after

the SEC’s 2009 regulation may affect the sample composition.

[Insert Table 2 About Here]

Empirical Method

To examine the impact of compensation consultant incentives on the level of CEO pay, we

model CEO compensation as a function of various measures of compensation consultant

incentives after controlling for CEO, compensation consultant, and firm characteristics

influencing CEO pay. The regression model is as follows5:

CEO Payt = α0 + α1CC variable + α2ln(Assets)t + α3Leveraget + α4Btmt + α5Roat + α6Returnt + α7Returnt-1 + α8Return Volatilityt + α9Chairman CEOt + α10CEO Aget + α11ln(CEO Tenure)t + α12Multiple Consultantst + Industry Effects + Year Effectst + e. (1)

where: CEO Payt is Total Payt, Cash Payt, or Equity Payt, and CC variablet is NEC Servicet, NEC Feet, EC Feet, Total Feet, or Fee Ratiot.

We collect variables related to CEO pay and CEO characteristics from the Execucomp

database. The dependent variables for this study is CEO’s annual total (Total Pay), cash (Cash

Pay), and equity (Equity Pay) compensation. Total compensation (TDC1 on Execucomp) is

comprised of salary, bonus, non-equity incentive plan, grant-date fair value of option and stock

awards, deferred compensation, and remaining other compensation. Following Cadman et al.

(2010), we also use cash compensation, defined as sum of salary, bonus, non-equity incentive

plan, and long-term incentive plan compensation. Equity compensation is comprised of grant-

date fair value of option and stock awards. We expect that cash and equity compensation have

5 For all regressions in this study, standard errors are corrected for heteroskedasticity using the Huber-White robust standard errors clustered by firm and industry fixed effects are controlled based on Fama French 48 industry classification (Fama and French 1997).

 

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different implications in the compensation package design, as secure cash payment may be

preferred by risk-averse CEOs while equity compensation may serve different purposes such as

promoting CEO’s risk-taking incentives.

An indicator variable that CEO also holds the board of directors’ chairman position

(Chairman CEO) is included to control for the influence CEO may have on her own

compensation issues. CEO age (CEO Age) and CEO tenure (CEO Tenure) variables are included

to examine whether boards award different level of compensation packages according to CEOs’

service years.

Following prior literature (e.g., Core et al. 1999), we include standard economic determinants

of CEO pay from Compustat and CRSP databases. Total assets (Asset) captures the size of

companies, leverage ratio (Leverage) shows financial condition of companies, book-to-market

ratio (Btm) indicates companies’ complexities and growth opportunities. We define firm’s

accounting performance as return on assets (Roa) and negative net income (Loss), and stock

price performance as stock returns (Return). Roa is measured as the ratio of income before

extraordinary items to book value of total assets at the beginning of the year. Stock return

volatility (Return Volatility) serves as a proxy for a noisier environment.

We include the variable regarding the consultant selection process. Management can hire an

additional consultant to attain its own information or to be advised on director compensation.

CEO pay could be higher in firms with multiple consultants (Multiple Consultants) since the

decision to hire multiple consultants may be related to firms’ incentives to avoid disclosing fees

and to cloak higher CEO pay (Cadman et al. 2010; Murphy and Sandino 2010).

Results for the Impact of Compensation Consultant Incentives on CEO Total Pay 

 

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Table 3 presents the results from the estimation of Equation (1), which examines the impact

of compensation consultant incentives on CEO total pay. Column (1) shows the results using

NEC Service indicator as the key explanatory variable. As indicated in the Column (1), CEO

total pay level is insignificantly related to the NEC Service indicator, suggesting that consultants

do not recommend higher CEO pay when executive compensation consultants have incentive to

retain other services provided to the companies, consistent with Cadman et al. (2010) but

inconsistent with Murphy and Sandino (2010). Columns (2) and (3) provide further evidence on

compensation consultants’ cross-selling incentives, where NEC Fee is the key explanatory

variable. The regression in Column (2) is based on 433 mandatory and voluntary fee disclosure

observations that reported non-zero non-EC fees and remaining 2,765 observations that were

assumed to have zero non-EC fees. Consistent with our finding with the NEC Service indicator,

CEO total pay level is not correlated with the non-EC fees in Column (2). However, the result

using the non-EC fee disclosure sample based on 433 observations in Column (3) indicates that

higher non-EC fees is associated with greater CEO pay, lending some support to the cross-selling

incentives argument. Taken together, the results in Columns (1) through (3) provide only limited

evidence that compensation consultants’ cross-selling incentives are associated with more

lucrative CEO pay.

Column (4) shows the empirical results using EC fees as the independent variable. The result

indicates that higher EC fees paid to consultants leads to higher CEO total pay. This evidence

supports the notion that when compensation consultant receives higher EC fees (i.e., they have

greater incentive to secure future business with the clients), the consultants are more inclined to

provide biased advice and in turn recommend greater level of CEO pay. This finding is in

contrast with Cadman et al. (2010) and Murphy and Sandino (2010), who fail to find evidence

 

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that repeat business incentives of compensation consultants are related to the level of CEO pay.

In line with Kinney and Libby (2002) and Ashbaugh et al. (2003), who advocate the use of

total fee as a proxy for economic bonding between an auditor and a firm, the result in Column

(5) suggests that total fee (sum of EC and non-EC fee for 424 firm-years disclosing both EC and

non-EC fees) is also positively associated with the level of CEO total pay. Unlike Murphy and

Sandino (2010) who report a positive relation between Fee Ratio and CEO pay using voluntary

EC and non-EC fee disclosures from a small number of Canadian firms, the coefficient on Fee

Ratio is insignificant in Column (6).

As for firm’s economic characteristics variables, company’s size (Assets) and stock price

performance (Return) are positively related to CEO total pay. Book-to-market ratio (Btm), an

inverse measure of investment opportunities, and leverage (Leverage) are negatively related to

CEO total pay. Moreover, firms with multiple consultants (Multiple Consultants) have higher

CEO pay (Kabir and Minhat 2014).6 The coefficients on CEO-related variables indicate that

while older CEOs receive lower pay, the CEO who is also the board’s chairman receives greater

pay.

[Insert Table 3 About Here]

Correcting for Potential Sample Selection Biases

In this section, we examine the incentives of compensation consultants on CEO pay after we

6 If we additionally incorporate the indicator variable on whether the consultant works exclusive for the board (Board Engagement) in Equation (1), we could expect the negative coefficient on Board Engagement because board-engaged consultants presumably have less to gain by recommending generous pay than they would if they work for management (Murphy and Sandino 2010). However, including both consultant selection variables, Board Engagement and Multiple Consultants in a single equation model might result in high multicollinearity problem (correlation = -0.92). To avoid the problem, we only incorporate one variable regarding the consultant selection process. If we replace Multiple Consultants with Board Engagement, the coefficient of Board Engagement is significantly negative in both Columns (1) and (2), further lending support to the repeat business incentive hypothesis. These findings, coupled with those of Chu et al. (2015), that CEO pay is actually higher when the consultant exclusively works for the management or additional consultant is hired by the management stand in sharp contrast to unexpected findings in Murphy and Sandino (2010).

 

19

address potential sample selection biases that may impact our conclusions. We note that there are

three potential sample selection issues underlying the results presented in Table 3. First, as

described in Table 1, about 16 percent of firm-years (616 firm-years out of 3,814 firm-years) has

dropped from our final sample since these firms do not use compensation consultants during our

sample period, suggesting that we need to control for the prior decision to retain a consultant

(Cadman et al. 2010). Consistent with Cadman et al. (2010) who use a Heckman model to

control for this selection issue, we control for the first-stage hiring decision of a consultant by

following a Heckman model discussed in Cadman et al. (2010). In untabulated findings, we

confirm that controlling for the first-stage hiring decision does not significantly change our

conclusions presented in Table 3.7

Second, mandatory disclosures of EC and non-EC consulting fees under some circumstances

(e.g., Figure 1) discussed in Section 3 presents some challenges in interpreting our results in

Table 3. To circumvent the new disclosure requirements, firms may strategically avoid Non-EC

services that exceed $120,000. Firms may switch to specialist consultants who do not provide

any non-EC service. Firms may allocate the EC and non-EC services into separate consultants.

Furthermore, some results presented in Table 3 are subject to selection bias. For example, the

results presented in column (4) are based on a sub-sample of 576 firm-years whose EC fees are

disclosed in proxy statements. A majority of these 576 firm-years (368 firm-years) are mandated

to disclose EC fee information since they receive non-EC service of more than $120,000 from

the same consultant. It is possible that firms that must disclose fee information because of having

7 Consistent with Cadman et al. (2010), we find that CEO ownership percentage is negatively associated and the number of compensation committee meetings is positively associated with the decision to hire a compensation consultant. In addition, as the number of committee member increases, the number of business segment increases, and CEO tenure decreases, the firm is more likely to retain compensation consultant. The pseudo R2 of our probit estimation is 0.213 which is much higher than that of Cadman et al. (2010).

 

20

their EC consultants provide other service after the new rules could be fundamentally different

from other firms. For example, these firms continue to hire its EC consultant for non-EC service

because they are more willing to compromise consultant independence for rent-seeking (Cadman

et al. 2010) or conversely these firms that stayed with multi-service consultants are likely to have

hired multi-service consultants for reasons unrelated to rent-seeking (Chu et al. 2015). Murphy

and Sandino (2010), in their propensity-matching analysis of consultant conflicts of interest, find

that larger, underperforming firms are more likely to be ones who have consultants provide other

services.

While there is little theory to guide us what factors are associated with a decision to have

their EC consultants provide other service to the firm, we employ a Propensity Score Matching

analysis and compare the mean CEO total pay between EC Fee disclosure group (576

observations) and the non-disclosure group (2,622 observations). Appendix C provides details on

a logit model used to find propensity scores.8 Panel A in Table 4 shows no significant difference

between CEO total pay between EC Fee disclosure group (treatment group) and non-disclosure

group (control group). This univariate analysis suggests that it is difficult to conclude that EC fee

disclosure choice drives CEO pay (t-stat. = 0.42).

Third, the association between consultant incentives and CEO pay could vary across the

mandatory versus voluntary disclosure groups. As seen from Panel B of Table 1, our final

sample includes a substantial number of firms disclosing EC and non-EC fee voluntarily when

8 We use a propensity-score matching methodology to account for observable variables that may impact the board’s decision to disclose EC fee (Rosenbaum 2002). We begin our tests by modeling each of these choices through a logistic regression as shown in Appendix C. The model is statistically significant with a pseudo R2 of 0.097. The probability of disclosing EC fee is increasing in firm size and whether CEO is chairman of the board and decreasing in the prior year’s stock return, CEO tenure, and whether the CEO is new to the position. Next, we estimate propensity scores for each firm using predicted probabilities from the logit model. We then match each treatment firm to the closest control, after imposing the constraint that the matching firm selected be within a distance of 0.0058 (equals to 0.05 times standard deviation of the propensity score) of the treatment firm’s propensity score to guarantee the similarity of the observable variables between the treatment and control samples.

 

21

they are not mandated to do so since their EC consultants do not provide other services or a

separate EC consultant is engaged by management. If voluntary EC and/or non-EC fee disclosers

intend to signal that their engagement with a consultant and associated fees are unrelated to

managerial rent-seeking motives, we would expect that including voluntary fee disclosers bias

against our findings presented in Table 3. Consequently, we are not very concerned about that

including the voluntary fee disclosers result in a bias toward our conclusions regarding disclosed

fees and CEO pay. Nevertheless, we re-estimate the equation (1) using a sub-sample with

mandatory fee disclosures and report our findings in the Panel B of Table 4. In Column (1), we

use a modified NEC Service indicator which is one if firms mandatorily disclose their non-EC

fees (368 observations) and zero otherwise (2,830 observations). In Column (2), we use modified

non-EC fees with zero assumption, representing that NEC Fee equals to non-EC fee amount only

if firms are mandatory disclosers (368 observations), otherwise NEC Fee is zero. Results

presented in Columns (3) through (6) are based on 368 observations of mandatory fee disclosures

only.

As indicated in the Column (1) to (6), only EC fee level is positively related to the CEO total

pay, suggesting that consultants appear to recommend higher CEO compensation only when they

have incentive to secure their existing business (repeat business incentive), whereas cross-selling

incentive does not prevail in our sample. That is, the relationship between EC fees and CEO

compensation continue to hold, regardless of whether disclosed fee information is voluntary or

mandatory. Moreover, when our sample is restricted to mandatory fee disclosures, the limited

evidence of cross-selling incentives in Table 3 disappears.

[Insert Table 4 About Here]

Result for the Impact of EC Fees on CEO Cash and Equity Pay 

 

22

So far, our evidence provides only limited evidence that the provision of non-EC services by

EC consultant is related to CEO pay. In contrast with prior studies, however, we find robust

evidence supporting that consultants’ retention incentives to secure lucrative EC service (repeat

business) may contribute to biasing their pay advice. Consequently, we further examine whether

the EC fee levels can explain variations in CEO pay components, Cash Pay and Equity Pay.

Columns (1) and (2) provide empirical results for the entire EC fee disclosure sample (based on

576 observations), suggesting that both cash and equity pay are positively related to the level of

EC fees. If we restrict the sample to mandatory EC fee disclosures, only CEO equity pay is

positively related to the EC fees, as indicated in Column (4). Overall, the results are similar to

the findings in Table 3, which show support for the repeat business hypothesis.

[Insert Table 5 About Here]

Analysis of the Determinants of Executive Compensation Consulting Fees

The audit literature suggests that auditors’ incentives to deter biased financial reporting differ

systematically, depending on whether their clients pay more or less than the normal level of audit

fee (Kinney and Libby 2002; Choi et al. 2010). Consistent with the literature that interprets audit

fee residuals as auditor rents that may impair auditor independence (Defond et al. 2002; Choi et

al. 2010; Hope and Langli 2010; Kanagaretnam et al. 2010)9, we estimate the expected EC fees

and fee residuals based on determinant model of EC fees and additionally test whether our

results supporting repeat business hypothesis are driven by abnormally high EC fees paid. Since

there is limited theory and prior research to guide us regarding the determinants of compensation

consulting fees, we adopt and modify the determinant model of audit fees (Defond et al. 2002;

9 Recent research such as Doogar et al. (2015), however, argue that audit fee residuals are a combination of auditor rents and unobserved audit production costs and that interpreting fee residuals as a measure of auditor rents is problematic.

 

23

Choi et al. 2010; Hope and Langli 2010; Kanagaretnam et al. 2010)10 by reflecting the models to

retain a compensation consultant in prior research (Cadman et al. 2010; Armstrong et al. 2012)

and estimate the following exploratory model of EC fee determinants as follows:

EC Feet = α0 + α1ln(Assets)t + α2ln(Employees)t + α3Roat + α4Leveraget + α5Btmt + α6Sales Growtht + α7Board Engagementt + α8Multiple Consultantst

+ α9Committee Independencet + α10Committee Busyt + α11ln(Committee Meet)t + α12Pay Mixt + α13ln(Cda Words)t + α14Foreignt + α15Big5 Consultantst + α16Chairman CEOt + α17CEO Aget + α18New CEOt + α19CEO Ownershipt + Industry Effects + Year Effectst + e. (2)

In estimating the determinants of EC consulting fees to construct a measure of abnormal EC

fees, we employ firm’s consultant, economic, and CEO characteristics. The demand for EC

consulting services is likely to increase with firm size, leading to a positive association between

firm size and EC fees. We include firm’s total asset (Assets) and the number of employees

(Employees) to control for client size. Since consultants charge higher EC fees for risky clients

(Simunic and Stein 1996), we include Roa and Leverage to proxy for a client’s risk

characteristics. In addition, the demand for consultant services is greater for high-growth firms

than for low-growth firms (Choi and Wong 2007). To control for these effects, we include Btm

and Sales Growth. The variables of consultant selection process, Board Engagement and

Multiple Consultants are included to control for the consultant selection effect on EC fees. We

include governance variables which are obtained from Risk Metrics database (Cadman et al.

2010; Armstrong et al. 2012). We consider the governance variables related to compensation

committee’s ability to monitor, such as the busyness of committee (Committee Busy),

independence of committee (Committee Independence), and number of compensation committee

meetings in the fiscal year (Committee Meet). We additionally include variables measuring pay

design complexity such as pay mix (Pay Mix), existence of foreign operation (Foreign) and

10 Simunic (1980) argues that the audit engagement fee reflects both auditor efforts and potential cost of litigation.

 

24

number of words in CD&A report (Cda Words). To account for fee premiums for high-quality

EC consultants, we identify the use of major Big5 consultants (Big5 Consultants), which are

Frederic W. Cook, Towers Perrin, Hewitt Associates, Mercer and Watson Wyatt to capture the

effect of Big 5 consultants on EC fees. Also, we add three indicator variables, Chairman CEO,

CEO Age, and New CEO, and a continuous variable, CEO Ownership to represent the CEO

characteristics. Finally, we include variables for compensation consultant characteristics, and

industry and year indicator variables to control for industry and year effects.

Table 6 presents the estimation results of Equation (2) where the natural logarithm of EC Fee

is the dependent variable. In line with increasing demand for larger firms and growth firms, we

find a positive coefficient on ln(Assets) and a negative coefficient on Btm. The coefficient of

Leverage is positive, suggesting that compensation consultants are likely to demand higher fees

for financially distressed firms since evaluating CEO performance in financially distressed firms

could be more challenging. Compensation committee meeting (Committee Meet) is positively

related to EC fees, indicating that more diligent committee supports the purchase of differentially

higher-quality consulting services, resulting in higher EC fees. Moreover, we find that board

engaged consultant (Board Engagement) is paid more. Pay design complexity (Cda Words) is

positively related to EC fees as pay design complexity requires more service hours from the

consultants. CEO ownership percentage is negatively associated with EC fee since greater CEO

ownership reduces agency problems thus decreasing the need for more complex pay plans. A

new CEO requires a new pay design, so fees will increase when a new CEO is appointed.

Although the adjusted R-squared, 0.358, is smaller than that of conventional audit fee

determinants, it provides a reasonable explanatory power to obtain abnormal EC fee metric.

[Insert Table 6 About Here]

 

25

Analysis of the Impact of Abnormal Executive Compensation Consulting Fees on CEO Pay

Using the estimated coefficients from Equation (2), we compute the fitted values of the EC

fees and use them as “normal EC fees.” We obtain the residuals (Residual) from individual

annual estimations of Equation (2) (excluding year indicators) to estimate the extent to which

ln(EC Fee) deviates from the expected level. Such abnormal EC fees explain the idiosyncratic

relationship between the consultant and the company. In the audit literature, abnormal fees may

be viewed as attempted bribes (Kinney and Libby 2002), and therefore can capture additional

revenues from idiosyncratic auditor-client relationship. Therefore, positive abnormal EC fees

could be an indication of additional revenues that consultants can receive beyond their normal

level of effort, thereby increasing their incentive to secure its relationship with the firm, which

may lead to recommending higher CEO pay levels. The following Equation (3) tests the impact

of abnormal EC fees on CEO pay.

CEO Payt = α0 + α1Positive Residualt + α2Negative Residualt + α3ln(Assets)t + α4Leveraget + α5Btmt + α6Roat + α7Returnt + α8Returnt-1 + α9Return Volatilityt + α10Chairman CEOt + α11CEO Aget + α12ln(CEO Tenure)t + α13Multiple Consultantst + Industry Effects + Year Effectst + e. (3)

where: CEO Pay is Total Pay, Cash Pay, or Equity Pay.

Equation (3) uses the same control variables as in Equation (1), except the key independent

variable is the positive and negative abnormal EC fees calculated from Equation (2). Following

Shin et al. (2015), Ittner et al. (2003), and Wade et al. (2006), we include separate variables for

positive and negative residuals to capture higher- or lower-than-expected EC fees. If the

deviation from the expected level of fees is an important factor in determining the level of

consultants’ repeat business incentives, then higher positive abnormal EC fees are expected to

increase CEO pay. The association between negative abnormal EC fees and CEO pay is

uncertain. On one hand, receiving smaller fees for the level of service may lower consultants’

 

26

incentive to retain the client. But on the other hand, consultants may be reluctant to deliberately

recommend lower CEO pay and in turn increase the chance of losing the client.

The regression results from Equation (3) are shown in Table 7. Consistent with our

expectation, the findings in Columns (1) through (3) indicate that positive abnormal EC fees are

significantly associated with CEO’s total and cash pay, whereas negative abnormal EC fees have

no impact on CEO pay. This evidence is consistent with the previous evidence on the relation

between EC fees and CEO pay being driven by positive abnormal EC fees and not by negative

abnormal EC fees. Again, this result supports the repeat business hypothesis. Consultants are

concerned about that the client will not retain the consultant for future EC services especially

when they can derive higher revenue for a given amount of effort. These concerns can lead them

to bias their recommendation in favor of the CEOs, resulting in lucrative pay packages. The sign

and significance of all other control variables are consistent with those in Table 3.

We also consider an alternative method for estimating Equation (2) as part of our sensitivity

checks. We estimate Equation (2) after deleting the voluntary fee disclosures and re-examine the

effect of abnormal EC fees on CEO pay as shown in Columns (4) to (6). The results remain

similar and continue to support the repeat business hypothesis.11

[Insert Table 7 About Here]

Further Analyses

Alternative Proxy for Repeat Business Incentives

We use a different proxy for repeat business incentive of consultants as a robustness test.

Cadman et al. (2010) develop the variable Percent Client Size, which equals the percent of assets

that the client represents relative to the sum of total assets of all of the consultant’s clients in the

11 Column (6) shows that positive abnormal EC fee is also positively associated with equity compensation using restricted sample of mandatory EC fee disclosures.

 

27

sample.12 This variable captures the relative importance of the particular client to a consultant,

quantifying the repeat business incentives of a consultant. Untabulated results present that when

we additionally include Percent Client Size in Equation (1) where the dependent variable is CEO

total pay, the coefficient on EC Fee remains positively significant at the 1 percent level. The

coefficient on Percent Client Size is negatively significant at the 5 percent level, suggesting that

the relative importance of clients is inversely related to the CEO total pay, a result inconsistent

with repeat business incentive hypothesis.13 These results imply that our proxy EC Fee is more

accurate and powerful in capturing repeat business incentives than the indirect proxy for repeat

business incentives, Percent Client Size used by prior research.

Excluding Financial Firms

Another possibility is that financial firms are fundamentally different from non-financial in

terms of CEO pay, CEO characteristics, firm economic characteristics, and compensation

committee characteristics. The results remain unchanged after we exclude financial firms from

our sample. Specifically, the association between EC Fee and CEO total pay remain significant

at the 1 percent significance level and the variables related to the cross-selling hypothesis are all

insignificant.

Other Robustness Tests

As further robustness tests, we use alternative types and definitions of control variables to

confirm our results. Existence of a founder CEO, number of business segments, and big

compensation consultant variables do not significantly alter the main findings of the study, while

they only change the statistical significance of other control variables. We also adopt a different

12 Cadman et al. (2010) provide the numerical example regarding the variable construction. “If a consultant retains three clients, with total assets of $100 million, $200 million, and $700 million, then PCT equals 0.1, 0.2, and 0.7, respectively.” 13 The correlation between Percent Client Size and EC Fee is -0.09 (p-value = 0.03).

 

28

model to test the impact of abnormal EC fees on CEO pay by including an interaction variable

between abnormal fees and a positive abnormal fee indicator variable (Choi et al. 2010).

Untabulated results show similar results to those in Table 7 with a significance level of

interaction variable between abnormal EC fee and a positive abnormal EC fee dummy) on CEO

total pay regression decreasing to the 10 percent level.

V. CONCLUSION

In this paper, we examine whether compensation consultants’ own incentives affect the CEO

pay level, by utilizing consulting fee data accessible through the SEC’s 2009 regulation. We

hand-collect 3,198 consultant engagement information and 576 EC fee and 433 non-EC fee data

from firms’ annual proxy statements from fiscal year 2009 to 2011. Our results on the impact of

compensation consultants’ incentives on the level of CEO pay are consistent with consultants

recommending higher CEO pay when they receive higher EC fees, thus supporting the repeat

business hypothesis. We, however, find limited evidence that the level of CEO pay is higher

when non-EC fees are higher, not generally supporting the cross-selling incentives. In order to

examine whether our results on the relation between EC fees and CEO pay are driven by

abnormal EC fees, we estimate the determinants of EC fees and analyze the relationship between

abnormal EC fees and CEO pay. Consistent with abnormal EC fees increasing consultants’

incentive to bias their pay recommendations, our regression results indicate that positive

abnormal EC fees are significantly associated with CEO’s total and cash pay.

This study contributes to the executive compensation literature in several ways. First, by

extending the studies on the role of compensation consultants, this study fills the void in the

literature on a significant participant in designing executive compensation packages. While prior

 

29

research has addressed factors related to firm economics, governance, and executive

characteristics, direct evidence on outside consultants has been scarce until now. Furthermore,

this study challenges the findings of prior studies on the relation between conflicted

compensation consultants and CEO pay (Conyon et al. 2009; Cadman et al. 2010; Murphy and

Sandino 2010) with more direct proxies for consultants’ incentives and provides novel evidence

consistent with repeat business incentives motivating consultants to bias their advice.

Consultants are concerned about that the client will not retain the consultant for future EC

services especially when they can derive higher revenue for a given amount of effort. These

concerns can lead them to bias their recommendation in favor of the CEOs, resulting in lucrative

pay packages.

The limitations of our study provide opportunities for future research. First, although our results

hold after controlling for various selection biases arising from a decision to retain compensation

consultants, a decision to have their EC consultants provide other service to the firm, and firms

that voluntarily disclose their EC and non-EC fees, we are unable to completely rule out the

possibility that our results could be clouded by sample selection issues. Second, in line with the

audit literature that interprets audit fee residuals as auditor rents, we interpret EC fee residuals as

consultant rents associated with economic bonding between a consultant and a firm. Fee

residuals, however, may simply capture noise and unobserved EC consulting costs.

 

30

APPENDIX A Definition of Variables

 

Variables Description

NEC Service = 1 if firm retains non-executive compensation service from the same compensation

consultant who serves executive compensation service, 0 otherwise; NEC Fee = non-executive compensation service fees;

EC Fee = executive compensation service fees; Total Fee = sum of executive compensation service fees and non-executive compensation

service fees (= NEC Fee + EC Fee); Fee Ratio = ratio of non-executive compensation service fees to executive compensation

service fees (= NEC Fee / EC Fee); Residual = actual ln(EC Fee) minus expected ln(EC Fee) estimated in Equation (2);

Multiple Consultant = 1 if the board and management have different executive compensation consultants, 0 otherwise;

Board Engagement = 1 if the compensation consultant is solely engaged by the board, 0 otherwise; Big5 Consultants = 1 if the executive compensation consultant is one of the big five executive

compensation consulting firm (Frederic W. Cook, Towers Perrin, Hewitt Associates, Mercer and Watson Wyatt), 0 otherwise;

Percent Client Size = client's assets scaled by the sum of the assets for all of the consultant’s clients; Cda Words = number of words in Compensation Discussion & Analysis disclosure (CDA);

Total Pay = CEO’s annual total compensation (TDC1 on Execucomp); Cash Pay = CEO’s annual cash compensation (salary + bonus + non-equity incentive + Long

Term Incentive Program); Equity Pay = CEO’s annual equity compensation (grant date fair value of stock + grant date fair

value of options); Pay Mix = ratio of long-term variable pay to total compensation;

Chairman CEO = dummy variable indicating CEO holding board’s Chairman position; CEO Age = 1 if CEO age is over 65, 0 otherwise;

CEO Tenure = years since date became CEO; CEO Ownership = percentage of total shares owned by CEO;

New CEO = dummy variable indicating change in CEO during the year; Assets = total assets;

Leverage = total debt divided by total assets; Btm = book-to-market ratio at fiscal-year-end; Roa = return on assets (net income minus income from discontinued operation divided by

beginning of the year assets); Loss = 1 if return on assets (Roa) has a negative value, 0 otherwise;

Return = monthly compounded annual stock return; Return Volatility = standard deviation of monthly compounded annual stock returns (Return) over five

years (t-5 to t-1); Sales Growth = sales growth (percent sales change from the prior year);

Foreign = 1 if the firm pays any foreign income tax, otherwise; Biz segment = number of business segments; Employees = number of employees;

Committee Size = number of compensation committee members; Committee Independence = fraction of outside directors on total number of compensation committee members;

Committee Busy = percent of directors holding three or more directorships; Committee Meet = number of meetings held by compensation committee; and

Committee Tenure = average tenure of compensation committee members.

 

31

APPENDIX B An Example of Compensation Consultant Disclosure

Following is an example of compensation consultant engagement and consulting fee information disclosed in 2010 proxy statement of Motorola Solutions, Inc. Independent Consultant Engagement The Committee engages an independent consultant to advise them on the Company’s compensation strategy and program design. The consultant conducts an in depth evaluation of our compensation program on a periodic basis (typically every one or two years), and annually reviews the specific compensation of our CEO and our senior leadership team, including our NEOs. During 2010, the Committee chose to continue the engagement of Compensation Advisory Partners as its independent compensation consultant. Compensation Advisory Partners does not have any other business or consulting relationships with the Company, and no additional business relationships are anticipated in the future. The Committee has occasional discussions with Compensation Advisory Partners without management present to ensure impartiality on certain decisions. In 2010, the Committee also engaged Deloitte Consulting to consult on the amendments to Dr. Jha’s employment agreement. Deloitte Consulting provides other services to the Company, but does not provide any other compensation consulting services to the Committee. The Committee does not anticipate any future Committee-related compensation consulting engagements with Deloitte Consulting. Motorola Mobility management engaged Deloitte Consulting separately on compensation matters during 2010 to support the Motorola Mobility business in preparation for the Separation. Prior to the Separation, the Committee decided to engage another compensation consultant, Compensia, as the consultant to the Committee for Motorola Mobility compensation matters. Compensia does not have any other business relationships with either Motorola Solutions or Motorola Mobility. The fees during 2010 for the three consultants are shown in the table below:

Type of Fees Compensation

Advisory Partners Compensia Deloitte Consulting

Committee-related $290,342 $349,498 $31,408Non-Committee-related $0 $0 $14,035,573

 

32

APPENDIX C Logit Regression Result of Executive Compensation Consultant Fee Disclosure a

(1) Dependent variable Prob(EC Fee Disclosure) ln(Assets)t 0.294*** (7.17) Roat 1.023

(1.12)Btmt -0.076 (-0.42) Returnt -0.220 (-1.50) Returnt-1 -0.242** (-2.01) Chairman CEOt 0.369*** (3.21) CEO Aget -0.087 (-0.43) ln(CEO Tenure)t -0.319*** (-3.24) New CEOt -0.477** (-2.26) Pay Mixt -0.455 (-1.58) Committee Sizet 0.047 (0.98) Committee Independencet 0.458 (0.50) ln(Committee Tenure)t 0.101 (0.70) Committee Busyt -0.153 (-0.73) ln(Committee Meet)t -0.024

(-0.16)Intercept -7.596*** (-5.12) Fixed Effects Year and Industry No. of observations 3,198 Pseudo R2 0.097

Z-statistics are reported in parentheses under each estimated coefficient. Standard errors are corrected for heteroskedasticity using the Huber-White robust standard errors clustered by firm. To mitigate any undue influence from outliers all continuous variables are winsorized at the top and bottom one percentile. The symbols *, **, and *** correspond to 10 percent, 5 percent, and 1 percent significance levels for two-tailed t-tests, respectively. The dependent variable EC Fee Disclosure is 1 if firm discloses EC fees, 0 otherwise. a The Logit regression model for this analysis is as follows:

Prob(EC Fee Disclosure)t = α0 + α1ln(Assets)t + α2Roat + α3Btmt + α4Returnt + α5Returnt-1

+ α6Chairman CEOt + α7CEO Aget + α8ln(CEO Tenure)t + α9New CEOt + α10Pay Mixt + α11Committee Sizet + α12Committee Independecet + α13ln(Committee Tenure)t

+ α14Committee Busyt + α15ln(Committee Meet)t + Industry Effects + Year Effectst + e. (A1)

 

33

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FIGURE 1 2009 SEC Fee Disclosure Requirement

The SEC requires the companies to disclose fees earned by providing both executive compensation and non-executive compensation services under certain circumstances. Specifically, if the board or the compensation committee engages its own compensation consultant to provide advice or recommendations on the design of executive compensation, and if the consultant or its integrated affiliates provide services other than executive compensation consulting to the company, then disclosure of the fees related to all services provided are required given that the fees for services the NEC services is more than $120,000. If the board and the company’s management engage separate compensation consultants, then no disclosure is required (SEC 2009).

NEC fee ≥ $120,000

Disclosure (EC fee and NEC fee)

Solely Board- or Company-engaged Consultant

No Disclosure

Yes No

Yes No

(Board and Company hire different consultants)

 

37

TABLE 1 Sample Selection

Panel A: Sample Selection

Initial Sample from S&P 1500 for Fiscal Years from 2009 to 2011 Firm-Year Observations

S&P 1500 firms 4,500 Deduct firms with missing years (98) Deduct firms with missing variables due to database merge (588) Initial sample 3,814 Deduct firms without compensation consultant (616) Executive compensation consulting fees sample 3,198

Panel B: Sample Composition of Consulting Fee (EC fee and NEC fee)

Consultant Engagement Condition

Total

(a)+(b)+(c)+(d)

No disclosure

(a)

OnlyEC fee

(b)

Only NEC fee

(c)

Both EC & NEC fees (d)

Total EC fee

(b)+(d)

Total NEC fee

(c)+(d)

(1) NEC fee less than $120,000 or Multiple consultants case (Voluntary Disclosure case)

2,830 2,613 152 9 56 208 65

(2) Solely Board or Company engaged consultant (Mandatory Disclosure case)

368 - - - 368 368 368

3,198 2,613 152 9 424 576 433

Panel C: Sample Composition by EC Consultant Engagement

Type Definition #Obs

(%)

#Obs w/ EC Fee

(%)

Mandatory Fee Disclosure a

Board Engagement

Multiple Consultants

I Only one consultant engaged by committee

2,991 (93.5%)

538 (93.4%)

Yes Yes No

II Multiple consultants engaged by committee

55 (1.7%)

8 (1.4%)

Yes Yes No

III Only one consultant engaged by management

23 (0.7%)

8 (1.4%)

Yes No No

IV Multiple consultants engaged by management

- - Yes No No

V

Additional consultant engaged by management, where the primary consultant is engaged by committee

129 (4.0%)

22 (3.8%)

No No Yes

Total 3,198 576 In Panel A, S&P 1500 firms are selected as of fiscal year 2009. In Panel B, 3,198 total observations of executive compensation consulting fees consist of 368 mandatory disclosure observations, 217 voluntary disclosure observations, and 2,613 non-disclosure observations. 576 (433) executive (non-executive) compensation consulting fee observations consist of 368 (368) mandatory disclosure observations and 208 (65) voluntary disclosure observations. a This classification whether firms should disclose their EC fee and non-EC fee is assumed that the receive non-EC service of more than $120,000. If the non-EC fee of the firms do not exceed $120,000, no fee disclosure is required.

 

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TABLE 2 Descriptive Statistics

Variables a N MeanStandard Deviation Min 25% Median 75% Max

Consultant:

NEC Service 3,198 0.14 0.34 0.00 0.00 0.00 0.00 1.00NEC Fee ($K) 433 1,442 2,264 8 194 555 1,581 13,000EC Fee ($K) 576 164 125 12 66 136 224 605Total Fee ($K) 424 1,816 3,877 22 337 732 1,817 50,604Fee Ratio 424 12.05 22.85 0.17 1.83 4.36 11.71 145.25Residual 576 0.00 0.58 -1.88 -0.32 0.00 0.39 1.27Multiple Consultants 3,198 0.04 0.20 0.00 0.00 0.00 0.00 1.00Board Engagement 3,198 0.95 0.21 0.00 1.00 1.00 1.00 1.00Big5 Consultants 3,198 0.32 0.47 0.00 0.00 0.00 1.00 1.00Percent Client Size 3,198 0.07 0.20 0.00 0.00 0.00 0.02 1.00Cda Words 576 16,202 4,784 5,991 12,630 15,935 19,510 30,479

CEO: Total Pay ($K) 3,198 6,077 5,270 533 2,442 4,511 7,917 29,701Cash Pay ($K) 3,198 3,398 3,569 0 949 2,253 4,616 18,697Equity Pay ($K) 3,198 1,294 1,598 0 200 829 1,779 9,515Pay Mix 3,198 0.73 0.19 0.00 0.67 0.79 0.85 0.96Chairman CEO 3,198 0.59 0.49 0.00 0.00 1.00 1.00 1.00CEO Age 3,198 0.08 0.27 0.00 0.00 0.00 0.00 1.00CEO Tenure 3,198 7.98 6.16 1.00 4.00 6.00 11.00 31.00CEO Ownership 3,198 0.01 0.03 0.00 0.00 0.01 0.01 0.21New CEO 3,198 0.09 0.28 0.00 0.00 0.00 0.00 1.00

Economic: Assets ($M) 3,198 15,603 40,570 178 1,183 3,370 11,192 302,510Leverage 3,198 0.56 0.21 0.11 0.41 0.56 0.71 0.98Btm 3,198 0.59 0.36 0.01 0.34 0.53 0.77 1.91Roa 3,198 0.05 0.07 -0.17 0.01 0.05 0.09 0.28Loss 3,198 0.13 0.34 0.00 0.00 0.00 0.00 1.00Return 3,198 0.20 0.42 -0.58 -0.05 0.15 0.36 2.00Return Volatility 3,198 0.11 0.04 0.04 0.08 0.11 0.13 0.28Sales Growth 3,198 0.06 0.20 -0.46 -0.05 0.05 0.14 0.91Foreign 3,198 0.61 0.49 0.00 0.00 1.00 1.00 1.00Biz Segment 3,198 3.37 2.25 1.00 1.00 3.00 5.00 10.00Employees 576 28,324 52,445 59 3,538 9,800 27,900 317,000

Compensation Committee: Committee Size 3,198 3.87 1.07 2.00 3.00 4.00 4.00 7.00Committee Independence 3,198 0.99 0.06 0.67 1.00 1.00 1.00 1.00Committee Busy 3,198 0.27 0.26 0.00 0.00 0.25 0.50 1.00Committee Meet 3,198 6.52 2.77 2.00 5.00 6.00 8.00 17.00Committee Tenure 3,198 9.58 3.89 2.75 6.80 9.00 11.67 22.67

The sample consists of 3,198 firm-year observations of S&P 1500 firms for fiscal year 2009 and 2011. Data for consulting service are hand-collected from companies’ proxy statements. CEO characteristics are attained from Execucomp, data for firm’s economic financial data is obtained from Compustat and CRSP, and governance variables are obtained from Risk Metrics. All continuous variables are winsorized at 1 and 99 percentile. Refer to the variable definitions in Appendix A.

 

39

TABLE 3 Impact of Compensation Consultant Incentives on CEO Total Pay

(1) (2) (3) (4) (5) (6)

Dependent variable ln(Total Pay)t ln(Total Pay)t ln(Total Pay)t ln(Total Pay)t ln(Total Pay)t ln(Total Pay)t

Independent variable (CC variable)

NEC Servicet ln(NEC Fee)t

(w/ zero assumption)

ln(NEC Fee)t ln(EC Fee)t ln(Total Fee)t Fee Ratiot

CC variable 0.019 0.002 0.040* 0.141*** 0.059** 0.000 (0.57) (0.81) (1.94) (4.43) (2.01) (0.24)

ln(Asset)t 0.410*** 0.410*** 0.407*** 0.402*** 0.399*** 0.427*** (24.37) (24.27) (14.10) (16.98) (13.20) (15.34)

Leveraget -0.390*** -0.391*** -0.392 -0.474** -0.398* -0.365 (-4.08) (-4.09) (-1.65) (-2.56) (-1.68) (-1.50)

Btmt -0.463*** -0.463*** -0.536*** -0.593*** -0.527*** -0.529*** (-8.86) (-8.86) (-4.55) (-5.62) (-4.44) (-4.31)

Roat -0.140 -0.141 0.990* 0.014 1.015* 0.954 (-0.36) (-0.36) (1.65) (0.02) (1.67) (1.54)

Losst -0.063 -0.062 -0.037 -0.130 -0.024 -0.044 (-1.20) (-1.20) (-0.34) (-1.19) (-0.22) (-0.38)

Returnt 0.051* 0.051* 0.025 -0.022 0.028 0.019 (1.73) (1.74) (0.32) (-0.29) (0.35) (0.24)

Returnt-1 0.082*** 0.082*** 0.078 0.154*** 0.074 0.066 (3.96) (3.96) (1.57) (2.63) (1.42) (1.30)

Return Volatilityt -0.344 -0.343 0.449 -1.186 0.226 0.506 (-0.88) (-0.88) (0.41) (-1.45) (0.20) (0.44)

Chairman CEOt 0.089*** 0.089*** 0.192** 0.154** 0.199** 0.199** (3.15) (3.14) (2.54) (2.20) (2.55) (2.50)

CEO Aget 0.012 0.012 -0.151 -0.205* -0.150 -0.142 (0.21) (0.21) (-1.00) (-1.96) (-0.97) (-0.92)

ln(CEO Tenure)t 0.040 0.040 -0.025 -0.002 -0.024 -0.027 (1.61) (1.62) (-0.50) (-0.04) (-0.48) (-0.52)

Multiple Consultantst 0.170*** 0.171*** 0.217 0.235* 0.219 0.207 (2.65) (2.66) (1.47) (1.87) (1.49) (1.39)

Intercept 5.754*** 5.756*** 3.731*** 4.198*** 3.630*** 3.936*** (31.52) (31.45) (8.16) (10.79) (7.74) (8.07)

Fixed Effects Year and Industry

Year and Industry

Year and Industry

Year and Industry

Year and Industry

Year and Industry

No. of observations 3,198 3,198 433 576 424 424

Adjusted R2 0.588 0.588 0.683 0.668 0.682 0.677 T-statistics are reported in parentheses under each estimated coefficient. Standard errors are corrected for heteroskedasticity using the Huber-White robust standard errors clustered by firm. To mitigate any undue influence from outliers all continuous variables are winsorized at the top and bottom one percentile. The symbols *, **, and *** correspond to 10 percent, 5 percent, and 1 percent significance levels for two-tailed t-tests, respectively. Please refer to the paper for a detailed explanation of these tests.

 

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TABLE 4 Impact of EC Fee Disclosure Issue on the Association between EC Fee and CEO Total Pay

Panel A: Mean Difference between EC Fee Disclosure Group and EC Fee Non-disclosure Group

EC Fee Disclosure (Treatment Group)

Non-Disclosure (Control Group)

No. of total observations 576 2,622 No. of matched observations 551 551

Mean of Total Pay 6,880 6,742 Difference (t-stat) 138 (0.42)

Panel B: Impact of Compensation Consultant Incentives on CEO Pay using Mandatory Disclosure Sample

(1) (2) (3) (4) (5) (6) Dependent variable ln(Total Pay)t ln(Total Pay)t ln(Total Pay)t ln(Total Pay)t ln(Total Pay)t ln(Total Pay)t

Independent variable (CC variable)

NEC Service2t ln(NEC Fee)t

(w/ zero assumption)

ln(NEC Fee)t ln(EC Fee)t ln(Total Fee)t Fee Ratiot

CC variable 0.042 0.003 0.007 0.072** 0.017 -0.000 (1.20) (1.25) (0.27) (2.00) (0.50) (-0.35)

ln(Asset)t 0.411*** 0.411*** 0.421*** 0.411*** 0.417*** 0.427*** (24.50) (24.41) (12.55) (14.23) (12.26) (13.89)

Leveraget -0.389*** -0.389*** -0.523** -0.575** -0.526** -0.522** (-4.07) (-4.07) (-2.19) (-2.49) (-2.20) (-2.19)

Btmt -0.466*** -0.466*** -0.497*** -0.483*** -0.496*** -0.497*** (-8.88) (-8.89) (-4.42) (-4.36) (-4.43) (-4.37)

Roat -0.163 -0.162 1.178** 1.122** 1.186** 1.165** (-0.42) (-0.41) (2.14) (2.11) (2.16) (2.15)

Losst -0.063 -0.063 0.013 0.002 0.015 0.007 (-1.20) (-1.20) (0.12) (0.02) (0.15) (0.07)

Returnt 0.049* 0.050* 0.028 0.037 0.029 0.027 (1.69) (1.69) (0.33) (0.43) (0.34) (0.32)

Returnt-1 0.081*** 0.082*** 0.040 0.043 0.041 0.040 (3.94) (3.94) (0.72) (0.75) (0.73) (0.71)

Return Volatilityt -0.393 -0.393 0.970 0.816 0.938 1.013 (-1.00) (-1.00) (0.87) (0.74) (0.84) (0.90)

Chairman CEOt 0.087*** 0.087*** 0.165** 0.164** 0.165** 0.165** (3.06) (3.06) (2.18) (2.22) (2.19) (2.19)

CEO Aget 0.009 0.009 -0.221 -0.216 -0.219 -0.223 (0.17) (0.17) (-1.36) (-1.37) (-1.35) (-1.38)

ln(CEO Tenure)t 0.040 0.040 -0.041 -0.041 -0.041 -0.043 (1.61) (1.61) (-0.75) (-0.76) (-0.74) (-0.78)

Intercept 5.755*** 5.756*** 5.245*** 4.607*** 5.151*** 5.304*** (31.51) (31.46) (13.14) (9.28) (11.47) (17.47)

Fixed Effects Year and Industry

Year and Industry

Year and Industry

Year and Industry

Year and Industry

Year and Industry

No. of observations 3,198 3,198 368 368 368 368

Adjusted R2 0.587 0.587 0.683 0.687 0.683 0.683 Panel A shows the result of mean difference between EC Fee Disclosure Group and EC Fee Non-disclosure Group. Propensity Score Matching (PSM) analysis is done by using the regression model in Appendix C. In Panel B, t-statistics are reported in parentheses under each estimated coefficient. Standard errors are corrected for heteroskedasticity using the Huber-White robust standard errors clustered by firm. To mitigate any undue influence from outliers all continuous variables are winsorized at the top and bottom one percentile. The symbols *, **, and *** correspond to 10 percent, 5 percent, and 1 percent significance levels for two-tailed t-tests, respectively. The CC

 

41

variable, NEC Service2 is the indicating variable that has 1 if firm is subject to mandatory disclosure of executive compensation consultant fee, 0 otherwise. Please refer to the paper for a detailed explanation of these tests.

 

42

TABLE 5 Impact of Executive Compensation Consultant Fees on CEO Cash and Equity Pay

(1) Full EC Fee

Disclosure (2) Full EC Fee

Disclosure (3) Mandatory EC

Fee Disclosure (4) Mandatory EC

Fee Disclosure Dependent variable ln(Cash Pay)t ln(Equity Pay)t ln(Cash Pay)t ln(Equity Pay)t

ln(EC Fee)t 0.059* 0.409*** 0.033 0.270* (1.95) (2.89) (0.94) (1.95)

ln(Asset)t 0.315*** 0.578*** 0.331*** 0.550*** (13.35) (6.36) (12.91) (6.01)

Leveraget 0.094 -0.196 -0.138 -1.683** (0.62) (-0.26) (-0.76) (-2.32)

Btmt -0.186** -0.910* -0.165 -0.662 (-2.00) (-1.93) (-1.45) (-1.05)

Roat 1.982*** -0.333 2.359*** -0.495 (4.23) (-0.15) (4.61) (-0.17)

Losst -0.300*** -0.558 -0.183** -0.604 (-3.29) (-1.33) (-2.04) (-1.33)

Returnt 0.073 0.114 0.126 0.780** (0.97) (0.33) (1.52) (2.03)

Returnt-1 0.148*** 0.645*** 0.138** 0.123 (2.63) (3.21) (2.37) (0.48)

Return Volatilityt -1.536* -1.285 0.519 4.274 (-1.89) (-0.37) (0.57) (0.96)

Chairman CEOt 0.071 0.349 0.044 0.291 (1.10) (1.18) (0.66) (0.97)

CEO Aget -0.082 -1.196* -0.108 -0.903 (-0.82) (-1.75) (-0.89) (-0.87)

ln(CEO Tenure)t 0.022 -0.148 0.007 -0.196 (0.50) (-0.90) (0.14) (-0.97)

Multiple Consultantst 0.015 0.839*** (0.15) (2.87)

Intercept 4.499*** -0.686 4.595*** 0.754 (12.92) (-0.39) (10.54) (0.38)

Fixed Effects Year and Industry Year and Industry Year and Industry Year and Industry

No. of observations 576 576 368 368 Adjusted R2 0.643 0.353 0.681 0.307

T-statistics are reported in parentheses under each estimated coefficient. Standard errors are corrected for heteroskedasticity using the Huber-White robust standard errors clustered by firm. To mitigate any undue influence from outliers all continuous variables are winsorized at the top and bottom one percentile. The symbols *, **, and *** correspond to 10 percent, 5 percent, and 1 percent significance levels for two-tailed t-tests, respectively. Please refer to the paper for a detailed explanation of these tests.

 

43

TABLE 6 Determinants of Executive Compensation Consulting Fee

(1) Dependent variable ln(EC Fee)t

ln(Assets)t 0.115* (1.68) ln(Employees)t 0.058 (1.08) Roat 0.313 (0.41) Leveraget 0.625** (2.01) Btmt -0.350** (-2.26) Sales Growtht 0.051 (0.27) Board Engagementt 0.490** (2.29) Multiple Consultantst 0.468 (1.61) Committee Independencet 0.660 (1.13) Committee Busyt 0.000 (0.00) ln(Committee Meet)t 0.342*** (2.71) Pay Mixt 0.124 (0.56) Foreignt 0.003 (0.02) ln(Cda Words)t 0.551*** (3.23) Big5 Consultantst 0.073 (0.82) Chairman CEOt 0.122

(1.46)CEO Aget 0.046 (0.31) CEO Ownershipt -3.834** (-2.51) New CEOt 0.222** (2.20) Intercept 2.629 (1.58) Fixed Effects Year and Industry No. of observations 576 Adjusted R2 0.358

T-statistics are reported in parentheses under each estimated coefficient. Standard errors are corrected for heteroskedasticity using the Huber-White robust standard errors clustered by firm. To mitigate any undue influence from outliers all continuous variables are winsorized at the top and bottom one percentile. The symbols *, **, and *** correspond to 10 percent, 5 percent, and 1 percent significance levels for two-tailed t-tests, respectively. Please refer to the paper for a detailed explanation of these tests.

 

44

TABLE 7 Impact of Abnormal Executive Compensation Consultant Fees on CEO Total Pay

(1) Full

EC Fee Disclosure

(2) Full EC Fee

Disclosure

(3) Full EC Fee

Disclosure

(4) Mandatory EC Fee

Disclosure

(5) Mandatory EC Fee

Disclosure

(6) Mandatory EC Fee

Disclosure Dependent variable ln(Total Pay)t ln(Cash Pay)t ln(Equity Pay)t ln(Total Pay)t ln(Cash Pay)t ln(Equity Pay)t

Positive Residualt 0.197** 0.136* 0.249 0.134* 0.205** 0.479* (2.57) (1.84) (0.64) (1.72) (2.36) (1.75)

Negative Residualt 0.012 -0.009 0.167 -0.060 -0.097 -0.242 (0.17) (-0.16) (0.57) (-0.80) (-1.52) (-0.82)

ln(Asset)t 0.432*** 0.326*** 0.674*** 0.422*** 0.332*** 0.590*** (18.72) (14.23) (7.51) (13.98) (13.14) (5.83)

Leveraget -0.358* 0.156 0.060 -0.494** -0.071 -1.380* (-1.92) (1.01) (0.08) (-2.12) (-0.41) (-1.84)

Btmt -0.651*** -0.209** -1.085** -0.493*** -0.164 -0.700 (-6.10) (-2.31) (-2.28) (-4.47) (-1.55) (-1.10)

Roat 0.143 2.044*** -0.027 1.146** 2.349*** -0.404 (0.24) (4.42) (-0.01) (2.14) (4.83) (-0.14)

Losst -0.122 -0.301*** -0.507 -0.003 -0.200** -0.621 (-1.08) (-3.29) (-1.17) (-0.03) (-2.27) (-1.33)

Returnt -0.045 0.063 0.063 0.022 0.112 0.719* (-0.58) (0.85) (0.18) (0.25) (1.45) (1.85)

Return t-1 0.139** 0.141** 0.615*** 0.032 0.124** 0.081 (2.50) (2.56) (3.19) (0.56) (2.17) (0.33)

Return Volatilityt -1.063 -1.491* -0.899 0.945 0.532 4.807 (-1.26) (-1.85) (-0.26) (0.85) (0.60) (1.07)

Chairman CEOt 0.166** 0.076 0.388 0.163** 0.042 0.286 (2.33) (1.17) (1.28) (2.19) (0.63) (0.93)

CEO Aget -0.219** -0.087 -1.234* -0.222 -0.111 -0.928 (-2.09) (-0.88) (-1.74) (-1.39) (-0.90) (-0.88)

ln(CEO Tenure)t -0.015 0.017 -0.191 -0.039 0.012 -0.186 (-0.32) (0.38) (-1.12) (-0.72) (0.22) (-0.92)

Multiple Consultantst 0.258** 0.025 0.904*** (2.10) (0.25) (3.23)

Intercept 5.573*** 5.075*** 3.294*** 5.325*** 4.937*** 3.455*** (22.24) (25.74) (3.74) (17.91) (22.22) (3.62)

Fixed Effects Year and Industry

Year and Industry

Year and Industry

Year and Industry

Year and Industry

Year and Industry

No. of observations 576 576 576 368 368 368

Adjusted R2 0.659 0.642 0.338 0.684 0.686 0.299 T-statistics are reported in parentheses under each estimated coefficient. Standard errors are corrected for heteroskedasticity using the Huber-White robust standard errors clustered by firm. To mitigate any undue influence from outliers all continuous variables are winsorized at the top and bottom one percentile. The symbols *, **, and *** correspond to 10 percent, 5 percent, and 1 percent significance levels for two-tailed t-tests, respectively. Residual is actual ln(EC Fee) minus expected ln(EC Fee) estimated in Equation (2). Positive Residual is the residual value (Residual) which has a positive value and 0 otherwise. Negative Residual is the residual value which has a negative value (Residual) and 0 otherwise. Please refer to the paper for a detailed explanation of these tests.