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1
Managerial pay disparity and firm outcomes
Research proposal for fulfilment of the requirements for Doctor
of Philosophy in Finance
School of Economics and Finance
Massey University
Xutang Liu
July 2020
Supervisors
Prof. Martin Young
Dr. Jing Liao
2
Table of Contents
Managerial pay disparity and firm outcomes................................................................. 1
1. Introduction ................................................................................................................ 5
1.1 CEO pay disparity: A brief overview ................................................................... 6
1.2. Why Chinese studies? ......................................................................................... 8
1.3 Overview of the three essays ................................................................................ 9
1.3.1 Essay one: CEO pay disparity and firm performance: New evidence from
China ..................................................................................................................... 10
1.3.2 Essay two: Managerial pay disparity and earnings management: Evidence
from China ............................................................................................................ 12
1.3.3 Essay three: Managerial pay disparity and firm decision-making and output:
Asia-Pacific study ................................................................................................. 13
1.4 Structure of the research proposal ...................................................................... 14
2. Literature review ...................................................................................................... 14
2.1 Rank-order tournament theory ........................................................................... 14
2.2 Managerial power theory ................................................................................... 15
2.3 CEO pay disparity .............................................................................................. 16
2.3.1 Measurement one: CEO pay gap ................................................................. 17
2.3.2 Measurement two: CEO Pay Slice (CPS).................................................... 18
2.4 CEO pay disparity and firm performance .......................................................... 19
2.4.1 CEO pay gap and firm performance ............................................................ 19
2.4.2 CEO pay slice (CPS) and firm performance ............................................... 21
2.5 CEO pay disparity and earnings management ................................................... 23
2.6 CEO pay disparity and firm behaviours and output ........................................... 25
3. Essay one ................................................................................................................. 28
3.1 Introduction ........................................................................................................ 28
3.2 Literature review and hypothesis development .................................................. 31
3.2.1 CEO pay disparity ....................................................................................... 31
3.2.2 Rank-order tournament theory ..................................................................... 31
3.2.3 Managerial power theory ............................................................................. 32
3.3 Sample and variable construction ...................................................................... 33
3.3.1 Data .............................................................................................................. 33
3
3.3.2 Variable construction ................................................................................... 34
3.3.3 Descriptive Statistics and correlation matrix ............................................... 35
3.3.4 Empirical analysis........................................................................................ 37
3.3.5 CEO pay disparity and firm performance, sub-sample analysis ................. 40
3.4 Conclusion .......................................................................................................... 44
3.5 Appendix ............................................................................................................ 46
Appendix A: Variable definitions ......................................................................... 46
3.6 Tables ................................................................................................................. 47
Table 1: Summary statistics .................................................................................. 47
Table 2: Time trend .............................................................................................. 48
Table 3: Correlation matrix .................................................................................. 50
Table 4: CEO pay disparity and firm performance. ............................................. 51
Table 5: Determinants of CEO pay disparity. ...................................................... 52
Table 6: CEO pay disparity and firm performance, PSM approach analysis. ...... 53
Table 7: CEO pay disparity and firm performance: SOEs and private firms ....... 55
Table 8: CEO pay disparity and firm performance: Pre and Post “pay ceiling”
regulation period ................................................................................................... 57
Table 9: CEO pay disparity and firm performance: does industry concentration
matter .................................................................................................................... 60
Table 10: CEO pay disparity and firm performance: does non-CEO executives’
age matter ............................................................................................................. 62
Table 11: CEO pay disparity and firm performance: does non-CEO executives’
gender matter ........................................................................................................ 63
4. Essay two ................................................................................................................. 64
4.1 Introduction ........................................................................................................ 64
4.2 Literature review and hypothesis development .................................................. 66
4.3 Sample and variable construction ...................................................................... 68
4.3.1 Data .............................................................................................................. 68
4.3.2 Variable construction ................................................................................... 68
4.3.3 Descriptive Statistics and correlation matrix ............................................... 70
4.3.4 Empirical analysis........................................................................................ 71
4.4 Future analysis.................................................................................................... 72
4.5 Appendix ............................................................................................................ 73
4
Appendix A: Variable definitions ......................................................................... 73
4.6 Tables ................................................................................................................. 74
Table 1: Summary statistics .................................................................................. 74
Table 2: Time trend .............................................................................................. 75
Table 3: Correlation matrix .................................................................................. 76
Table 4: Managerial pay disparity and accrual-based earnings management. ..... 77
5. Essay three ............................................................................................................... 80
5.1 Introduction ........................................................................................................ 80
5.2 Literature review and hypothesis development .................................................. 82
6. Proposed timeline for the completion of Dissertation ............................................. 84
7. References ................................................................................................................ 85
5
1. Introduction
The goal of this thesis is to investigate whether and how managerial pay disparity
affects firm outcomes. Managerial pay disparity has become one of the corporate
governance topics that attract wide attention in recent years. The three essays in this
thesis will have a focus on managerial pay disparity to examine whether it can be served
as an effective corporate governance mechanism for improved firm outcomes. Besides,
the executive gender, age, tenure, and other corporate governance factors are addressed
in this thesis. My study will be useful for policy-makers to ensure that appropriate
regulations are put in place to improve corporate governance.
The top management team is responsible for a firm’s day-to-day operations and
profitability. Besides, the nature of executive work requires a high degree of task
interdependence (Siegel & Hambrick, 2005). As the key to the corporate remuneration
structure, managerial pay disparity plays an important role in the inner workings of the
top management team (Bebchuk, Cremers, & Peyer, 2011). Thus, a proper managerial
pay disparity is essential to incentivise senior executives to make best efforts and
improve firm outcomes.
The first two essays investigate the effect of managerial pay disparity on firm
performance and earnings management, respectively. The main focus is chief executive
officer (CEO) pay disparity defined as the compensation differential between the CEO
and other top executives. According to the rank-order tournament theory, a larger CEO
pay disparity is beneficial to firm outcomes because it provides non-CEO executives
with tournament incentives to make them work harder and to invest in firm specific
human capital (Lazear & Rosen, 1981). Therefore, a large pay disparity helps build a
large pool of skilled internal candidates to compete for the CEO position (Chen, Huang,
& Wei, 2013). However, the managerial power theory argues that a large CEO pay
disparity harms firm performance since it reflects the relative power and dominance of
the CEO within the top management team and relative to the board of directors
(Bebchuk et al., 2011; Chen et al., 2013). That is, a large CEO pay disparity indicates
6
an entrenched CEO (Chen et al., 2013). It is important to investigate whether and how
CEO pay disparity can serve as a governance mechanism to improve corporate
governance structure and firm outcomes. According to the upper echelons theory
(Hambrick & Mason, 1984), the objective and psychological characteristics of top
management team drive their strategic choices and impact firm decision-making; thus,
top executives’ personal characteristics such as age, gender, education, tenure, and
politically connection will be investigated as well in this thesis.
China, as the biggest emerging market, provides a unique setting to investigate the
influence of CEO pay disparity on firm outcomes. It is argued that China’s corporate
governance system is poor, and the outside investor protection is insufficient (Firth,
Fung, & Rui, 2006; Hu, Pan, & Tian, 2013). Stakeholders of public listed firms could
prefer to believe the internal monitoring mechanisms such as setting managerial
compensation, rather than the external mechanisms (Firth et al., 2006; Murphy, 1999).
Thus, it is of great importance to investigate whether managerial pay disparity plays a
role. By conducting the studies using China data (essay one and two), the thesis makes
a further contribution to the relevant literature by providing evidence from the largest
emerging economy. The proposed research (essay three) studies the efficiency of
managerial pay disparity in Asian markets, e.g. China, Japan, South Korea, and
Singapore, therefore addressing how culture and legal systems affect the roles of CEO
pay disparity which is still a research challenge in the relevant literature.
1.1 CEO pay disparity: A brief overview
Compensation policy is one of the most important factors that affect organisational
success (Jensen & Murphy, 1990). The compensation structure of a top management
team has received considerable attention from academics and practitioners alike.
Particularly, managerial pay disparity is an essential aspect of the corporate
remuneration structure. CEO pay disparity, defined as the pay differential between CEO
and other top executives, plays an important role in the inner workings of the top
7
management team and influences firm performance and behaviours significantly
(Bebchuk et al., 2011; Kale, Reis, & Venkateswaran, 2009; Kini & Williams, 2012).
There are two competing theories on the role of CEO pay disparity, e.g., the rank-order
tournament theory and managerial power theory. According to the tournament theory,
a large CEO pay gap provides strong tournament incentives for non-CEO executives to
make great efforts to increase the likelihood of promotion to the next CEO (Lazear &
Rosen, 1981). Since the rank-order tournaments are schemes of relative performance
evaluation and the managerial skills are hard to measure, a large pay gap provides non-
CEO executives with effective promotion-based tournament incentives for improved
enterprise performance. For example, Kale et al. (2009) document that the pay gap
between the CEO and other top executives is positively associated with firm value and
performance. With a larger pay gap, non-CEO executives have an increased motivation
to perform for the advancement chances of becoming the next CEO (Goel & Thakor,
2008; Ramakrishan & Thakor, 1991). It is consistent with the finding of Lee, Lev, &
Yeo (2008) that a larger executive pay dispersion leads to higher firm performance.
Besides, a large CEO pay dispersion provides a large tournament prize for non-CEO
executives that promotes aggressive and competitive behaviours (Siegel & Hambrick,
2005), such as taking riskier projects (Kini & Williams, 2012) or engaging in more
earnings manipulation (Park, 2017). Therefore, the tournament theory suggests a
positive association between CEO pay disparity and corporate aggressive behaviours.
Managerial power is defined as the ability of an individual manager to exert his or her
will to corporate decision-making (Finkelstein, 1992; Hickson, Hinings, Lee, Schneck,
& Pennings, 1971; Pfeffer, 1981). According to the managerial power theory, a larger
pay disparity between the CEO and other top executives reflects the CEOs' relative
power and dominance in influencing the remuneration decisions made by the
compensation committee of the board (Bebchuk & Fried, 2003; Bebchuk, Fried, &
Walker, 2002). The larger the compensation gap, the higher the motivation of CEOs to
protect both their financial wealth and career security. Hence, powerful CEOs are more
likely to design pay packages to pursue self-interests rather than shareholders’ interests.
8
This, in turn, leads to more agency problems that reduce corporate performance and
value (Adams, Almeida, & Ferreira, 2005; Bebchuk et al., 2011; Bebchuk & Fried,
2003). For instance, Bebchuk et al. (2011) find that a large CEO pay disparity is
associated with lower firm value and accounting performance.
With a larger pay dispersion, CEOs are more incentivised to demand and protect their
high compensation through relatively strong power and influence within the top
management team and relative to the board of directors. Thus, a large pay dispersion
suggests that the powerful CEO is entrenched so that more agency issues may happen
during his/her tenure. As a result, the managerial power theory proposes a negative
relationship between CEO pay disparity and firm performance.
1.2. Why Chinese studies?
Existing studies have examined the pay disparity and its relationship with corporate
performance and value, but controversy remains in this line of research. Most of the
existing studies in this area are conducted utilising data from Western industrialised
societies, and it may not be appropriate to draw general conclusions about the role of
executive pay disparity basing on existing studies.
China provides an interesting setting to examine such a research topic due to its unique
institutional mechanisms. Since the disclose of individual compensation for senior
executives (including CEO, CFO, Chairman, and other executives) in 2005, reports and
supervision by the news media have made the issue of compensation a focus of attention
from all walks of life in China. The corporate governance system is relatively poor and
the protection for investors and transactions is weak in the Chinese market (Allen, Qian,
& Qian, 2005; Feng, Ge, Luo, & Shevlin, 2011). It is very common for top management
teams to obtain extremely high and unreasonable pay packages in listed firms. Under
this circumstance, increased salary payments and widened compensation gaps have
attracted substantial public attention and caused significant controversy in society. The
Chinese central government has introduced a series of regulations to regulate the
9
compensation of top executives to mitigate the strong social complaints about pay
inequality.
In particular, the Chinese government put forward the “pay ceiling” regulation for top
executives in central state-owned enterprises (SOEs) in 20141 and it was officially
implemented from January 1, 2015. The regulation served primarily to set a cap on the
ratio of total executive pay to the average salary of employees to limit excessive
executive compensation. Specifically, the compensation structure includes basic annual
salary, performance-based annual salary, and term incentive bonus. All these three
components of executive pay are restricted by this regulation respectively. The basic
annual salary is at the maximum twice as much as the average annual wage of non-
executive employees in the central SOEs, calculated basing on the previous year’s
payments. The annual salary for performance shall not exceed twice as the basic annual
salary. The term incentive bonus within an executive’s tenure should not exceed 30%
of the total annual salary. After putting in place a ceiling, the executive-worker pay
ratio is expected to trim down to about eight. The local SOEs are required by the central
government to follow this executive pay ceiling regulation.
1.3 Overview of the three essays
My first two essays focus on the effects of managerial pay disparity on firm
performance and earnings management in China, respectively. Prior studies on top
management pay disparity primarily focus on the United States market. The Chinese
government announced the “Reform Scheme on Executive Compensation of the
Central State-Owned Enterprises” in 2015, which provides a unique natural shock to
explore whether the narrowed inequality between the CEO and other top executive pay
will have a significant impact on firm performance and earnings management. The
robustness checks such as subsample analysis will further be done to explore the
efficiency of CEO pay disparity in depth. The third essay will conduct a cross-country
study to examine whether the effect of managerial pay disparity on firm decision-
1 http://www.china.org.cn/china/2014-08/28/content_33374610.htm
10
making and output varies across Asian countries such as China, Japan, South Korea,
and Singapore.
1.3.1 Essay one: CEO pay disparity and firm performance: New evidence from
China
My first essay is on the impact of CEO pay disparity on firm performance in China.
The main focus is CEO pay disparity that indicates the pay differential between the
CEO and other top executives. Kale et al. (2009) highlight that a large CEO pay gap
provides non-CEO executives with tournament incentives to work harder and improve
firm performance. Under this argument, firms with a large CEO pay disparity would be
related to better performance. Bebchuk et al. (2011) document that a large CEO pay
disparity reflects a powerful and entrenched CEO that leads to worse firm performance.
Due to the inconclusive evidence, the first essay investigates the impact of CEO pay
disparity on firm performance in China’s listed firms. Particularly, the executive pay
ceiling regulation will be employed as the exogenous shock to examine the relationship.
The literature on the CEO pay disparity in China is very sparse and very few researches
focuses on the salary reform in 2015. My research examines the effect of CEO pay
disparity on firm performance in China before and after the 2015 regulatory change.
Moreover, subsample analysis is conducted to investigate whether the positive relation
between CEO pay disparity and firm performance is robust.
CEO pay disparity is addressed through two approaches. Following Kale et al. (2009),
the CEO pay gap (CPG) between the CEO and other top executives is used as the first
measure. CEO pay slice (CPS) measured as the ratio of CEO pay to the total
compensation of the top five executives is utilised as the second approach following
(Bebchuk et al., 2011). Using a sample of executives’ cash compensation data from the
CSMAR database for the period 2005 to 2017, I first find that CPG is associated with
better corporate performance measured as return on assets (ROA) and return on equity
(ROE). This finding is in line with the rank-order tournament theory. Moreover, CPS
also has a positive relationship with firm performance. This result does not support the
11
managerial power theory but the tournament theory. The significantly and positively
relationship remains robust after addressing the endogeneity concerns by employing
the propensity score matching method. Hence, a large CEO pay disparity as a corporate
governance mechanism plays a positive role in firm performance in China’s listed firms.
In addition, the subsample analysis is conducted to examine whether the positive
influence of CEO pay disparity on firm performance is robust. CPG is used to present
the CEO pay disparity in sub-samples since the CPG is a better measurement than CPS
to capture the tournament effects based on previous literature. I first split the full sample
into subsamples of state-owned enterprises (SOEs) and private firms basing the
ultimate controller of sample firms. It is found that the positive tournament effects apply
to both SOEs and private firms. Besides, the 2015 pay ceiling regulation could drive
the relationship between CEO pay disparity and firm performance in SOEs. By dividing
the SOEs sample into pre-regulation (before 2015) and post-regulation (after 2015)
subsamples, I find that the CPG is positively associated with firm performance (ROA)
in both the pre and post regulation periods. It indicates that the tournament effects
remain robust when addressing the influence of the regulation. However, the effect of
CPG is not significant in the post-regulation period in SOEs directly controlled by
government bureaus who could be more sensitive to the pay ceiling regulation.
Therefore, the “pay ceiling” regulation decreases the CEO pay disparity that in turn
reduces the tournament incentives of non-CEO executives in SOEs directly controlled
by government bureaus.
Further, I examine the sensitivity of non-CEO executives to tournament incentives. The
tournament effects in SOEs are subject to industry-concentration measured by
Herfindahl-Hirschman Index (HHI). In highly concentrated industries (high HHI), there
is no significant relation between CPG and ROA. Within the SOEs, the non-CEO
executives’ tournament incentives may not play a role in highly concentrated industries
since their current firms have the monopoly power and outside career markets are very
limited. I further find that the CPG does not play a role in firms where the non-CEO
executives are too young or too old because their work incentives are driven by their
12
age. For example, the ambition of older top executives to a higher position is limited,
and younger executives could be more active in job-hopping that can provide them with
higher salaries and better positions. Finally, I examine whether the executives’ gender
matters for the tournament effects. It is found that the positive influence of CPG on
ROA is insignificant if the female ratio within non-CEO executives is greater than 50%.
Female executives are more risk-averse than males (Byrnes, Miller, & Schafer, 1999;
Charness & Gneezy, 2012), thus, leading to reduced work incentives for promotion to
higher position.
Overall, the tournament theory is applied to China’s listed firms, and a large CEO pay
disparity as a useful governance mechanism is beneficial to firm performance. It is
obviously essential to address social fairness, but the policy-makers should consider
keeping enough tournament incentives for top executives to keep them work harder.
Simply limiting the compensation of top executives in SOEs may not necessarily
improve firm performance.
1.3.2 Essay two: Managerial pay disparity and earnings management: Evidence
from China
My second essay is on the impact of managerial pay disparity on earnings management
in China. The pay disparity between the CEO and other top executives is the focus of
this study. In particular, chief financial officers (CFOs) could play an important role in
earnings manipulation since they have the primary responsibility in overseeing the
firms’ overall financial reporting (Geiger & North, 2006). Hence, the pay gap between
the CEO and the CFO is an important focus as well. Earnings management includes
accrual-based earnings management and real earnings management, and both are
evidence of weak corporate governance. Given the fact that earnings management
activities are common in China (Firth et al., 2006; Liu & Lu, 2007), it is worthwhile to
examine whether and how managerial pay disparity influence earnings manipulation.
I first examine the relationship between the managerial pay disparity and accrual-based
earnings management. My preliminary results show that the pay gap between the CEO
13
and the CFO is negatively associated with accrual-based earnings management. This
finding indicates that the firm with a large pay gap between the CEO and the CFO is
less likely to manipulate reported earnings. It is argued that CFOs bear more legal costs
and higher loss of reputation and wealth than that of CEOs in manipulating earnings
(Feng et al., 2011; Mian, 2001). In firms with a large managerial pay gap, CFOs are
motivated by large tournament incentives to increase their chances of advancing to the
CEO position. Given the fact that CFOs would be exposed to potentially high loss in
both career and wealth from accounting manipulations, they could be more
conservative and cautious in manipulating reported earnings. Therefore, if CFOs aim
for an increased chance of promotion, they would be less likely to conduct accrual-
based earnings management.
I also find that the pay gap between the CEO and other top executives is not
significantly correlated with accrual-based earnings management. Jiang, Petroni, &
Wang (2010) document that CEOs or CFOs are more likely to have professional
financial and accounting knowledge compared to other top executives. Hence, non-
CEO executives could face higher costs of managing accruals than CFOs (Park, 2017).
Given the fact that most of the top managers carry out and oversee the firms’ daily
operational decisions, they could have a stronger influence on real earnings
management than accrual-based earnings management. I will examine the impact of
managerial pay disparity on real earnings management. Overall, the tournament
incentives make CFOs more conservative in engaging in accrual-based earnings
management. The large managerial pay disparity could be served as a useful
governance mechanism to improve corporate governance for Chinese listed firms.
1.3.3 Essay three: Managerial pay disparity and firm decision-making and output:
Asia-Pacific study
My third essay will investigate the efficiency of managerial pay disparity in Asian
markets, e.g. China, Japan, South Korea, and Singapore. Most of the existing studies
examine the influence of managerial pay disparity in Western industrialised societies,
14
especially the US market. Given the fact that the legal system and institution setting
vary across countries, the conclusion generated from prior literature may not apply to
other economies. For instance, China, Korea, and Japan belong to the Civil Law System,
while Singapore belongs to the Common Law System. Moreover, the literature
document that corporate governance and investor protection are weak in China and
Korea, whereas in Japan and Singapore they are good (ASFRC, 2017; Jiang et al., 2010).
Thus, it is expected that the role of managerial pay disparity is subject to the legal
system and institution setting. Al-Najjar, Ding, & Hussainey (2016) find that CPS
reflects managerial talents rather than managerial power in UK listed firms. CEOs with
outstanding abilities and skills can be rewarded relatively higher salaries within the top
management team. It is because the UK public listed firms developed strengthened
internal governance and established relative independent remuneration committees.
Therefore, a cross-economy study can address how culture and legal systems affect the
role of managerial pay disparity, which is still a research challenge in the relevant
literature.
1.4 Structure of the research proposal
The reminder of this research proposal is structured as follows. Section 2 is the literature
review of the managerial pay disparity and firm outcomes. Section 3, 4 and 5 present
the research details of essay one, essay two and essay three, respectively. Section 6
shows the proposed timeline for the Ph.D. completion. Section 7 presents the references.
2. Literature review
2.1 Rank-order tournament theory
Rank-order tournament theory, first proposed by Lazear & Rosen (1981), indicates that
large pay gaps provide strong tournament incentives for workers to make greater effort
to garner higher positions. The level of employee compensation stepped increase with
the promotion of positions because the wage differences are based not on marginal
productivity but instead based on relative differences between the individuals. Thus,
15
employees can be rewarded by their rank in an organization, suggesting that the higher
the rank, the larger the salaries. However, the tournament prize is not always the same,
since it varies from the level of the pay gap and the number of tournament participants.
The large pay disparity and the number of top executives both lead to increased
tournament prize (Eriksson, 1999; Lin, Shen, & Su, 2009; Lin, Yeh, & Shih, 2013).
According to that, a larger CEO pay gap will provide the non-CEO executives with
more incentives to work harder to increase their chances of becoming the next CEO
(Goel & Thakor, 2008; Haß, Müller, & Vergauwe, 2015; Kini & Williams, 2012;
Ramakrishan & Thakor, 1991). Since the rank-order tournaments are schemes of
relative performance evaluation and the managerial skills are hard to quantify,
executives’ compensation depends on their performance ranking rather than objective
performance itself. Thus, top executives will only be able to become the best relative
performer and receive the tournament prize by working harder to increase their
perceived outputs, and ultimately improve firm performance. This viewpoint supports
that a large CEO pay gap provides goals for top executives and incentivises to work
hard, which is beneficial to corporate performance (Eriksson, 1999; Hu et al., 2013;
Kale et al., 2009; Main, O'Reilly III, & Wade, 1993).
Overall, tournament theory states that a larger pay gap is effective as it provides
appropriate incentives for non-CEO executives to exert effort so that they may one day
be promoted to CEO of a company. Based upon the rank-order tournament theory, it is
expected that the CEO pay gap has a positive influence on corporate performance and
behaviours.
2.2 Managerial power theory
Managerial power is defined as the ability of an individual manager to exert his or her
will to corporate decision-making (Finkelstein, 1992; Hickson et al., 1971; Pfeffer,
1981). A powerful CEO can influence firm decision-making, such as exert his or her
desires on the remuneration decisions made by the compensation committee of the
board (Bebchuk et al., 2011; Finkelstein, 1992; Lambert, Larcker, & Weigelt, 1993).
16
Thus, CEOs can design their own pay packages to pursue high salary for private
benefits rather than shareholders’ interests. According to the managerial power
perspective, large CEO pay and pay disparity reflect the relatively high bargaining
power of a CEO within the top management team and relative to board of directors
(Bebchuk & Fried, 2003; Chen et al., 2013; Dai, Kong, & Xu, 2017). Therefore, a large
pay dispersion between the CEO and other top executives indicates the substantial
impact of a powerful CEO on the compensation scheme. The powerful CEOs might be
entrenched, which lead to more agency problems and corporate value might decline
during their tenure (Adams et al., 2005; Bebchuk et al., 2011; Bebchuk & Fried, 2003).
As a result, it is proposed that the CEO pay disparity has negative influences on
corporate performance and behaviours.
2.3 CEO pay disparity
CEO compensation and the gap between the CEO and other top executives
remuneration reported and supervised by the news media has been a focus of attention
from the public and society recently. The CEO pay disparity indicates the pay
differential between the CEO and other top executives. It reflects the promotion-based
tournament incentives for non-CEO executives and the managerial power of CEOs. Lin,
Shen, & Su (2009) document several characteristics of tournament theory on executive
compensation structures. First, an executive’s pay increases with the move up of his
rank. Second, the pay disparity between the first and second tire executives is the largest
within the top executive team. Third, a greater number of tournament participants are
associated with increased pay disparity, which is in line with Eriksson (1999) that the
number of participants is positively related to the tournament prize. Based on the
previous literature, there are two main measurements which include CEO pay gap
employed by Kale et al. (2009) and CEO pay slice (CPS) introduced by Bebchuk et al.
(2011). In particular, the CEO pay gap is measured as the natural logarithm of the
difference between the CEO's total compensation and the median total compensation
of all other executives in the top management team. It indicates that a large pay gap can
provide promotion-based tournament incentives for non-CEO executives. The larger
17
the CEO pay gap, the higher the efforts executives will put into work. In addition, the
CPS is the ratio of CEO pay to the total compensation of the top five executives within
the top management team. It reflects the CEO managerial power relative to the top
management team and board of directors. The larger the CPS, the more influence of
CEOs on firm decision-making.
2.3.1 Measurement one: CEO pay gap
Promotion-based tournament incentives are defined as the natural logarithm of the
difference between the CEO's total compensation and the median total compensation
of all other executives in the top management team (Kale et al., 2009). According to
the rank-order tournament theory, with a larger pay gap, the non-CEO executives have
an increased motivation to make more effort to increase their chances of promotion to
the CEO position (Lin et al., 2013; Ridge, Aime, & White, 2015). High-performing
executives with considerable managerial potential are more likely to win promotion to
the CEO position and receive commensurate pay, thereby improving firm value and
performance (Hu et al., 2013). Kale et al. (2009) document a significantly positive
relation between CEO pay gap and firm performance in US firms. This evidence
supports the rank-order tournament theory and demonstrates the effectiveness of
promotion-based tournament incentives for non-CEO executives. In particular, the
positive tournament incentive effect is more pronounced if the incumbent CEO is close
to retirement. On the contrary, the tournament incentive effect is weaker if the firm just
hired a new CEO. These findings are consistent with Ridge et al. (2015) that the
tournament incentives generated from large CEO pay gap are positively associated with
firm performance. Moreover, the effects of CEO pay gap apply to corporate behaviours,
such as firm risk-taking. For example, Kini & Williams (2012) find that a larger CEO
pay gap results in greater firm risk-taking. This finding is driven by the tournament
incentives of top executives to increase their chance of becoming the next CEO.
Therefore, senior executives prefer to undertake riskier projects and implement riskier
policies, thereby increasing firm risks (Goel & Thakor, 2008). Overall, existing
18
literature indicates that the CEO pay gap as the measurement of the promotion-based
tournament incentives influences corporate outcomes and behaviours.
2.3.2 Measurement two: CEO Pay Slice (CPS)
Bebchuk et al. (2011) introduce the CEO Pay Slice (CPS) to proxy for the relative
importance and managerial power of a CEO. CPS is defined as the fraction of aggregate
compensation of the top five members of the executive team that is captured by the
CEO. According to the managerial power theory, power is the capability of top
executives to impact the remuneration decisions made by the board of directors or the
compensation committee of the board (Finkelstein, 1992; Lambert et al., 1993). Senior
managers can pursue their self-interest to obtain high compensation (Grabke-Rundell
& Gomez-Mejia, 2002). Therefore, a larger pay gap between the CEO and other top
executives signals the relative power and dominance of the CEOs in demanding higher
remuneration. CPS is widely employed by the literature to examine its relation to firm
performance and behaviours. Using a sample of US-listed firms from 1993 to 2004,
Bebchuk et al. (2011) illustrate that a higher CPS is related to lower firm performance
measured by industry-adjusted Tobin's Q. It is also found that CPS is correlated with a
lower performance-CEO turnover sensitivity. Moreover, Chen et al. (2013) document
a significantly positive relation between CPS and the cost of equity capital. These
findings are in line with the notion that powerful CEOs are entrenched and are
associated with more severe agency problems (Bebchuk et al., 2011). Therefore, a
larger CPS indicates that the CEO plays a more dominant role among top executive
team (Jiraporn, Chintrakarn, & Liu, 2012).
In addition, the CPS as the measurement of CEO pay disparity reflects the tournament
incentives. For instance, Hu et al. (2013) find that the CEO pay gap and CPS are both
significantly and positively associated with firm performance in China. This evidence
supports the promotion-based tournament incentives for top executives. Overall, the
CPS mainly represents the CEO power and dominance within the top management team.
19
Thus, CPS as a governance mechanism has significant implications for firm behaviours
and outcomes.
2.4 CEO pay disparity and firm performance
2.4.1 CEO pay gap and firm performance
The rank-order tournament theory illustrates that a larger CEO pay disparity will
provide higher promotion-based tournament incentives for non-CEO executives,
leading to greater efforts on the part of non-CEO executives and increased firm
performance (Lazear & Rosen, 1981). The literature documents the importance of the
tournament pay structure and tournament incentives to the management team members.
Ehrenberg & Bognanno (1990) analyse the effect of the compensation structures in
professional sports tournaments on team outcomes. It is found that tournament-type pay
structures can lead to better players’ performance. This kind of compensation system is
suitable for certain groups of workers, such as firm executives, sport-team members,
and college professors. This finding is consistent with Becker & Huselid (1992) that
tournament compensation systems have a positive influence on individual performance.
What’s more, Eriksson (1999) argues that managerial compensation differentials
provide effective promotion-based incentives for senior managers to enhance firm
performance. Lee et al. (2008) support the tournament theory by showing a positive
association between pay dispersion within the management team and corporate
performance. Kale et al. (2009), investigating the US-listed firms from 1993 to 2004,
document that the compensation gap between the CEO and the next level of executives
has a significantly positive relation to firm value and accounting performance. In
particular, the positive relation is more pronounced if the incumbent CEO is nearing
retirement, and this relation is weaker if the CEO is new. Overall, empirical evidences
generated in developed economies such as Europe and the US indicate that the
tournament-type compensation structures are beneficial to both individuals and firm
performance.
20
Additionally, literature provides evidence of the positive tournament-incentives effect
in emerging markets. Hu et al. (2013) examine the relationship between the CEO pay
disparity and firm performance in China, the largest emerging economy. Consistent
with the rank-order tournament theory, CEO pay disparity provides tournament
incentives to non-CEO executives and is associated with better firm performance.
Moreover, the positive tournament-incentive effect on firm performance is subject to
firm ultimate controller and CEO political status. For example, this positive relation is
weaker in firms controlled by the government than in private firms, due to the non-
economic goals of SOEs such as maintaining social fairness (Jensen, 2001). CEO
political connection also has an incremental effect on the effectiveness of tournament
incentives. Faccio, Masulis, & McConnell (2006) find that CEOs with political
connections have the privilege to access key resources managed and provided by the
government (e.g. bank loans and favourable tax treatment) and firms benefit from the
resources. In this case, the compensation of political connected CEOs is less likely to
be fully decided by firm performance, thereby leading to lower pay-performance
sensitivity (Chen, Li, Su, & Sun, 2011).
Importantly, the positive tournament incentives effect on corporate performance is not
“one size fits all”. The effectiveness of tournament theory might be subject to the
institutional background, specific industry, and individual firm's cooperation
atmosphere. Moreover, Lin et al. (2013) advocate that a large executive pay gap is
beneficial to corporate performance in Taiwanese public-traded firms. The relation is
more pronounced in non-high-technology firms in which a large pay gap is a useful
motivation mechanism to improve executives’ work efforts and firm performance. The
positive tournament-incentives effect is not valid in high-technology companies
because a larger pay disparity might reduce the efficiency of collaboration and
coordination within the top management team. This evidence supports the finding of
Siegel & Hambrick (2005) that pay disparity within the senior executive team is
negatively correlated with corporate performance in high-technology firms since
collaboration is diminished when large pay disparities exist. So, the large pay dispersion
21
within the top management team is more detrimental to high-technology firms
compared with non-high-technology firms. Using a cross-country sample, Burns,
Minnick, & Starks (2017) investigate the CEO tournament structure and the results
support the tournament incentives. The pay difference between the CEO and other top
executives is positively correlated with firm value after controlling for endogeneity. In
addition, the tournament effect varies from firm and country culture characteristics.
Overall, a large CEO pay gap shows a positive influence on firm performance in both
developed and emerging markets.
2.4.2 CEO pay slice (CPS) and firm performance
According to the managerial power theory, a large pay disparity reflects the power and
dominance of the CEO in the firm's pay-setting process (Bebchuk et al., 2002). The
powerful CEOs might influence corporate decision-making through relative strong
power to pursue high salary for their self-benefits. It leads to more severe agency
problems that might damage the shareholder’s interests and firm value (Adams et al.,
2005; Bebchuk et al., 2011; Landier, Sauvagnat, Sraer, & Thesmar, 2012). Bebchuk et
al. (2011) investigate the relationship between CPS and firm performance for US-listed
firms during the period 1993 to 2004. CPS is employed to measure CEO pay disparity,
which is calculated as the ratio of the total compensation to the top five executives that
goes to the CEO. It is found that larger executive pay dispersion is associated with
lower firm value and accounting profitability. In particular, firms with higher CPS are
negatively correlated with stock returns after the announcements of acquisition
decisions. CPS is also related to lower CEO turnover-performance sensitivity,
reflecting the CEO dominance within the top management team. These results indicate
that CEOs in high CPS firms have more power and influence over firm decision-making,
in which leads to decreased corporate performance. Therefore, a high CPS reflects the
potential rent-seeking by the CEO and can be viewed as an agency problem. Similarly,
Jiraporn et al. (2012) adopt CPS as the measurement of CEO power and demonstrate a
consistent finding that powerful CEOs are related to poor firm performance and
outcomes. Bugeja, Matolcsy, & Spiropoulos (2017) argue that excess CPS has a
22
negative effect on firm performance, indicating the possible agency problems. Han,
Nanda, & Silveri (2016) examine the relationship between CEO power measured as
CPS and firm performance. It is found that firms with higher CPS are significantly
related to worse performance under industrywide-downturns pressure. The findings
also support that CPS is a useful indicator of CEO dominance, and higher CPS leads to
worse corporate performance. Correa & Lel (2016) examine the influences of CEO pay
dispersion on firm valuation by using a large sample of firms from 38 countries during
the period of 2001 to 2012. Say on pay (SoP)2 laws as a quasi-exogenous shock narrow
the pay inequality between the CEO and other top executives. Compared with the firms
without passing the SoP laws, the value of the firms that passed the SoP laws
significantly enhanced. The results are in line with the findings of Bebchuk et al. (2011)
that high CPS reflects CEO entrenchment that is harmful to firm value.
Literature also documents the positive effect of CPS on firm performance. For example,
Al-Najjar et al. (2016) find a significantly positive relation between CPS and firm
performance in UK listed firms from 2003 to 2009. They argue that CPS reflects
managerial talent rather than managerial power. CEOs with outstanding abilities and
skills can be rewarded relatively higher salary within the top management team. They
find that CPS will be higher if a firm has better corporate governance disclosure,
indicating that well-governed companies attract high talented CEOs. In addition, the
effect of CPS on firm performance is subject to institutional background. UK public
listed firms developed strengthened internal governance and established relative
independent remuneration committees. Thus, the pay-setting process is less likely to be
intervened by powerful CEOs. Besides, the positive effect of CPS on firm performance
is also applicable in China. Hu et al. (2013) find that higher CPS leads to better firm
performance and they argue this positive effect is driven by tournament incentives. The
result is consistent with Burns et al. (2017) who find that the pay difference between
the CEO and other top executives measured by CPS is correlated with enhanced firm
2 Say on pay is a term used for a role in corporate law whereby a firm’s shareholders have the right to
vote on the remuneration of executives.
23
value using a cross-country sample includes China and UK. Overall, this line of
research about CPS provides inconclusive evidence.
All in all, prior literature on CEO pay disparity focuses on the economic consequence,
e.g. firm value and performance. However, the rank-order tournament theory and
managerial power theory are not “one size fits all” since the role of CEO pay disparity
is subject to many factors such as institutional background in different countries and
companies.
2.5 CEO pay disparity and earnings management
The promotion-based tournament incentives for top executives influence not only firm
performance but also earnings management behaviour. Earnings management is the use
of accounting techniques to produce financial reports that present an overly positive
view of a company's business activities and financial position to obtain some private
gain (Schipper, 1989). Accounting information is a critical element in the Chinese
regulators’ administrative governance of listed firms (Liu & Lu, 2007). For instance,
minimum ROE hurdles must be met to gain approval for rights issues, and regulators
will mark the companies as potential delisting companies if they report net losses over
three sequential years (Chen & Yuan, 2004; Haw, Qi, Wu, & Wu, 2005; Liu & Lu,
2007). Given such accounting regulations, top executives have incentives to manipulate
reported earnings. On the one hand, to help firms meeting specific accounting
information hurdles; On the other hand, to help themselves increasing financial wealth
as well as keeping career security (Bergstresser & Philippon, 2006).
In particular, senior managers have financial incentives to increase their performance-
based and equity-based compensation by engaging in earnings management
(Bergstresser & Philippon, 2006; Burns & Kedia, 2006; Healy, 1985; Jiang et al., 2010).
For example, CFOs have the primary responsibility in the firm’s overall financial
reporting. CFOs’ financial incentives should play an important role in earnings
management (Jiang et al., 2010). In terms of the non-CEO executives, most of them
carry out as well as oversee the firm’s daily operational decisions. Thus, the tournament
24
compensation structure may provide them with strong financial incentives to engage in
earnings management (Park, 2017). According to the tournament theory, most increases
in top executive pay occur due to a promotion to a higher ranked position rather than
continued service in the same position (Eriksson, 1999; Lazear, 1992; Lazear & Rosen,
1981). In this case, becoming the next CEO is attractive to non-CEO executives for
increased compensation. In terms of the career concerns of senior managers, Demers &
Wang (2010) find that older executives are more likely to engage in both accruals-based
and real earnings management than younger executives. This finding supports the
career incentives in earnings management. Overall, with a larger CEO pay gap, non-
CEO executives are more motivated to manipulate reported earnings for their private
interests. Therefore, a large pay gap between the CEO and other top executives provide
potential promotion-based tournament incentives for non-CEO executives to conduct
earnings management.
In addition, CEOs are highly incentivised to engage in earnings management for their
financial interests, including performance-based and stock-based compensation
(Bergstresser & Philippon, 2006; Cheng & Warfield, 2005). According to the
managerial power theory, a large CEO pay gap reflects the relative power and influence
of CEOs in demanding higher compensation (Bebchuk et al., 2011). Besides, the career
incentives lead to powerful CEOs to manipulate reported earnings (Mande & Son,
2012). With a greater pay gap, dominant CEOs have an increased motivation to protect
and enhance both their financial wealth and job security. Also, powerful CEOs are more
likely to lead to a breakdown of good governance (Bebchuk et al., 2011; Chen et al.,
2013). For instance, larger CEO pay dispersion is correlated with a lower sensitivity of
CEO turnover to performance (Bebchuk et al., 2011) and a higher likelihood of the
CEO also holding the chairman position (Bebchuk et al., 2011; Faleye, Reis, &
Venkateswaran, 2013). Under these circumstances, powerful CEOs might influence
firm decision-making for their self-benefits but harm shareholders’ interests. Overall,
powerful CEOs could be more likely to manipulate reported earnings because they want
to maintain high firm performance to avoid adverse compensation and career
25
consequences. That is, a large pay disparity incentivises powerful CEOs to engage in
earnings management for their self-interests.
Park (2017) investigates the relationship between the CEO pay dispersion and earnings
management behaviours in the US-listed firms from 1994 to 2013. The CEO pay gap
(Kale et al., 2009) and CPS (Bebchuk et al., 2011) are both employed to measure the
CEO pay disparity within the top management team. It is found that CEO pay disparity
has a significantly positive impact on earnings management through real activities
manipulation (RAM) as most top executives oversee the daily operational decisions.
The compensation gap between the CEO and the CFO leads to more accrual-based
earnings management because of the finance and accounting expertise of the CFO. Both
relations are driven by short-term pay (salary and bonus) dispersion rather than long-
term pay (stocks and options) dispersion. They argue that the competitions of being
promoted to CEO provide tournament incentives for non-CEO executives to engage in
more earnings manipulations. These findings are consistent with the idea that large
tournament prize leads to extremely aggressive and competitive behaviours (Siegel &
Hambrick, 2005).
Overall, CEO pay disparity influences corporate earnings management. On the one
hand, the large pay disparity provide tournament incentives for non-CEO executives to
engage in earning management in order to enhance their chances of promotion to the
next CEO. On the other hand, dominant CEOs who receive relatively higher
compensation may lead to more earnings management activities for their own salary
and career security. Therefore, a large CEO pay disparity increases the intensity of
earnings management because of the tournament prizes for non-CEO executives as well
as the CEO power.
2.6 CEO pay disparity and firm behaviours and output
According to rank-order tournament theory, the promotion-based tournament
incentives push top executives to work harder for increased chances of becoming the
next CEO (Lazear & Rosen, 1981). Large tournament prize of senior managers leads to
26
extremely aggressive and competitive behaviours (Siegel & Hambrick, 2005). Kini &
Williams (2012) examine the tournament incentives effect of top executives on firm
risk and corporate policies. It is found that CEO pay gap is significantly and positively
associated with risk-taking in both non-financial and financial companies. Besides, this
positive tournament incentive effect results in riskier policies such as more R&D
investment and higher firm leverage. These results are consistent with the finding of
Goel & Thakor (2008) that the tournament prizes highly motivate top executives to
increase their chances of promotion to CEO by taking more risks. Further, the
tournament compensation structures have the potential to meet the requirement of
employers who want their employees to take more risk and not careless.
In addition, the promotion-incentives effect may also result in other activities. Haß et
al. (2015) find a significantly positive relationship between CEO pay gap and corporate
fraud. It indicates that the non-CEO executives are more likely to engage in fraud to
increase the chance of winning the tournament prizes. Zhang, Huang, & Habib (2018)
suggest that tournament incentives measured as CEO pay gap has a negative effect on
the firm’s financial restatements in Chinese listed firms. It is found that both core and
non-core financial restatement are reduced in firms with larger gap disparity between
the CEO and top executives. Kubick & Masli (2016) support the effective influence of
tournament incentives on CFO. It is found that the compensation gap between CEO and
CFO has a positive relation with tax aggressiveness. Overall, the CEO pay disparity
can provide top executives with promotion-based incentives, thereby leading to more
aggressive and competitive behaviours.
The managerial power theory suggests that powerful CEOs are more related to agency
problems that influence firm behaviours and outcome (Bebchuk et al., 2011). For
example, Chen et al. (2013) investigate the relationship between executive pay disparity
(CPS) and the cost of equity capital. They find that the pay dispersion between the CEO
and other top executives is associated with a higher cost of capital. Chintrakarn,
Chatjuthamard, Tong, & Jiraporn (2018) document that higher CPS lead to a reduced
probability of paying dividends. This evidence supports the agency theory that dividend
27
payouts are detrimental to the firm in the view of CEOs since the dividends will
decrease the free cash flows of firms. Thus, powerful CEOs are more related to lower
dividend payouts. Therefore, the CPS reflects the CEO dominance that will affect the
firm outcome and behaviours.
Overall, the large CEO pay disparity provides promotion-based incentives to non-CEO
executives and reflects the relative power of CEOs, and both play an important role in
firm behaviours and outcomes.
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3. Essay one
CEO pay disparity and firm performance: New evidence from China
3.1 Introduction
CEO pay disparity in recent years has become one of the corporate governance research
interests that attracts a lot of attention. As the top management team is responsible for
firms’ daily operations and profitability, a proper corporate compensation structure is
essential to incentivise top executives to make great efforts and improve firm
performance. In particular, the pay disparity between the CEO and other top executives,
as the key to the executive compensation design, plays an important role in the inner
workings of the top management team (Bebchuk et al., 2011).
In this essay, I investigate the relationship between CEO pay disparity and firm
performance using Chinese data. China as the second-largest economy provides an
interesting setting to examine such a research topic due to its unique institutional
mechanisms. China’s corporate governance system is poor, and the outside investor
protection is insufficient (Firth et al., 2006). Moreover, the extremely high salary
compared to lower-level employees and the widening pay gap of senior executives have
attracted substantial public attention and caused significant controversy in society since
the disclose of individual compensation of senior executives in 2005. The Central
Government of China has introduced a series of regulations to mandate the
compensation of top executives to mitigate the strong social complaints about pay
inequality. For example, the Chinese central government put forward a regulation to
limit executive salaries for the country’s centrally-controlled state-owned enterprises
(CSOEs)3 in 2009. In 2014, a stricter “pay ceiling” regulation was announced to further
limit the compensation of top executives in CSOEs. This regulation was officially
3. State-owned enterprises (SOEs) in China are either controlled by the central government (CSOEs) or
local governments (LSOEs). The central government directly controls and manages strategic SOEs
through the State Assets Supervision and Administration Commission (SASAC).
29
implemented from January 1, 2015, and gradually implemented to SOEs owned by the
local governments (LSOEs). Therefore, the CEO pay disparity is expected to play a
critical role in firm performance in China’s listed firms.
My study makes several contributions to the literature. First, I add evidence on the
influence of CEO pay disparity on firm performance. Existing studies have examined
the relationship between pay disparity and corporate performance, but controversy
remains in this line of research. Most of the existing studies in this area such as Kale et
al. (2009), Bebchuk et al. (2011), Chen et al. (2013), and Al-Najjar et al. (2016) are
conducted utilising data from Western industrialised societies. It may not be appropriate
to draw general conclusions about the role of CEO pay disparity without evidence from
emerging economies. In this study, I document that the CEO pay disparity measured by
both the CEO pay gap (Kale et al., 2009) and CPS (Bebchuk et al., 2011) is positively
associated with firm performance in China’s listed firms. This is in line with the rank-
order tournament theory, which argues that a larger CEO pay gap provides greater
tournament incentives for non-CEO executives to work harder for increased chances of
promotion to the CEO position (Kale et al., 2009; Lazear & Rosen, 1981). However,
the positive relation between CPS and performance in China is not consistent with
managerial power theory, which indicates that higher CPS reflects more CEO power
that leads to more agency problems and decreased firm performance (Bebchuk et al.,
2011; Finkelstein, 1992). The results in this study suggest that higher CPS in China
reflects positive tournament effects and it supports the rank-order tournament theory.
Second, to our best knowledge, this could be the first to focus on the characteristics of
non-CEO executives to explore their sensitivity to tournament incentives. Previous
literature mainly focusses on how CEOs’ characteristics impact the tournament
incentives for other top executives. Very few studies pay attention to whether
tournament incentives are driven by the non-CEO executives’ characteristics. This
study explores the tournament effects based on non-CEO executives’ personal
characteristics and provides more robust evidence supporting the positive influence of
CEO pay disparity on firm performance. In particular, I examine whether the
30
tournament incentives are shaped by non-CEO executives’ age and gender. By
conducting the subsample analysis, I find that the CEO pay gap does not play a role if
the non-CEO executives are neither too old nor too young. The ambition of older top
executives to higher positions is minor, and younger executives could be more active
in job-hopping that can give them higher salaries and better positions. Besides, the
positive tournament effects on firm performance are not significant only if the female
ratio within the non-CEO executive team is equal and larger than 50%. Female
executives are more risk-averse (Byrnes et al., 1999; Charness & Gneezy, 2012) that
makes them more conservative, thereby, leading to less incentives to promotion
compared to males.
Third, to our best knowledge, this is the first study to investigate the effects of the 2015
“pay ceiling” regulation on the relationship between CEO pay disparity and firm
performance. This study finds that the CEO pay gap is positively associated with firm
performance in both the pre-regulation and post-regulation periods in SOEs subsample.
It indicates that the positive effects of CPG on performance are not driven by the
regulation. However, this result is not robust in the subsample of SOEs that are
controlled by government bureaus because they could be more sensitive to political
objectives. It is found that the positive effect of CPG on performance is not significant
in the post-regulation period in SOEs controlled by government bureaus. Therefore, the
“pay ceiling” regulation reduces the tournament incentives of non-CEO executives in
SOEs directly controlled by government bureaus.
In addition, the industry concentration measured by HHI influences the efficiency of
tournament effects in SOEs. In highly concentrated industries, the CPG has no
significantly impact on firm performance in SOEs subsample. This finding indicates
that the positive tournament effect is not applied to monopoly industries.
31
3.2 Literature review and hypothesis development
3.2.1 CEO pay disparity
CEO pay disparity is defined as the pay differential between the CEO and other top
executives. There are two competing theories on the role of CEO pay disparity to firm
performance. The first one is the rank-order tournament theory that indicates a large
CEO pay disparity provides great tournament incentives for non-CEO executives to
compete for the CEO position (Lazear & Rosen, 1981). The second one, which we call
managerial power theory, sees a large CEO pay disparity reflects the relative power and
dominance between the CEO and other top executives. Both theories predict that the
CEO pay disparity can be related to firm performance.
3.2.2 Rank-order tournament theory
According to the tournament theory, a large CEO pay disparity provides non-CEO
executives with strong tournament incentives to make greater effort to increase the
likelihood of becoming the next CEO (Lazear & Rosen, 1981). The level of employee
compensation stepped increase with the promotion of positions since the rank-order
tournaments are schemes of relative performance evaluation and the managerial skills
are hard to quantify. A CEO as the leader within top executives is required to have firm-
specific skills to run a firm. However, a company cannot rely on the CEO alone but the
hard work and skills of the entire top management team. Besides, these CEO skills are
not beneficial to other top executives if they do not intend to work for a long time in
the firm. Particularly, these skills become useless when non-CEO executives leave the
firm. Thus, providing non-CEO executives with incentives to stay for the long term and
develop their abilities is very necessary to run the firm. There are mainly two
advantages of a large pay disparity between the CEO and other top executives. First,
the relatively higher compensation level for CEOs can attract and encourage them to
do their best for better performance. More importantly, a large pay disparity can
motivate non-CEO executives to make more efforts on working for higher rank with
more salaries (Goel & Thakor, 2008; Haß et al., 2015; Kini & Williams, 2012). Thereby,
32
a large pay disparity helps to build a large pool of skilled internal candidates to compete
for the CEO position (Chen et al., 2013).
Overall, this tournament perspective indicates that a large CEO pay disparity provides
tournament incentives for other top executives and incentivises to work hard, which is
beneficial to corporate performance (Eriksson, 1999; Hu et al., 2013; Kale et al., 2009).
The CEO pay gap, defined as the natural logarithm of difference between the CEO's
total compensation and the median total compensation of all other executives in the top
management team, is used to measure such tournament incentives (Kale et al., 2009). I
suppose that a large CEO pay gap has positive influence on firm performance in China.
The above discussions lead to my first hypothesis:
H1: The CEO pay gap is positively associated with firm performance.
3.2.3 Managerial power theory
Managerial power is defined as the ability of an individual manager to exert his or her
will to corporate decision-making (Finkelstein, 1992; Hickson et al., 1971). A powerful
CEO could exert his desires on the remuneration decisions for their self-interests rather
than shareholder’s interests (Lambert et al., 1993). According to the managerial power
theory, a large CEO pay disparity reflects the relative strong power of a CEO to other
top executives (Bebchuk et al., 2011; Bebchuk & Fried, 2003). With the larger CEO
pay disparity, CEOs have more incentives to protect their self-interests such as financial
wealth and career security. Therefore, a powerful CEO is associated with more CEO
entrenchment and more agency problems (Adams et al., 2005; Bebchuk et al., 2011).
Consistent with this perspective, Bebchuk et al. (2011) document that a large CEO pay
disparity is associated with low CEO turnover sensitivity to performance and worse
firm performance.
In addition, a powerful CEO may unwilling to develop other top executives skills or
may even hinder their career development, because high-quality executives as the
potentially internal CEO successor candidates could harm CEO’s career and financial
security (Rajan & Wulf, 2006). Thus, poor inside promotion incentives for non-CEO
33
executives could result in more job-hopping for high skilled or talented executives,
thereby, leading to worse firm performance. For instance, high ability insiders are rare
in firms with more entrenched CEOs (Masulis & Mobbs, 2011). Bebchuk et al. (2011)
introduced the CEO pay slice (CPS), defined as the ratio of the total CEO pay to the
sum of the total pay of the top four executives plus CEO pay, to measure the managerial
power of CEOs. Overall, the managerial power view suggests that a large CEO pay
disparity is associated with reduced firm performance. Therefore, I have the following
hypothesis:
H2: The CEO pay slice is negatively associated with firm performance.
However, most literatures examine the relationship between CPS and firm performance
using US data, and the conclusions may not apply to other countries. For example, some
literature documents the positive effects of CPS on firm performance. Al-Najjar et al.
(2016) find that CPS is associated with better firm performance in UK listed firms from
2003 to 2009. They argue that CPS reflects a CEO’s managerial talents rather than
managerial power. CEOs with outstanding abilities and skills can be rewarded
relatively higher salary within the top management team. Besides, Hu et al. (2013)
document that CPS plays positive tournament roles in firm performance in China. These
findings are consistent with Burns et al. (2017) who find that pay difference between
the CEO and other top executives measured by CPS is associated with enhanced firm
value using a cross-country sample includes China and UK. Therefore, I expect the CPS
is positively associated with firm performance in China.
H3: The CEO pay slice is positively associated with firm performance.
3.3 Sample and variable construction
3.3.1 Data
The initial sample of this study includes all Chinese companies listed in A-share
markets in the Shanghai and Shenzhen Stock Exchanges from 2005 to 2017 (the data
will be updated to 2018 and later). All data are collected from the China Listed Firms
34
Research Database of China Stock Market and Accounting Research (CSMAR). The
starting year of our sample is 2005 when the listed firms started to disclose the
compensation of top executives (including Chairman of the Board, CEO, and other top
executives). Only the aggregate amount of payment to the top three executives were
disclosed in firm annual reports before 2005.
Following the prior literature, financial firms and special treatment (ST) firms are
excluded because of their unique accounting standards. We also remove observations
with missing information and delete the observations with extreme values. The final
sample includes 3,091 firms that consist of 20,760 firm-year observations.
3.3.2 Variable construction
3.3.2.1 Measuring CEO pay disparity
Following Kale et al. (2009) and Bebchuk et al. (2011), I use two measures to measure
the CEO pay disparity: CEO pay gap (CPG) and CEO pay slice (CPS). CPG is defined
as the natural logarithm of the difference between CEO pay and the median pay of all
other executives in the top management team.
CPG = Ln (Total compensation of CEO - Median of total compensation of other
executives in the firm-year).
CPS is defined as the fraction of aggregate compensation of the top five members in
the executive team that is captured by the CEO. In particular, the top five members
include the CEO plus the four highest paid executives excluding the CEO.
CPS = Total compensation of CEO / (Total compensation of top four executives +
Total compensation of CEO).
An executive's total compensation is the sum of salary, bonuses and other cash
compensation. This compensation does not include long-term incentives such as stock
options and restricted stocks, because these are rarely exercised in China.
35
3.3.2.2 Measuring firm performance
Following Liu, Miletkov, Wei, & Yang (2015), I use two accounting measures to
represent firm performance: return on assets (ROA) and return on equity (ROE). ROA
is calculated as net income divided by total assets and ROE refers to net income divided
by total equity. Liu, Wei, and Xie (2014) suggest that the market-based measures such
as Tobin's Q and stock returns are not proper performance measures for Chinese listed
firm because Chinese stock ownership underwent significant reform4 during our sample
period.
3.3.2.3 Control variables
I include CEO age, CEO gender, CEO tenure, CEO duality, firm size, board size, board
independence, leverage, largest shareholder ownership and firm age as control variables.
Appendix A provides definitions for all variables.
3.3.3 Descriptive Statistics and correlation matrix
Table 1 provides the basic summary statistics of the variables employed in this study.
The mean CEO compensation is 637,991 RMB that is significantly greater than average
median-compensation of non-CEO executives, which is 417,327 RMB. The mean CEO
pay gap is 220,664 that is in line with the existence of tournaments. The average CPS
is 24.89%, which shows that total CEO compensation accounts for about one-fourth of
total compensation of the top five paid executives. In addition, 94.56% of CEOs are
male, and 24.07% of CEOs also hold the position of Chairman of the board. The
average proportion of independent directors is 36.90%, which satisfies the requirements
of the China Securities Regulatory Commission (CSRS) that independent directors
must account for at least one-third of the total numbers on boards for all listed firms.
4. The Chinese state ownership reform in 2005 required that the listed firms gradually convert their non-
tradable shares into tradable shares. The ownership reform was basically completed by 2007. However,
the former non-tradable shareholders still face a number of restrictions on share trading in terms of, for
instance, the percent of shares allowed to be traded and the lockup period (Haveman and Wang, 2013).
36
Insert Table 1 here
Table 2 reports the time trend of CEO pay disparity, top executives’ compensations and
firm performance measures included in this study. Panel A shows that the senior
executives’ compensation and CEO pay gap both have a significant increase from 2005
to 2017. The ROA and ROE in 2008 are relatively low that indicates the influence of
2008 financial crisis. Panel B and Panel C show the time trends in SOEs and private
firms, respectively. Compared with private firms, the salaries for CEOs and other top
executives are higher in SOEs even though SOEs’ performance is worse. Moreover, the
CEO pay gap in private firms is greater than that in SOEs. It could reflect more
tournament incentives in private firms.
As shown in Panel B, the mean CEO pay gap of SOEs has a significantly reduce in year
2015 because of the implement of the “pay ceiling regulation”. We can observe the
mean CEO compensation of SOEs has a minor decrease, but non-CEO executives’
average salaries are still increase in year 2015. This makes the decrease of CEO pay
gap in SOEs. According to Panel C, the CEO and other top executives’ compensation,
as well as CEO pay gap are all increasing year by year in private firms since they are
not affected by the “pay ceiling” regulation.
Insert Table 2 here
Table 3 shows the correlation matrix between used variables. Both CPG and CPS have
positive correlations with ROA and ROE. Most of the correlations reported are between
-0.20 and 0.20. The highest correlation is between ROA and ROE at 0.796, and the
second highest correlation is between CPG and CPS at 0.642. It is reasonable because
ROA and ROE measure firm performance and CPG and CPS measure CEO pay
disparity. Overall, the correlations do not indicate any serious multicollinearity
problems.
Insert Table 3 here
37
3.3.4 Empirical analysis
3.3.4.1 CEO pay disparity and firm performance in China
I conduct the following regression to investigate the influence of CEO pay disparity on
firm performance. Table 4 contains the baseline regression results after controlling for
industry and year effects. Firm performance is measured by both ROA and ROE. CEO
pay disparity is measured by the CPG and CPS in each regression, respectively.
Firm performance = 𝛼 + 𝛽1CEO pay disparity + 𝛽2LnCEO age + 𝛽3CEO duality +
𝛽4CEO gender+ 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7LnBoard independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽10Largest shareholder + 𝜀
The results of Models 1 and 2 show that the estimated coefficients on CPG are 0.029
and 0.053 and both are significant at the 1% level, meaning that CPG is positively
associated with firm performance. These results support the rank-order tournament
theory that a large CEO pay disparity provides non-CEO executives with tournament
incentives that leads to better firm performance. Similarly, Models 3 and 4 document
the positive and significant relationship between CPS and firm performance at the 1%
level. It indicates that a higher CPS leads to better firm performance in China. This
finding is not consistent with managerial power theory but supports the tournament
theory. Thus, CPS does not reflect the CEO power but the tournament incentives for
other top executives.
CEO tenure is significantly and negatively related to firm performance which means
CEOs with longer tenure leads to worse firm performance. In addition, firms with
higher debt ratio measured by Leverage are significantly associated with worse
performance. The positive coefficients on Firm size indicate that larger firms perform
better.
Insert Table 4 here
38
3.3.4.2 CEO pay disparity and firm performance, robustness check
It is a challenge to establish the causal relationship between CEO pay disparity and firm
performance because of the endogeneity problems. Managerial pay disparity is not an
exogenous random variable. It is impossible to randomly assign observations to a
treatment or control group, thus, selection bias is a potential issue associated with
collecting empirical data. In addition, reverse causality between CEO pay disparity and
firm performance is uncertain. Palia (2001) suggests that managerial compensation and
firm performance are jointly determined. Thus, firm’s performance might impact the
pay disparity between the CEO and other top executives rather than CEO pay disparity
affects firm performance. For instance, the performance-based compensation and pay
gap would be larger if the firm performance is better. Therefore, reverse causality is an
issue to approve a positive association between CEO pay disparity and firm
performance.
Following Armstrong, Jagolinzer, & Larcker (2010), I address the above problems by
employing the propensity score matching (PSM) approach. The aim of the PSM is to
produce two statistically similar samples with high-and low-pay disparity, respectively.
First, firm-year observations are allocated to the treatment and control groups based on
the level of the pay disparity. Specifically, a firm-year observation is allocated to the
treatment group if its CEO pay disparity is above the 75% percentile of the pay disparity
of that year. A binary variable equal to one is constructed if the pay disparity is above
the 75% percentile value and zero if it is below the 75% percentile value. Next, to
perform the PSM analysis for high-pay disparity versus low-pay disparity firms, the
propensity score is calculated as a function of CEO characteristics and other firm-level
control variables. Then, I compare average firm performance between the treatment
(high-pay disparity) and control groups (low-pay disparity) since they are statistically
similar in all other relevant characteristics that may impact firm performance. The
sample consists of 10,374 / 10,370 firm-year observations.
39
Table 5 displays the model to estimate the propensity scores. I first estimate a probit
model to predict the determinants of the pay disparity dummy. CEO gender is not
included in this regression because near 95% CEOs are males, and it could affect the
efficiency of matching. CPG75 and CPS75 are used to measure CEO pay disparity. The
regression specification is as follows:
CEO pay disparity = 𝛼 + 𝛽1LnCEO age + 𝛽2CEO duality + 𝛽3LnCEO tenure +
𝛽4LnBoard size + 𝛽5Board independence + 𝛽6Leverage + 𝛽7Firm size + 𝛽8LnFirm age
+ 𝛽9Largest shareholder + 𝜀
Table 5 presents that both CPG and CPS are significantly higher in firms with a CEO
who has longer tenure or also holds the chairman position. The results show that
powerful CEOs achieve higher salaries as CEO duality and CEO tenure are the reflects
of CEO power. Besides, the Board independence is negative related to both CPG and
CPS which indicates the monitoring role of independent directors. The negative
coefficient on Leverage shows that the salary difference between the CEO and other
top executives is lower in firms with higher debt ratio. In addition, the CEO pay
disparity is lower if the firm’s largest shareholder holds more shares. These results
indicate that the CEO pay disparity level is determined by some CEO characteristics,
board composition and firm specific factors.
Insert table 5 here
Second, I use the propensity scores estimated from Table 5 to perform a one-to-one
PSM procedure. It produces two statistically similar samples with high-CEO pay
disparity and low-CEO pay disparity, respectively. Table 6 contains Panel A and Panel
B. Panel A is the t test of the difference between high and low CEO pay disparity to
firm performance. Panel B reports the OLS regression model as same as Table 4 using
the PSM sample.
In Panel A, ROA of the treatment group is statistically higher than that of the control
group (t statistic = 16.18). A similar pattern is found for using ROE as performance
measure. The average ROE of the treatment group is 0.0994, compared with 0.0692 of
40
the control group. The difference is 0.0301 that is statistically significant (t statistic =
16.41). Besides, I find similar significant and positive results when using CPS75
measuring pay disparity. These results show that CEO pay disparity is significantly
associated with better firm performance measured by ROA and ROE at the 1% level,
which is in line with the findings of Table 4.
Panel B reports the estimates of the regression results of CEO pay disparity on corporate
performance using the PSM sample. As shown in Panel B, CEO pay disparity is
significantly and positively associated with corporate performance measured by both
ROA and ROE. The results are consistent with the baseline findings of Table 4. It
indicates the positive tournament effect is robust after addressing sample selection bias.
Thus, a large CEO pay disparity provide non-CEO executive with tournament
incentives that leads to enhanced firm performance in China. The CEO pay disparity
shows as a corporate governance mechanism to improve firm performance.
Insert Table 6 here
3.3.5 CEO pay disparity and firm performance, sub-sample analysis
Next, I conduct the subsample analysis to examine whether the positive influence of
CEO pay disparity on firm performance is robust, based on different settings. CPG is
mainly used to present the CEO pay disparity in sub-samples. Besides, ROA is mainly
employed to represent firm performance.
3.3.5.1 CEO pay disparity and firm performance: SOEs and private firms
First, I examine whether the enhanced firm performance through large CEO pay
disparity applies to both SOEs and private firms. I split the full sample into subsamples
of SOEs and private firms basing the ultimate controller of sample firms. SOEs
subsample includes the firms whose ultimate controllers are government, and private
firms are the firms whose ultimate controllers are private firms or individual person.
Then, I re-run the baseline regression (Table 4) using the subsample of SOEs and
private firms, respectively.
41
Table 7 shows that the positive relationship between CEO pay disparity and firm
performance exists in both SOEs and private firms. It indicates that CEO pay disparity,
as a corporate governance mechanism, plays an important role in enhancing firm
performance in China. Thus, a large CEO pay disparity provides promotion-based
tournament incentives for non-CEO executives that lead to better firm performance.
Insert Table 7 here
3.3.5.2. CEO pay disparity and firm performance: Pre and Post “pay ceiling”
regulation period
Considering about the 2015 pay ceiling regulation only applied to SOEs, I conduct a
sub-sample analysis to examine whether the positive tournament effects are driven by
the regulation. By dividing the SOEs sample into pre-regulation (before 2015) and post-
regulation (after 2015) subsamples, I find that the CPG is positively associated with
ROA in both the pre and post regulation periods as shown in Panel A. It indicates the
positive effects of CPG on performance are not driven by the regulation. However, CPS
is not significantly related to ROA in neither pre-nor post-regulation period in SOEs.
Panel B shows the CPG and CPS are both positively related to ROA in pre and post
period in private firms. Thus, the regulation does not weaken the efficiency of positive
tournament effects in private firms.
In Panel C, I conduct a subsample that only includes the SOEs directly controlled by
government bureaus to further examine how the regulation affects the tournament
effects. SOEs directly controlled by government bureaus should be more sensitive to
the pay ceiling regulation. Panel C shows that the significantly positive relationship
between CPG and ROA becomes insignificant after year 2015. This finding indicates
that the non-CEO executives’ promotion incentives are mitigated by the regulation.
Therefore, the positive tournament effects are more pronounced in SOEs who are
directly controlled by government bureaus in the pre-regulation period.
Insert Table 8 here
42
3.3.5.3 CEO pay disparity and firm performance: does industry concentration
matter
It is supposed that the industry concentration could impact the positive tournament
effects. The tournament incentives for non-CEO executives are subject to outside career
market, and the outside job market is subject to industry concentration. For example,
outside job selections for top executives will be greater if their firms are in the
competitive industries and the outside opportunities are limited if firms are in the
monopoly industries. Herfindahl-Hirschman Index (HHI) is employed to measure the
industry concentration and determine industry competitiveness. The range of HHI is
from 0 to 1, and a large HHI indicates a high concentration of industry.
𝐻𝐻𝐼 =∑(𝑋𝑖/𝑋)2
𝑁
𝑖=1
=∑𝑆𝑖2
𝑁
𝑖=1
Where Xi refers to the operating revenue for a specific firm in its industry; X is the total
operating revenue for all firms in the given industry.
Based on the HHI of each industry-year, I divide the full sample into three sub-groups
that include highly competitive industries (HHI in the bottom 25% range), highly
concentrated industries (HHI in the top 25% range), and medium concentrated
industries (HHI is in between). Table 9 shows the relationship between CPG and ROA
in three sub-samples. Panel A shows that CPG is significantly and positively associated
with ROA in SOEs from highly competitive and medium concentrated industries.
However, this relationship changes to be insignificant in highly concentrated industries,
indicating that the positive tournament effect is not apply to monopoly industries. Panel
B shows that in private firms, the positive relationship between CPG and ROA is always
significant regardless industry competitiveness.
The different results between SOEs and private firms could come from the promotion
difficulties of non-CEO executives and the political objectives of top executives in
SOEs. The opportunity of promotion to CEO position for non-CEO executives is harder
in SOEs than private firms because CEOs in SOEs are appointed by the government.
43
Moreover, non-CEO executives not only focus on monetary incentives but also political
incentives. These could be the reasons why industry competitiveness shapes the
relationship between CPG and ROA in SOEs. In contrast, the promotion chances are
relatively fair for top executives in private firms, thus, the relationship is consistent
regardless of industry competitiveness.
Within the SOEs, the non-CEO executives’ tournament incentives may not play a role
in highly concentrated industries since their current firms have the monopoly power
and outside career markets are very limited. Moreover, the monopoly SOEs are very
important for the nation’s economy and the CEO selection process could be driven by
multiple factors including political and social objectives. Considering about the
importance of CEO position in monopoly SOEs, CPG may have limited effect on firm
performance.
Insert Table 9 here
3.3.5.4 CEO pay disparity and firm performance: does non-CEO executives’ age
matter
The age of non-CEO executives may moderate the role of CEO pay disparity on firm
performance. I conduct the subsample based on the average age of non-CEO executives.
It shows in table 10 that CPG is positive associated with ROA if non-CEO executives’
average age is between 41 and 51. However, the positive relation becomes insignificant
if the average age of non-CEO executives is old (>=51) or young (<=41). Younger top
executives could be more active in job-hopping that can give them higher salary and
better positions, because they are more willing to take more risk (Hambrick & Mason,
1984; Prendergast, 2002). If the non-CEO executives’ team is young, some of them
might be more willing to move for better positions rather than stand still. However,
older senior executives could be more conservative (Hambrick & Mason, 1984), thus,
their ambition to higher position tends to be limited. If the ages of non-CEO executives
are relatively high, some of them may prefer to enjoy life until retirement. Their
44
incentives for promotion could be less. Therefore, the efficiency of positive tournament
effects is found to be subject to the non-CEO executive’s age.
Insert Table 10 here
3.3.3.5 CEO pay disparity and firm performance: does non-CEO executives’
gender matter
The gender of the top management team is another important aspect and literature has
already documented that women are more risk-averse than men. I conduct the sub-
sample analysis based on the female ratio within non-CEO executives to examine
whether the positive tournament effects are shaped by gender effects. As shown in
Table 11, the positive influence of CPG on ROA is robust if the female ratio of non-
CEO executives is lower than 50%. On the contrast, CPG does not have a significantly
positive effect on ROA if at least half number of top executives are female. These
findings indicate that the tournament incentives are subject to non-CEO executives’
gender. Female managers tend to be more risk-averse (Byrnes et al., 1999; Charness &
Gneezy, 2012), thus, females could be less active in job-hopping and more likely to be
happy with staying in current firm compared with males.
Insert Table 11 here
3.4 Conclusion
In this study, I investigate the influence of CEO pay disparity on firm performance.
Using a sample of Chinese listed firms from 2005 to 2017, I document that CEO pay
disparity is significantly associated with better firm performance. Similar findings are
demonstrated after addressing the endogeneity issues. These findings support the rank-
order tournament theory that a large CEO pay disparity provides non-CEO executives
with large tournament incentives, thereby, leading to enhanced firm performance.
I further document that the robustness of the positive tournament effects is subject to
the executives’ characteristics and industry concentration. For example, the positive
tournament effect become insignificant if non-CEO executives team is older or younger.
45
The ambition of older top executives to higher position is limited, and younger
executives could be more active in job-hopping. Besides, I find that the positive
influence of CEO pay disparity on firm performance is insignificant if the female ratio
within non-CEO executives is greater than 50% since female executives are more risk
averse. Moreover, it is found that the tournament effects do not play a role in highly
concentrated SOEs.
In addition, I investigate the effect of year 2015 “pay ceiling” regulation on the
relationship between CEO pay disparity and firm performance. I find that the positive
tournament effect is robust in SOEs in both the pre- and post-regulation subsample
periods. However, the positive effect of CEO pay disparity is not significant in the post-
regulation period in SOEs directly controlled by government bureaus. The result
indicates reason that the SOEs directly controlled by government bureaus are more
sensitive to the government regulation. Thus, the “pay ceiling” regulation weakens the
efficiency of tournament incentives in SOEs directly controlled by government bureaus.
Overall, the tournament theory applies to China’s listed firms, and a large CEO pay
disparity is beneficial to firm performance. CEO pay disparity can be used as an
effective corporate governance mechanism to build a skilled top management team and
enhance firm performance.
46
3.5 Appendix
Appendix A: Variable definitions
This appendix presents the definition of the variables used in this study
Variables Definition
ROA Net income divided by total assets in the year t.
ROE Net income divided by total equity in the year t.
CEO pay gap The difference between CEO pay and the median pay of all other
executives in the top management team.
CPG The natural logarithm of CEO pay gap.
CEO pay slice (CPS)
The fraction of aggregate compensation of the top five
executives that is captured by the CEO.
CPG75 A dummy variable equals 1 if the CPG is above the 75%
percentile CPG in the year t, and 0 otherwise.
CPS75 A dummy variable equals 1 if the CPS is above the 75%
percentile CPS in the year t, and 0 otherwise.
LnCEO age The natural logarithm of the CEO's age.
CEO duality A dummy variable equals 1 if CEO and Chairman of the board
are the same person, and 0 otherwise.
CEO Gender A dummy variable equals 1 if CEO is male, and 0 otherwise.
LnCEO Tenure
The natural logarithm of the number of years that the CEO has
served as CEO in the sample firm.
LnBoard size The natural logarithm of total number of directors.
Board independence Number of independent directors divided by number of
directors.
Firm size The natural logarithm of total assets.
Leverage The book value of debt divided by book value of total asset.
Largest shareholder Percentage of shares owned by the largest shareholder.
LnFirm age The natural logarithm of the number of years (plus one) since
incorporation.
47
3.6 Tables
Table 1: Summary statistics
This table reports the summary statistics of the variables employed in the analysis. The
sample comprises 20,760 observations (firm-years) from 2005 to 2017. The
descriptions of all variables are reported in Appendix A.
Variable Obs Mean SD P25 Median P75
Panel A: Firm performance
ROA (%) 20,760 4.37% 5.38% 1.64% 3.94% 6.86%
ROE (%) 20,760 7.40% 10.96% 3.49% 7.42% 11.68%
Panel B: Executive compensation
CEO pay 20,760 637,991 695,123 283,180 469,941 751,950
Median pay-other top executives 20,760 417,327 364,623 204,000 331,000 518,325
Top5 20,760 2,545,000 2,420,000 1,220,000 1,955,050 3,093,400
Panel C: CEO pay disparity
CEO pay gap 20,760 220,664 449,370 48,750 119,000 251,850
CPS (%) 20,760 24.89% 7.25% 21.74% 24.20% 27.86%
Panel D: CEO characteristics
CEO gender 20,760 94.56% 22.68% 1 1 1
CEO age 20,760 48.46 6.45 44 48 53
CEO duality 20,760 24.07% 42.75% 0 0 0
CEO tenure 20,760 3.795 2.97 2 3 5
Panel E: Control variables
Board size 20,760 8.91 1.79 8 9 9
Board independence (%) 20,760 36.90% 5.43% 33.33% 33.33% 40.00%
Leverage 20,760 0.44 0.22 0.27 0.44 0.60
LnFirm Size 20,760 21.94 1.29 21.03 21.77 22.65
Largest shareholder (%) 20,760 36.40% 15.30% 24.28% 34.52% 47.11%
Firm age 20,760 2.665 0.42 11 15 19
48
Table 2: Time trend
This table displays the time trend of CEO pay disparity, top executives’ compensation
and firm performance measures. Panel A and Panel B indicates the sub-sample of SOEs
and private firms, respectively. The descriptions of all variables are reported in
Appendix A.
Panel A: Full sample
Panel B: SOEs
Year CEO pay Median pay CEO pay gap Top4 CPS ROA ROE
2005 249,235 179,676 69,558 757,490 24.42% 2.26% 4.08%
2006 304,200 208,246 95,954 887,539 24.84% 3.51% 6.50%
2007 429,503 293,009 136,494 1,277,844 24.81% 4.54% 9.36%
2008 469,817 328,591 141,227 1,424,845 24.67% 3.01% 5.44%
2009 490,692 355,950 134,742 1,546,892 24.12% 3.70% 7.57%
2010 600,080 424,869 175,210 1,864,729 24.02% 4.64% 9.47%
2011 676,649 476,707 199,942 2,095,377 23.91% 4.31% 8.91%
2012 691,169 490,986 200,183 2,164,279 23.69% 3.44% 6.73%
2013 721,848 520,927 200,921 2,308,250 23.26% 3.20% 6.20%
2014 750,897 541,080 209,817 2,403,220 23.39% 2.87% 5.16%
2015 749,111 548,420 200,691 2,464,717 22.64% 2.24% 3.77%
2016 776,404 575,830 200,574 2,587,297 22.49% 3.11% 5.73%
2017 876,507 647,420 229,087 2,912,771 22.50% 3.72% 7.21%
Year CEO pay Median pay CEO pay gap Top4 CPS ROA ROE
2005 258,745 175,344 83,402 748,362 25.02% 2.27% 3.74%
2006 297,039 197,729 99,310 861,158 25.28% 3.64% 6.76%
2007 412,453 271,983 140,470 1,192,603 25.40% 4.86% 9.69%
2008 460,120 306,715 153,404 1,340,409 25.26% 3.74% 6.36%
2009 482,125 324,792 157,334 1,439,766 25.12% 4.83% 8.78%
2010 557,559 363,216 194,343 1,606,739 25.53% 5.62% 10.16%
2011 608,645 396,222 212,423 1,773,319 25.27% 5.30% 9.01%
2012 630,836 412,944 217,892 1,863,836 25.18% 4.32% 7.10%
2013 671,942 444,292 227,650 2,022,748 24.79% 4.09% 6.86%
2014 699,184 462,398 236,786 2,112,535 24.79% 4.02% 6.48%
2015 748,014 484,660 263,354 2,246,954 24.45% 3.63% 5.71%
2016 787,949 512,880 275,069 2,417,926 24.29% 4.37% 7.04%
2017 861,634 554,105 307,529 2,611,150 24.51% 4.93% 8.15%
49
Panel C: Private firms
Year CEO pay Median pay CEO pay gap Top4 CPS ROA ROE
2005 288,425 161,824 126,601 719,878 26.91% 2.28% 2.67%
2006 278,420 170,385 108,035 792,568 26.42% 3.98% 7.43%
2007 376,368 227,481 148,886 1,012,189 26.66% 5.56% 10.39%
2008 441,011 263,614 177,397 1,174,041 26.42% 5.17% 8.17%
2009 469,048 277,230 191,818 1,276,245 26.65% 6.56% 10.62%
2010 513,143 298,815 214,328 1,337,252 27.11% 6.65% 10.88%
2011 553,051 330,425 222,626 1,510,035 26.38% 6.11% 9.09%
2012 584,999 353,652 231,346 1,635,580 26.32% 4.99% 7.38%
2013 635,667 388,589 247,077 1,815,229 25.89% 4.73% 7.34%
2014 664,507 409,636 254,871 1,917,613 25.73% 4.79% 7.37%
2015 747,352 446,204 301,148 2,115,610 25.55% 4.47% 6.88%
2016 794,245 478,547 315,698 2,325,552 25.27% 5.05% 7.75%
2017 854,640 510,223 344,418 2,469,311 25.46% 5.49% 8.59%
50
Table 3: Correlation matrix
This table shows the correlations between variables employed in this study. The descriptions of all variables are reported in Appendix A.
1 2 3 4 5 6 7 8 9 10 11 12 13 14
1 ROA 1.000
2 ROE 0.796 1.000
3 CPG 0.126 0.127 1.000
4 CPS 0.064 0.045 0.642 1.000
5 CEO gender -0.024 -0.021 -0.045 -0.024 1.000
6 LnCEO age 0.002 0.002 0.085 0.040 0.017 1.000
7 CEO duality 0.081 0.029 0.063 0.099 0.025 0.165 1.000
8 LnCEO tenure -0.062 -0.023 0.134 0.127 0.018 0.201 0.021 1.000
9 Board size -0.015 0.017 0.010 -0.047 0.070 0.036 -0.194 0.056 1.000
10 Board independence -0.012 -0.009 -0.007 -0.024 -0.043 0.024 0.122 -0.015 -0.458 1.000
11 leverage -0.376 -0.088 0.006 -0.066 0.028 0.010 -0.177 0.098 0.157 -0.020 1.000
12 Firm size -0.053 0.075 0.161 -0.115 0.027 0.146 -0.177 0.145 0.220 0.060 0.425 1.000
13 LnFirm age -0.110 -0.051 0.098 -0.018 -0.021 0.127 -0.077 0.148 -0.020 -0.004 0.163 0.192 1.000
14 Lsharerholder 0.103 0.114 -0.052 -0.057 -0.008 0.030 -0.039 -0.111 0.011 0.040 0.047 0.208 -0.163 1.000
51
Table 4: CEO pay disparity and firm performance.
This table shows the estimates of the OLS regression model, controlling for industry
and year effects, to examine the influence of CEO pay disparity on firm performance.
The regression specification is as follows:
Firm performance = 𝛼 + 𝛽1CEO pay disparity + 𝛽2CEO gender + 𝛽3LnCEO age +
𝛽4CEO duality + 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7Board independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽10Largest shareholder + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Dependent variable
Model 1
ROA
Model 2
ROE
Model 3
ROA
Model 4
ROE
CPG 0.029*** 0.053***
(10.478) (8.033)
CPS 0.034*** 0.067***
(6.235) (5.120)
CEO gender -0.003* -0.008 -0.004* -0.008*
(-1.645) (-1.607) (-1.778) (-1.714)
LnCEO age -0.000 -0.004 0.001 -0.003
(-0.023) (-0.416) (0.147) (-0.297)
CEO duality 0.002 0.004 0.002 0.004
(1.392) (1.375) (1.376) (1.349)
LnCEO tenure -0.002*** -0.004*** -0.002*** -0.003***
(-4.743) (-2.947) (-4.495) (-2.825)
LnBoard size 0.001 -0.011 0.001 -0.010
(0.253) (-1.408) (0.428) (-1.272)
Board independence -0.013 -0.035 -0.013 -0.035
(-1.394) (-1.590) (-1.404) (-1.595)
Leverage -0.088*** -0.074*** -0.087*** -0.073***
(-32.320) (-11.363) (-32.214) (-11.314)
Firm size 0.002** 0.009*** 0.003*** 0.010***
(2.386) (4.840) (3.339) (5.585)
LnFirm age -0.012*** -0.015* -0.013*** -0.016**
(-3.358) (-1.762) (-3.676) (-1.993)
Lsharerholder 0.061*** 0.161*** 0.060*** 0.161***
(12.021) (13.368) (11.963) (13.325)
Constant -0.361*** -0.818*** 0.035 -0.094
(-7.857) (-7.455) (1.432) (-1.587)
Observations 20,760 20,760 20,760 20,760
Adjusted R-squared 0.456 0.250 0.454 0.248
Industry-Year FE Yes Yes Yes Yes
52
Table 5: Determinants of CEO pay disparity.
This table displays the estimates of the basic propensity score model, controlling for
industry and year effects.
CEO pay disparity = 𝛼 + 𝛽1CEO duality + 𝛽2LnCEO age + 𝛽3LnCEO tenure +
𝛽4LnBoard size + 𝛽5 Board independence + 𝛽6Leverage + 𝛽7Firm size + 𝛽8LnFirm age
+ 𝛽9Largest shareholder + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Model 1 Model 2
Dependent variable CPG75 CPS75
CEO duality 0.241*** 0.295***
(5.550) (7.155)
LnCEO age 0.160 0.085
(1.106) (0.649)
LnCEO tenure 0.125*** 0.087***
(5.984) (4.416)
LnBoard size -0.025 -0.529***
(-0.223) (-5.178)
Board independence -0.693* -0.719**
(-1.873) (-2.177)
Leverage -0.752*** -0.259***
(-7.207) (-2.928)
Firm size 0.229*** -0.068***
(12.298) (-3.799)
LnFirm age 0.049 0.055
(0.859) (1.079)
Lshareholder -0.619*** -0.447***
(-4.607) (-3.562)
Constant -5.458*** 1.531**
(-7.109) (2.068)
Observations 20,487 20,701
Industry-Year FE Yes Yes
53
Table 6: CEO pay disparity and firm performance, PSM approach analysis.
Panel A reports t-test analysis of CEO pay disparity effects on firm performance. It
shows the different influence between the treatment group (CPG75/CPS75=1) and
control group (CPG75/CPS75=0) to ROA and ROE. Mean refers to the average firm
performance associated with the high or low CEO pay disparity. Difference is equal to
the mean of treatment minus the mean of control.
Panel B reports the results of propensity score matching approach analysis to address
selection issue. OLS regression model is employed to examine the effect of CEO pay
disparity on firm performance.
Firm performance = 𝛼 + 𝛽1CEO pay disparity + 𝛽2CEO gender + 𝛽3LnCEO age +
𝛽4CEO duality + 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7Board independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽10Largest shareholder + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Panel A: t-test analysis of CEO pay disparity effects on firm performance
CPG75 Treatment
Mean
Control
Mean
Difference
t stat
ROA 0.0572 0.0414 0.0158*** 16.18
ROE 0.0994 0.0692 0.0301*** 16.41
CPS75 Treatment
Mean
Control
Mean
Difference
t stat
ROA 0.0486 0.0433 0.0053*** 4.92
ROE 0.0799 0.0696 0.0103*** 4.79
Panel B: CEO pay disparity and firm performance, PSM approach analysis
Dependent variable
Model 1
ROA
Model 2
ROE
Model 3
ROA
Model 4
ROE
CPG75 0.008*** 0.014***
(7.401) (5.596)
CPS75 0.003** 0.008***
(2.369) (2.654)
CEO duality -0.000 -0.000 0.001 0.002
(-0.174) (-0.109) (0.647) (0.593)
LnCEO age 0.004 0.004 0.010* 0.009
(0.747) (0.385) (1.650) (0.698)
LnCEO tenure -0.002*** -0.004*** -0.002*** -0.006***
(-3.562) (-2.739) (-2.858) (-3.035)
LnBoard size 0.004 -0.016 0.002 -0.008
(0.939) (-1.584) (0.332) (-0.651)
Board independence 0.009 -0.014 -0.023 -0.029
(0.721) (-0.505) (-1.527) (-0.836)
54
Leverage -0.083*** -0.056*** -0.089*** -0.078***
(-18.887) (-5.621) (-21.151) (-7.995)
Firm size 0.004*** 0.011*** 0.001 0.011***
(3.450) (4.361) (1.099) (3.841)
LnFirm age -0.000 0.015 -0.014** -0.026**
(-0.041) (1.345) (-2.424) (-1.986)
Lshareholder 0.041*** 0.107*** 0.068*** 0.143***
(5.521) (6.397) (8.286) (7.574)
Constant -0.051 -0.216*** 0.037 -0.109
(-1.425) (-2.697) (0.955) (-1.223)
Observations 10,374 10,374 10,370 10,370
Adjusted R-squared 0.557 0.361 0.445 0.254
Industry-Year FE Yes Yes Yes Yes
55
Table 7: CEO pay disparity and firm performance: SOEs and private firms
This table shows the results of subsample analysis, controlling for industry and year
effects, to examine the influence of CEO pay disparity on firm performance in SEOs
and private firms, respectively.
Firm performance = 𝛼 + 𝛽1CEO pay disparity + 𝛽2CEO gender + 𝛽3LnCEO age +
𝛽4CEO duality + 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7Board independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽10Largest shareholder + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Panel A SOEs subsample
(1)
ROA
(2)
ROE
(1)
ROA
(2)
ROE
CPG 0.020*** 0.046***
(4.894) (4.083)
CPS 0.016* 0.045**
(1.882) (1.996)
CEO gender -0.003 -0.004 -0.003 -0.005
(-0.964) (-0.507) (-1.086) (-0.610)
LnCEO age 0.008 0.011 0.008 0.012
(1.420) (0.787) (1.502) (0.848)
CEO duality -0.001 0.001 -0.000 0.002
(-0.297) (0.267) (-0.230) (0.315)
LnCEO tenure -0.000 -0.001 -0.000 -0.000
(-0.552) (-0.349) (-0.036) (-0.033)
LnBoard size -0.009** -0.040*** -0.008** -0.040***
(-2.036) (-3.507) (-1.991) (-3.464)
Board independence -0.026** -0.090*** -0.027** -0.092***
(-2.197) (-2.807) (-2.269) (-2.858)
Leverage -0.118*** -0.107*** -0.118*** -0.108***
(-29.280) (-9.860) (-29.347) (-9.925)
Firm size 0.006*** 0.011*** 0.006*** 0.012***
(5.152) (3.533) (5.519) (3.844)
LnFirm age -0.011** -0.015 -0.013** -0.018
(-2.188) (-1.080) (-2.471) (-1.301)
Lsharerholder 0.022*** 0.062*** 0.022*** 0.061***
(3.132) (3.216) (3.060) (3.164)
Constant -0.314*** -0.701*** -0.027 -0.056
(-4.484) (-3.699) (-0.733) (-0.562)
Observations 9,615 9,615 9,615 9,615
Adjusted R-squared 0.482 0.278 0.481 0.277
Industry-Year FE Yes Yes Yes Yes
56
Panel B Private firms subsample
(1) (2) (1) (2)
ROA ROE ROA ROE
CPG 0.029*** 0.045***
(7.673) (5.835)
CPS 0.034*** 0.057***
(4.570) (3.770)
CEO gender 0.001 0.003 0.001 0.003
(0.450) (0.575) (0.404) (0.528)
LnCEO age -0.005 -0.018* -0.005 -0.017*
(-1.086) (-1.756) (-0.936) (-1.654)
CEO duality 0.003* 0.003 0.002 0.003
(1.652) (1.043) (1.586) (0.982)
LnCEO tenure -0.004*** -0.006*** -0.004*** -0.006***
(-5.167) (-3.624) (-5.221) (-3.700)
LnBoard size 0.012** 0.027*** 0.013*** 0.028***
(2.503) (2.653) (2.719) (2.815)
Board independence 0.008 0.035 0.009 0.037
(0.525) (1.149) (0.630) (1.226)
Leverage -0.055*** -0.039*** -0.055*** -0.038***
(-14.047) (-4.713) (-13.869) (-4.590)
Firm size -0.000 0.008*** 0.000 0.009***
(-0.295) (3.435) (0.279) (3.881)
LnFirm age -0.005 -0.006 -0.006 -0.007
(-1.064) (-0.579) (-1.190) (-0.665)
Lsharerholder 0.093*** 0.221*** 0.094*** 0.222***
(12.138) (13.922) (12.182) (13.953)
Constant -0.363*** -0.795*** 0.028 -0.179**
(-5.776) (-6.102) (0.798) (-2.450)
Observations 11,145 11,145 11,145 11,145
Adjusted R-squared 0.452 0.318 0.450 0.317
Industry-Year FE Yes Yes Yes Yes
57
Table 8: CEO pay disparity and firm performance: Pre and Post “pay ceiling”
regulation period
This table shows the results of subsample analysis, controlling for industry and year
effects, to examine the influence of the “pay ceiling” regulation on the relationship
between CEO pay disparity and firm performance in SEOs, private firms and SOEs
directly controlled by government bureaus, respectively.
Firm performance = 𝛼 + 𝛽1CEO pay disparity + 𝛽2CEO gender + 𝛽3LnCEO age +
𝛽4CEO duality + 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7Board independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽10Largest shareholder + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Panel A
SOEs subsample
Pre
period
Post
period
Pre
period
Post
period
05-14 15-17 05-14 15-17
ROA ROA ROA ROA
CPG 0.023*** 0.017**
(4.186) (2.101)
CPS 0.011 0.022
(1.138) (1.225)
CEO gender -0.005 -0.001 -0.006 -0.001
(-1.411) (-0.133) (-1.469) (-0.162)
LnCEO age 0.003 -0.042** 0.003 -0.041**
(0.454) (-2.414) (0.459) (-2.372)
CEO duality -0.000 0.006 0.000 0.006
(-0.070) (1.419) (0.007) (1.413)
LnCEO tenure 0.000 0.001 0.001 0.002
(0.459) (0.828) (1.034) (0.918)
LnBoard size -0.011** 0.021 -0.010** 0.021
(-2.091) (1.484) (-2.041) (1.475)
Board independence -0.024* 0.012 -0.025* 0.010
(-1.700) (0.332) (-1.741) (0.275)
Leverage -0.136*** -0.163*** -0.136*** -0.162***
(-26.861) (-10.098) (-26.903) (-10.066)
Firm size 0.008*** 0.027*** 0.008*** 0.027***
(5.060) (5.488) (5.265) (5.511)
LnFirm age -0.012* -0.017 -0.014** -0.017
(-1.853) (-0.311) (-2.161) (-0.311)
Lsharerholder 0.021** 0.018 0.021** 0.016
(2.407) (0.631) (2.395) (0.566)
Constant -0.358*** -0.590** -0.028 -0.355*
(-3.894) (-2.486) (-0.607) (-1.689)
Observations 7,156 2,459 7,156 2,459
Adjusted R-squared 0.530 0.522 0.529 0.521
Industry-Year FE Yes Yes Yes Yes
58
Panel B
Private firms subsample
Pre
period
Post
period
Pre
period
Post
period
05-14 15-17 05-14 15-17
ROA ROA ROA ROA
CPG 0.031*** 0.026***
(4.617) (4.967)
CPS 0.018* 0.059***
(1.662) (4.711)
CEO gender -0.001 -0.002 -0.001 -0.002
(-0.236) (-0.387) (-0.193) (-0.352)
LnCEO age 0.000 0.004 0.001 0.002
(0.041) (0.362) (0.151) (0.213)
CEO duality -0.002 0.001 -0.002 0.001
(-0.948) (0.265) (-0.853) (0.211)
LnCEO tenure -0.004*** -0.004** -0.004*** -0.004***
(-3.690) (-2.511) (-3.560) (-2.632)
LnBoard size 0.007 0.013 0.009 0.013
(1.132) (1.128) (1.384) (1.138)
Board independence -0.007 0.048 -0.004 0.047
(-0.371) (1.467) (-0.211) (1.456)
Leverage -0.042*** -0.080*** -0.042*** -0.081***
(-7.578) (-8.506) (-7.553) (-8.552)
Firm size -0.009*** 0.004 -0.008*** 0.005*
(-5.063) (1.563) (-4.643) (1.872)
LnFirm age -0.011 -0.056 -0.012* -0.056
(-1.611) (-1.615) (-1.794) (-1.611)
Lsharerholder 0.127*** 0.061*** 0.128*** 0.062***
(10.639) (2.952) (10.637) (2.991)
Constant -0.216** -0.306** 0.209*** 0.045
(-2.028) (-2.133) (4.019) (0.360)
Observations 6,532 4,613 6,532 4,613
Adjusted R-squared 0.488 0.575 0.486 0.574
Industry-Year FE Yes Yes Yes Yes
59
Panel C:
Directly controlled SOEs
Full
sample
Pre
period
Post
period
05-17 05-14 15-17
ROA ROA ROA
CPG 0.020*** 0.021*** 0.012
(4.379) (3.487) (1.429)
CEO gender -0.005 -0.008* -0.001
(-1.527) (-1.830) (-0.120)
LnCEO age 0.006 0.001 -0.045**
(1.075) (0.206) (-2.418)
CEO duality -0.001 -0.002 0.005
(-0.603) (-0.637) (1.076)
LnCEO tenure -0.001 0.000 0.002
(-0.978) (0.101) (1.202)
LnBoard size -0.007 -0.009* 0.036**
(-1.557) (-1.650) (2.271)
Board independence -0.033** -0.037** 0.031
(-2.554) (-2.368) (0.779)
Leverage -0.133*** -0.146*** -0.166***
(-29.387) (-26.289) (-9.512)
Firm size 0.006*** 0.007*** 0.029***
(4.787) (4.186) (5.511)
LnFirm age -0.017*** -0.017** -0.001
(-2.728) (-2.216) (-0.013)
Lsharerholder 0.029*** 0.029*** -0.006
(3.577) (2.900) (-0.202)
Constant -0.279*** -0.286*** -0.654**
(-3.661) (-2.841) (-2.490)
Observations 8,160 5,980 2,180
Adjusted R-squared 0.494 0.546 0.498
Industry-Year FE Yes Yes Yes
60
Table 9: CEO pay disparity and firm performance: does industry concentration
matter
This table shows the results of subsample analysis, controlling for industry and year
effects, to examine whether the positive relationship between CEO pay disparity and
firm performance is subject to industry concentration.
Firm performance = 𝛼 + 𝛽1CEO pay disparity + 𝛽2CEO gender + 𝛽3LnCEO age +
𝛽4CEO duality + 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7Board independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽10Largest shareholder + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Panel A: SOEs
Highly competitive
industry
Medium-concentrated
industry
Highly concentrated
industry
ROA ROA ROA
CPG 0.014* 0.022*** 0.015
(1.830) (3.884) (1.132)
CEO gender 0.012** -0.010** -0.003
(2.234) (-2.455) (-0.318)
LnCEO age 0.017* 0.018** -0.029
(1.746) (2.339) (-1.558)
CEO duality 0.006* -0.001 -0.002
(1.767) (-0.471) (-0.384)
LnCEO tenure 0.001 -0.000 -0.002
(1.006) (-0.417) (-1.115)
LnBoard size -0.009 -0.015** 0.017
(-1.129) (-2.573) (0.989)
Board independence -0.009 -0.012 -0.094**
(-0.465) (-0.694) (-2.155)
Leverage -0.119*** -0.106*** -0.185***
(-14.758) (-18.818) (-13.607)
Firm size 0.007*** 0.005*** 0.007
(3.139) (3.073) (1.603)
LnFirm age -0.004 -0.020** -0.039*
(-0.513) (-2.082) (-1.943)
Lsharerholder 0.035** 0.008 0.026
(2.470) (0.852) (0.967)
Constant -0.342*** -0.309*** -0.027
(-2.612) (-3.191) (-0.117)
Observations 2,778 5,160 1,677
Adjusted R-squared 0.531 0.494 0.524
Industry-Year FE Yes Yes Yes
61
Panel B: Private firms
Highly competitive
industry
Medium-concentrated
industry
Highly concentrated
industry
ROA ROA ROA
CPG 0.032*** 0.022*** 0.028***
(3.268) (4.441) (3.745)
CEO gender -0.007 0.002 0.004
(-0.848) (0.549) (0.654)
LnCEO age -0.014 0.001 -0.017
(-1.067) (0.168) (-1.524)
CEO duality 0.001 0.000 0.009***
(0.145) (0.049) (2.605)
LnCEO tenure -0.004* -0.003*** -0.005***
(-1.841) (-3.248) (-2.924)
LnBoard size 0.018 0.022*** 0.003
(1.451) (3.350) (0.254)
Board independence 0.058 0.016 -0.022
(1.497) (0.845) (-0.637)
Leverage -0.029*** -0.068*** -0.050***
(-2.678) (-11.647) (-5.375)
Firm size -0.015*** 0.003** -0.003
(-5.049) (2.015) (-0.863)
LnFirm age 0.008 -0.004 0.023*
(0.637) (-0.617) (1.914)
Lsharerholder 0.144*** 0.078*** 0.086***
(5.842) (7.490) (4.790)
Constant -0.144 -0.402*** -0.300**
(-0.842) (-4.713) (-2.219)
Observations 2,380 6,021 2,744
Adjusted R-squared 0.440 0.496 0.496
Industry-Year FE Yes Yes Yes
62
Table 10: CEO pay disparity and firm performance: does non-CEO executives’
age matter
This table shows the results of subsample analysis, controlling for industry and year
effects, to examine whether the positive relationship between CEO pay disparity and
firm performance is subject to the age of non-CEO executives.
Firm performance = 𝛼 + 𝛽1CEO pay disparity + 𝛽2CEO gender + 𝛽3LnCEO age +
𝛽4CEO duality + 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7Board independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽10Largest shareholder + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Average age of non-
CEO executives:
<=41 41<age<43 43<age<46 46<age<51 49<age<51 >=51
ROA ROA ROA ROA ROA ROA
CPG 0.007 0.038*** 0.035*** 0.026*** 0.030*** 0.011
(0.510) (3.389) (5.596) (4.068) (3.480) (1.340)
CEO gender -0.023** 0.010 0.004 -0.002 -0.018* 0.003
(-2.329) (1.296) (0.921) (-0.380) (-1.954) (0.425)
LnCEO age -0.027* -0.011 -0.009 -0.014 0.004 0.001
(-1.805) (-0.765) (-0.976) (-1.585) (0.288) (0.048)
CEO duality -0.001 0.001 0.000 0.001 0.006 0.010**
(-0.229) (0.131) (0.055) (0.363) (1.572) (2.343)
LnCEO tenure -0.006** 0.001 -0.004*** -0.003** -0.003** -0.004**
(-2.404) (0.381) (-3.223) (-2.264) (-2.276) (-2.387)
LnBoard size 0.016 -0.028** -0.001 -0.014* 0.036*** 0.003
(1.089) (-2.470) (-0.142) (-1.760) (3.300) (0.299)
Board independence -0.068 -0.037 -0.028 -0.018 0.039 0.021
(-1.542) (-1.066) (-1.284) (-0.863) (1.233) (0.679)
Leverage -0.040*** -0.096*** -0.077*** -0.089*** -0.150*** -0.073***
(-3.256) (-9.637) (-10.759) (-13.601) (-14.381) (-6.151)
Firm size -0.016*** 0.002 0.007*** 0.007*** 0.009*** 0.003
(-4.240) (0.545) (3.392) (3.733) (3.127) (0.983)
LnFirm age -0.031* -0.005 -0.024** -0.012 -0.013 -0.014
(-1.904) (-0.317) (-2.241) (-1.240) (-0.869) (-0.839)
Lsharerholder 0.139*** 0.099*** 0.066*** 0.057*** 0.076*** 0.034*
(5.642) (4.475) (5.189) (4.676) (4.414) (1.736)
Constant 0.480** -0.433** -0.500*** -0.353*** -0.625*** -0.153
(2.141) (-2.308) (-4.464) (-3.312) (-3.967) (-0.949)
Observations 2,240 2,988 4,938 5,354 3,152 2,088
Adjusted R-squared 0.454 0.522 0.568 0.486 0.562 0.592
Industry-Year FE Yes Yes Yes Yes Yes Yes
63
Table 11: CEO pay disparity and firm performance: does non-CEO executives’
gender matter
This table shows the results of subsample analysis, controlling for industry and year
effects, to examine whether the positive relationship between CEO pay disparity and
firm performance is subject to the gender of non-CEO executives.
Firm performance = 𝛼 + 𝛽1CEO pay disparity + 𝛽2CEO gender + 𝛽3LnCEO age +
𝛽4CEO duality + 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7Board independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽10Largest shareholder + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Panel A:
Female ratio within
non-CEO executives
<=10%
>10% and <25% >25% and <50% >=50%
ROA ROA ROA ROA
CPG 0.022*** 0.034*** 0.039*** 0.015
(4.977) (6.783) (4.143) (0.992)
CEO gender -0.010** 0.002 0.001 -0.011
(-2.480) (0.516) (0.219) (-1.165)
LnCEO age 0.000 -0.005 0.030** 0.030
(0.049) (-0.875) (2.287) (1.362)
CEO duality 0.002 0.002 0.000 0.010
(1.075) (0.779) (0.008) (1.438)
LnCEO tenure -0.002*** -0.001 -0.003* -0.010***
(-2.728) (-1.455) (-1.778) (-3.701)
LnBoard size 0.005 0.004 0.030*** 0.006
(1.012) (0.624) (2.583) (0.366)
Board independence 0.008 -0.023 -0.002 -0.010
(0.538) (-1.340) (-0.051) (-0.215)
Leverage -0.109*** -0.086*** -0.137*** -0.006
(-21.866) (-17.047) (-12.921) (-0.425)
Firm size 0.004*** 0.002 0.004 -0.010**
(3.375) (1.111) (1.243) (-2.120)
LnFirm age -0.013** -0.006 0.024* -0.052**
(-2.127) (-1.032) (1.759) (-2.242)
Lsharerholder 0.050*** 0.068*** 0.083*** 0.045
(5.916) (7.385) (3.970) (1.393)
Constant -0.319*** -0.442*** -0.833*** 0.091
(-4.210) (-5.299) (-5.032) (0.363)
Observations 8,705 8,009 2,666 1,380
Adjusted R-squared 0.492 0.485 0.539 0.518
Industry-Year FE Yes Yes Yes Yes
64
4. Essay two
Managerial pay disparity and earnings management: Evidence from
China
4.1 Introduction
It is an important research question whether pay disparity among the top management
team affects firm behaviours. Prior studies present inconclusive evidence regarding the
effects of managerial pay disparity on firm value and performance, but very few studies
focus on the impact of managerial pay disparity on firm earnings management activities.
This essay investigates the relationship between managerial pay disparity and earnings
management. More specifically, I examine whether and how the pay gap between the
CEO and other top executives influences corporate accrual-based earnings
manipulation.
Senior corporate management groups are responsible for firms’ day-to-day operations
and profitability. Besides, the nature of executive work requires a high degree of task
interdependence (Siegel & Hambrick, 2005). Thus, executive compensation schemes
are expected to influence the functioning of top management teams. In particular, the
managerial pay disparity is the key to the corporate remuneration structure that plays
an important role in the inner workings of the top management team (Bebchuk et al.,
2011).
The focus of this essay is to examine how pay disparity between the CEO and other top
executives affects firm accrual-based earnings management. Accounting information is
a critical element in the Chinese regulators’ administrative governance of listed firms
(Liu & Lu, 2007). For example, regulators will mark the companies as potential
delisting companies if they report net losses over three sequential years (Chen & Yuan,
2004; Liu & Lu, 2007). According to the tournament theory, a large managerial pay
disparity provides non-CEO executives with great tournament incentives to pursue the
promotion to be the next CEO (Lazear & Rosen, 1981). It is argued that a large
tournament prize for senior managers leads to extremely aggressive and competitive
behaviours (Siegel & Hambrick, 2005). Therefore, a large managerial pay disparity
may provide non-CEO executives with tournament incentives to engage in earnings
management.
65
Managerial pay disparity is addressed through two approaches in this study. The pay
gap between the CEO and other top executives is utilised as the first measure following
existing studies (Kale et al., 2009; Kini & Williams, 2012; Park, 2017). More
importantly, the pay gap between the CEO and the CFO is the other focus to explore
the impact of pay disparity on accrual-based earnings management. Jiang et al. (2010)
document that CEOs or CFOs are more likely to have sophisticated accounting and
finance expertise that is required for accrual-based earnings management. Hence, the
other non-CEO executives could have less capability to engage in accrual-based
earnings management than CFOs. CEOs are responsible for the strategic operations of
the firm, while CFOs have the primary responsibility in overseeing firms overall
financial reporting (Geiger & North, 2006). In this situation, the influence of CFOs over
the financial reporting process could be more important than that of other non-CEO
executives. Therefore, the pay gap between the CEO and the CFO is expected to play a
more important role in earnings management activities.
This study investigates the relationship between managerial pay disparity and accrual-
based earnings management in Chinese listed firms. China provides an ideal situation
to examine the impact of tournament effects on firms’ earnings management. In
Chinese markets, where accounting information is essential for regulatory controls,
corporate governance system portends to be inefficient and investor protection is weak.
Literature shows that earnings management that could harm shareholders’ benefits is
common in China (Firth et al., 2006; Liu & Lu, 2007).
My results show that the pay gap between the CEO and the CFO is negatively
associated with accrual-based earnings management. This finding indicates that a large
managerial pay gap provides CFOs tournament incentives that mitigate the accrual-
based earnings manipulation. CFOs need to consider and balance the benefits and costs
from engaging in accrual-based earnings management since they are ultimately
responsible for the quality of financial reporting. Feng et al. (2011) and Mian (2001)
document that CFOs undertake greater legal costs and bear potential higher loss of
reputation and wealth than that of CEOs in manipulating earnings. As a result, CFOs
appear to obtain fewer benefits and suffer greater loss from accounting manipulations
relative to CEOs. Further, a CFO’s career and promotion opportunities will be greatly
harmed if the company is found to have committed an accounting violation. By
66
considering that a large tournament prize incentivizes CFOs to work hard for the higher
rank in the top management team, CFOs could be more cautious and conservative to
engage in accrual-based earnings management.
In addition, the pay gap between the CEO and other top executives is not significantly
associated with accrual-based earnings management. It is consistent with the notion that
non-CEO top executives (exclude CFO) face higher costs of engaging in accrual-based
earnings management because they are less likely to have sophisticated accounting and
finance expertise (Baker, Lopez, Reitenga, & Ruch, 2019; Jiang et al., 2010). Overall,
a large pay gap between the CEO and the CFO is a useful governance mechanism that
can mitigate the accrual-based earnings management in China.
4.2 Literature review and hypothesis development
Earnings management is the use of accounting techniques to produce financial reports
that present an overly positive view of a company's business activities and financial
position to obtain some private gain (Schipper, 1989). In China, accounting information
is essential for regulatory controls. For example, the minimum ROE hurdles must be
met to gain approval for rights issues, and companies will be marked as potential
delisting firms if they report net losses over three sequential years. High ownership
concentration and state ownership are the main sources of agency conflicts in listed
firms, thus, controlling shareholders may manipulate earnings to fulfil certain goals
(Liu & Lu, 2007). Given the fact that the corporate governance system is weak and the
protection for investors or business transactions is poor, earnings management activities
are rife in Chinese markets (Liu & Lu, 2007). Firms should employ many incentive
mechanisms to ensure the consistency of managers’ interests and shareholders’ interests,
thereby, preventing managers manipulating reported earnings.
Tournament theory indicates that a large managerial pay gap provides other top
executives with a large tournament prize to incentivize hard work for advancement to
the CEO position (Kale et al., 2009; Lazear & Rosen, 1981). Furthermore, Siegel &
Hambrick (2005) suggest that a large tournament prize leads to extremely aggressive
and competitive behaviours. Hence, the promotion-based tournament incentives for
non-CEO executives could play an important role in earnings management. For
example, Healy (1985) finds that executives manage accruals to maximize bonus
payments. Besides, senior managers have financial incentives to increase their
67
performance-based and equity-based compensation by engaging in earnings
management (Bergstresser & Philippon, 2006; Jiang et al., 2010). If the pay gap
between the CEO and other top executives is large, non-CEO executives could be
motivated to engage in earnings manipulations for higher ranks and more salaries. Park
(2017) examines how managerial pay disparity affects firm earnings management
activities in the US-listed firms from 1994 to 2013. It is found that pay disparity
between the CEO and other top executives is positively associated with earnings
management. This positive relation is driven by short-term compensation rather than
long-term compensation. Overall, a large tournament prize motivates non-CEO
executives to compete extremely for more chances of becoming the next CEO.
Therefore, I have the following hypothesis:
H1: Pay disparity between the CEO and other top executives is positively
associated with accrual-based earnings management.
Accrual earnings management requires senior executives with accounting and finance
expertise, while this is more likely to be limited to CEOs and CFOs (Jiang et al., 2010).
Under this circumstance, the other executives could face higher costs in manipulating
accrual earnings activities (Baker et al., 2019). Besides, most top executives carry out
and oversee firms’ daily operational decisions, while CFOs have the ultimate
responsibility in overseeing firms’ overall financial reporting (Geiger & North, 2006).
The individual influences of CFOs over the financial reporting process are more
essential than that of the other senior executives (Feng et al., 2011; Jiang et al., 2010).
Consequently, most top executives could prefer to play roles in real earnings
management rather than accrual earnings management. I propose the following
hypothesis:
H2: Pay disparity between the CEO and other top executives is not associated with
accrual-based earnings management.
Given the fact that CFOs are primarily responsible for overseeing the quality of firms’
financial reporting, the CFOs’ incentives could play important roles in accrual earning
management. It is argued that CFOs in manipulation firms bear greater litigation risks
and undertake higher loss of reputation and wealth than do CEOs (Feng et al., 2011;
Mian, 2001). In this situation, CFOs appear to obtain fewer benefits and suffer greater
losses from accounting manipulations (Baker et al., 2019). According to the survey
68
evidence of Graham, Harvey, & Rajgopal (2005), CFOs prefer to engage in real
earnings management rather than accrual earning management to meet the earnings
goals. A large pay disparity between the CEO and the CFO provides CFOs with large
tournament incentives, thus, CFOs could be more cautious and conservative to engage
in accrual earnings management for the higher rank and salaries. I propose the
following hypothesis:
H3: Pay disparity between the CEO and the CFO is negatively associated with
accrual-based earnings management.
4.3 Sample and variable construction
4.3.1 Data
The initial sample of this study includes all Chinese companies listed in A-share
markets in the Shanghai and Shenzhen Stock Exchanges from 2005 to 2017 (the data
will be updated to 2018 and later). All data are collected from the China Listed Firms
Research Database of China Stock Market and Accounting Research (CSMAR). The
starting year of our sample is 2005 because the listed firms started to disclose the
compensation of top executives (including Chairman of the Board, CEO, and other top
executives) since 2005. Only the aggregate amount of payment to the top three
executives were disclosed in annual reports before 2005.
Following the prior literature, financial firms and special treatment (ST) firms are
excluded because of their unique accounting standards. We also remove observations
with missing information and delete the top and bottom percentile of observations. The
final sample includes 2,507 firms that consistent of 17,849 firm-year observations.
4.3.2 Variable construction
4.3.2.1 Measuring CEO pay disparity
I follow Kale et al. (2009) to measure the pay gap between the CEO and other top
executives. The first measure is CEOPG, which is defined as the natural logarithm of
the difference between CEO pay and the median pay of all other executives in the top
management team. The second measure is the CFOPG, which is defined as the natural
logarithm of the difference between CEO pay and CFO pay.
69
CEOPG = Ln (Total compensation of CEO - Median of total compensation of other
executives in the firm-year).
CFOPG = Ln (Total compensation of CEO - Total compensation of CFO in the firm-
year).
An executive's total compensation is the sum of salary, bonuses and other cash
compensation. This compensation does not include long-term incentives such as stock
options and restricted stocks, because these are rarely exercised in China.
4.3.2.2 Measuring accrual-based earning management
The Jones Model:
Following Jones (1991), I estimate the following cross-sectional models within each
industry and year.
𝑇𝐴𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1= 𝛽1
1
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝛽2
∆𝑅𝐸𝑉𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝛽3
𝑃𝑃𝐸𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝜀𝑖,𝑡 (1)
where i indexes firms and t indexes years. ASSETt−1 is total assets at the end of year t−1;
ΔREVt is the change in sales revenue from year t−1 to t; and PPEt is the gross value of
property, plant, and equipment at the end of year t. The composition of total accruals
(TAi,t) is as follows: TAi,t = [ΔCurrent Assetsi,t – ΔCashi,t] – [ΔCurrent Libilitiesi,t] –
Depreciation and Amortization Expensesi,t. The change (Δ) is computed between time
t and time t-1. It is required at least 10 observations to perform each cross-sectional
estimation.
Then, the Jones Model for nondiscretionary accruals is:
𝑁𝐷𝐴𝑖,𝑡 = 𝛽11
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝛽2
∆𝑅𝐸𝑉𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝛽3
𝑃𝑃𝐸𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1 (2)
Finally, firm-year-specific discretionary accruals are calculated as:
𝐷𝐴𝑖,𝑡 =𝑇𝐴𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1− 𝑁𝐷𝐴𝑖,𝑡 (3)
The Modified Jones Model:
My second proxy for earnings management is the discretionary accruals measure of
Dechow, Sloan, & Sweeney (1995). The modification is designed to eliminate the
conjectured tendency of the Jones Model to measure discretion-nondiscretionary
70
accruals with error when discretion is exercised over revenues. To construct this
measure, I first estimate the following model within each industry and year.
𝑇𝐴𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1= 𝛽1
1
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝛽2
∆𝑅𝐸𝑉𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝛽3
𝑃𝑃𝐸𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝜀𝑖,𝑡 (4)
where i indexes firms and t indexes years. ASSETt−1 is total assets at the end of year t−1;
ΔREVt is the change in sales revenue from year t−1 to t; and PPEt is the gross value of
property, plant, and equipment at the end of year t. The composition of total accruals
(TAi,t) is as follows: TAi,t = [ΔCurrent Assetsi,t – ΔCashi,t] – [ΔCurrent Libilitiesi,t] –
Depreciation and Amortization Expensesi,t. The change (Δ) is computed between time
t and time t-1. It is required at least 10 observations to perform each cross-sectional
estimation.
Next, I use the following model and the estimated coefficients from equation (4) to
compute the nondiscretionary accruals (NDAi,t):
𝑁𝐷𝐴𝑖,𝑡 = 𝛽11
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝛽2
(∆𝑅𝐸𝑉𝑖,𝑡−∆𝐴𝑅𝑖,𝑡)
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1+ 𝛽3
𝑃𝑃𝐸𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1 (5)
Following Dechow et al. (1995), the change in accounts receivable is subtracted from
the change in sales revenue as credit sales might also provide a potential opportunity
for accounting distortion.
Finally, the firm-year-specific discretionary accruals are calculated as
𝐷𝐴𝑖,𝑡 =𝑇𝐴𝑖,𝑡
𝐴𝑆𝑆𝐸𝑇𝑖,𝑡−1− 𝑁𝐷𝐴𝑖,𝑡 (6)
4.3.2.3 Control variables
I include the characteristics of CEOs and CFOs (e.g. age, gender and tenure), firm size,
board size, board independence, leverage, largest shareholder ownership, firm age and
ROA as control variables. Appendix A provides definitions for all variables.
4.3.3 Descriptive Statistics and correlation matrix
Table 1 provides the basic summary statistics of the variables employed in this study.
The discretionary accruals generated from Jones Model and Modified Jones Model are
similar, shown as 0.0066 and 0.0074, respectively. The mean CEO compensation is
607,484 RMB that is significantly greater than the mean CFO compensation and the
71
average median-compensation of non-CEO executives. The mean pay gap between the
CEO and non-CEO executives is 209,664 RMB, and the mean pay gap between the
CEO and the CFO is 217,647 RMB. In addition, 94.61% of CEOs are male, while 70.67%
of CFOs are male. The average proportion of independent directors is 36.81%, which
satisfies the requirements of the China Securities Regulatory Commission (CSRS) that
independent directors must account for at least one-third of the total numbers on boards
for all listed firms.
Insert Table 1 here
Table 2 reports the time trend of managerial pay disparity, top executives’
compensations and accrual-based earnings management measures included in this
study. Both the executives’ compensations and managerial pay gaps have a significant
increase from 2005 to 2017.
Insert Table 2 here
Table 3 reports the correlation matrix between the variables. The correlation
coefficients do not indicate any serious multicollinearity problems.
Insert Table 3 here
4.3.4 Empirical analysis
4.3.4.1 Managerial pay disparity and accrual-based earnings management
I conduct the following regression to investigate the influence of managerial pay
disparity on accrual-based earnings management. Table 4 contains the baseline
regression results after controlling for industry and year effects. Accrual-based earnings
management is measured by both discretionary accruals (DA1) and modified
discretionary accruals (DA2). Managerial pay disparity is measured by CFOPG and
CEOPG. CFOPG is employed in Panel A and CEOPG is used in Panel B.
Accrual-based earning management = 𝛼 + 𝛽1CFOPG/CEOPG + 𝛽2CEO gender +
𝛽3LnCEO age + 𝛽4CEO duality+ 𝛽5CEO tenure + 𝛽6CFO gender + 𝛽7LnCFO age
+𝛽8CFO director + 𝛽9LnCFO tenure + 𝛽10LnBoard size + 𝛽11Board independence +
𝛽12Leverage + 𝛽13Firm size + 𝛽14LnFirm age + 𝛽15Largest shareholder + 𝛽16ROA+ 𝜀
(7)
72
The results of Models 1 and 2 in Panel A show that the coefficients on CFOPG are both
-0.0297 and they are significant at the 5% level. It indicates that the pay gap between
the CEO and the CFO is negatively associated with accrual-based earnings management.
CFOs are less likely to engage in earnings manipulations in firms with a large pay gap
between the CEO and the CFO. As a large tournament prize induces CFOs to seek
higher ranks and more salaries, they could be more cautious and conservative in
managing accruals. This could be due to the reason that CFOs appear to obtain fewer
benefits and suffer greater losses of wealth and reputation from accounting
manipulations (Feng et al., 2011). A CFO’s career and promotion opportunities will be
greatly damaged if the company is found to have committed an accounting fraud. This
result is consistent with Hypothesis 3 that a large pay gap between the CEO and the
CFO can mitigate the accrual-based earnings management.
Models 1 and 2 in Panel B document that CEOPG is insignificantly associated with
accrual-based earnings management, which is in line with Hypothesis 2. It indicates
that the pay gap between CEO and other top executives does not play a role in
mitigating earnings manipulation. Most non-CEO top executives are less capacity to
influence earnings manipulation compared with CFOs. Non-CEO executives may have
greater influence on real earnings management that is more relative to their job because
they oversee firms’ daily operational decisions.
Overall, we have evidence that the large pay disparity between the CEO and the CFO
serves as a governance mechanism to mitigate the accrual-basing earnings management.
Insert Table 4 here
4.4 Future analysis
This section lists the future tests which are planned but not done yet.
1. Investigate the relation between managerial pay disparity and real earnings
management.
2. PSM test. Given the importance of endogeneity concerns, it is necessary to conduct
the propensity score matching sample test.
3. Discover the different influence of CEOs and CFOs on earnings management.
4. Other robustness checks.
73
4.5 Appendix
Appendix A: Variable definitions
This appendix presents the definition of the variables used in this study
Variables Definition
DA1 The residual of Jones model.
DA2 The residual of modified Jones model.
CFO pay gap The difference between the CEO pay and the CFO pay.
CFOPG The natural logarithm of CFO pay gap.
CEO pay gap The difference between the CEO pay and the median pay of all
other executives in the top management team.
CEOPG The natural logarithm of CEO pay gap.
LnCEO age The natural logarithm of the CEO's age.
CEO duality A dummy variable equals 1 if CEO and Chairman of the board
are the same person, and 0 otherwise.
CEO Gender A dummy variable equals 1 if CEO is male, and 0 otherwise.
LnCEO Tenure
The natural logarithm of the number of years that the CEO has
served as CEO in the sample firm.
LnCFO age The natural logarithm of the CFO's age.
CFO director A dummy variable equals 1 if CFO also hold the position of
board of director, and 0 otherwise.
CFO Gender A dummy variable equals 1 if CFO is male, and 0 otherwise.
LnCFO Tenure
The natural logarithm of the number of years that the CFO has
served as CFO in the sample firm.
LnBoard size The natural logarithm of total number of directors.
Board independence Number of independent directors divided by number of
directors.
Firm size The natural logarithm of total assets.
Leverage The book value of debt divided by book value of total asset.
Largest shareholder Percentage of shares owned by the largest shareholder.
LnFirm age The natural logarithm of the number of years (plus one) since
incorporation.
ROA Net income divided by total assets in the year t.
74
4.6 Tables
Table 1: Summary statistics
This table reports the summary statistics of the variables employed in the analysis. The
sample comprises 17,849 firm-years observations from 2005 to 2017. The descriptions
of all variables are reported in Appendix A.
Variable Obs Mean SD P25 Median P75
Panel A: Accrual EM
DA1 17,849 0.0066 0.1278 -0.0536 0.0048 0.0644
DA2 17,849 0.0074 0.1284 -0.0530 0.0055 0.0655
Panel B: Executive compensation
CEO pay 17,849 607,484 636,778 260,000 449,600 729,400
CFO pay 17,849 389,837 382,619 175,000 299,000 485,000
Median-other top executives 17,849 398,257 354,584 190,000 311,500 498,550
Panel C: Executive pay gap
CEO pay gap 17,849 209,227 401,930 46,300 114,400 248,350
CFO pay gap 17,849 217,647 416,221 46,000 120,000 266,400
Panel D: Executive characteristics
CEO gender 17,849 94.61% 22.58% 1 1 1
CFO gender 17,849 70.67% 45.53% 0 1 1
CEO age 17,849 48.19 6.44 44 48 52
CFO age 17,849 44.84 6.49 40 44 49
CEO duality 17,849 21.20% 40.87% 0 0 0
CFO director 17,849 25.37% 43.51% 0 1 1
CEO tenure 17,849 4.02 2.92 2 3 5
CFO tenure 17,849 4.22 3.04 2 3 6
Panel E: Control variables
Board size 17,849 8.74 1.22 8 9 9
Board independence 17,849 36.81% 5.40% 33.33% 33.33% 40.00%
Leverage 17,849 0.47 0.23 0.30 0.47 0.62
Firm size 17,849 21.96 1.31 21.04 21.80 22.70
LnFirm age 17,849 2.67 0.39 2.48 2.71 2.94
Lshareholder 17,849 36.04% 15.22% 23.97% 34.05% 46.75%
ROA 17,849 3.73% 5.99% 1.33% 3.44% 6.30%
75
Table 2: Time trend
This table displays the time trend of managerial pay disparity, top executives’
compensation and accrual-based earnings management measures. The descriptions of
all variables are reported in Appendix A.
Year DA1 DA2 CEO pay CFO pay CFO pay gap Median-VPs CEO pay gap
2005 -0.0003 -0.0005 252,666 160,306 92,360 168,132 84,534
2006 0.0079 0.0069 288,751 177,891 110,859 188,356 100,395
2007 0.0070 0.0061 380,877 234,760 146,116 243,849 137,028
2008 -0.0021 -0.0014 443,019 274,881 168,138 287,074 155,945
2009 -0.0005 0.0008 462,171 289,119 173,052 305,948 156,223
2010 0.0169 0.0164 561,605 349,615 211,990 362,450 199,155
2011 0.0159 0.0167 595,807 376,270 219,537 390,528 205,279
2012 0.0062 0.0067 617,556 389,948 227,609 403,990 213,566
2013 0.0096 0.0097 650,659 415,952 234,707 426,674 223,984
2014 0.0105 0.0124 684,974 441,284 243,690 448,546 236,428
2015 0.0016 0.0031 719,093 466,718 252,376 472,073 247,020
2016 0.0033 0.0056 821,955 536,574 285,381 536,245 285,709
2017 0.0030 0.0047 926,337 631,427 294,910 620,521 305,816
76
Table 3: Correlation matrix
This table shows the correlations between variables employed in this study. The descriptions of all variables are reported in Appendix A.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
1 DA1 1.000
2 DA2 0.997 1.000
3 CFO PG 0.021 0.024 1.000
4 CEO PG 0.027 0.029 0.902 1.000
5 CEO gender -0.009 -0.010 -0.068 -0.059 1.000
6 LnCEO age -0.012 -0.012 0.089 0.103 0.019 1.000
7 CEO duality -0.004 -0.002 0.066 0.073 0.018 0.161 1.000
8 LnCEO tenure -0.012 -0.013 0.146 0.153 0.005 0.255 0.078 1.000
9 CFO gender -0.007 -0.007 -0.042 -0.025 0.039 0.025 -0.038 0.002 1.000
10 LnCFO age 0.001 0.000 -0.030 0.013 0.020 0.167 -0.047 0.094 -0.023 1.000
11 CFO director 0.011 0.011 -0.073 -0.017 0.015 0.018 0.079 0.031 0.021 0.099 1.000
12 LnCFO tenure -0.001 -0.003 -0.019 0.029 0.029 0.100 -0.069 0.291 0.017 0.306 0.105 1.000
13 LnBoard size 0.016 0.013 0.014 0.010 0.070 0.039 -0.171 0.029 0.034 0.063 0.055 0.067 1.000
14 Board independence -0.004 -0.003 -0.018 -0.006 -0.041 0.025 0.104 -0.013 0.007 0.013 -0.061 -0.025 -0.444 1.000
15 Leverage -0.131 -0.132 -0.015 0.001 0.023 0.005 -0.138 -0.001 0.053 0.032 -0.011 0.046 0.122 -0.022 1.000
16 Firm size 0.023 0.023 0.151 0.176 0.028 0.155 -0.138 0.064 0.061 0.186 -0.029 0.124 0.214 0.053 0.336 1.000
17 LnFirm age -0.002 -0.002 0.072 0.100 -0.019 0.119 -0.067 0.089 0.007 0.144 0.016 0.144 -0.039 0.013 0.183 0.180 1.000
18 Lsharerholder 0.002 0.002 -0.052 -0.053 -0.011 0.027 -0.057 -0.080 0.035 0.025 -0.041 -0.025 0.023 0.028 0.026 0.242 -0.155 1.000
19 ROA 0.169 0.174 0.132 0.130 -0.029 0.007 0.039 0.040 -0.022 -0.009 -0.006 0.009 0.015 -0.021 -0.369 0.038 -0.093 0.088 1.000
77
Table 4: Managerial pay disparity and accrual-based earnings management.
Panel A shows the estimates of the OLS regression model, controlling for industry and
year effects, to examine the influence of CFO pay gap on accrual-based EM. The
regression specification is as follows:
Accrual-based earnings management = 𝛼 + 𝛽1CFOPG+ 𝛽2CEO gender + 𝛽3LnCEO
age + 𝛽4CEO duality+ 𝛽5CEO tenure + 𝛽6CFO gender + 𝛽7LnCFO age +𝛽8CFO
director + 𝛽9LnCFO tenure + 𝛽10LnBoard size + 𝛽11Board independence +
𝛽12Leverage + 𝛽13Firm size + 𝛽14LnFirm age + 𝛽15Largest shareholder + 𝛽16ROA+ 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
Panel B reports the estimates of the OLS regression model, controlling for industry and
year effects, to examine the effect of CEO pay gap on accrual-based EM. The regression
specification is as follows:
Accrual-based earnings management = 𝛼 + 𝛽1CEOPG+ 𝛽2CEO gender + 𝛽3LnCEO
age + 𝛽4CEO duality + 𝛽5LnCEO tenure + 𝛽6LnBoard size + 𝛽7Board independence +
𝛽8Leverage + 𝛽9Firm size + 𝛽10LnFirm age + 𝛽11Largest shareholder + 𝛽12ROA + 𝜀
The superscripts *, **, and *** indicate significance at the 90%, 95% and 99%
confidence levels, respectively.
78
Panel A: CFO pay gap and accrual-based earnings management.
Model 1 Model 2
Dependent variable DA1 DA2
CFOPG -0.027** -0.027**
(-2.130) (-2.092)
CEO gender -0.006 -0.007
(-0.921) (-0.996)
LnCEO age 0.001 0.002
(0.097) (0.193)
CEO duality 0.002 0.002
(0.524) (0.451)
LnCEO tenure -0.003* -0.003*
(-1.774) (-1.948)
CFO gender -0.004 -0.005
(-1.225) (-1.272)
LnCFO age -0.005 -0.006
(-0.403) (-0.500)
CFO director 0.007* 0.008**
(1.957) (2.145)
LnCFO tenure 0.000 -0.000
(0.100) (-0.079)
LnBoard size 0.006 0.005
(0.566) (0.482)
Board independence 0.013 0.010
(0.416) (0.332)
Leverage -0.168*** -0.167***
(-19.965) (-19.797)
Firm size 0.008*** 0.009***
(3.548) (4.081)
LnFirm age 0.023 0.024*
(1.632) (1.689)
Lsharerholder -0.013 -0.012
(-0.807) (-0.758)
ROA 0.327*** 0.339***
(15.012) (15.527)
Constant 0.236 0.203
(1.131) (0.969)
Observations 17,849 17,849
Adjusted R-squared 0.072 0.074
Industry-Year FE Yes Yes
79
Panel B: CEO pay gap and accrual-based earnings management.
Model 1 Model 2
Dependent variable DA1 DA2
CEOPG -0.014 -0.013
(-1.032) (-0.915)
CEO gender -0.006 -0.006
(-0.837) (-0.914)
LnCEO age 0.001 0.002
(0.049) (0.137)
CEO duality 0.002 0.002
(0.553) (0.497)
LnCEO tenure -0.003** -0.004**
(-1.960) (-2.187)
LnBoard size 0.007 0.006
(0.692) (0.609)
Board independence 0.013 0.010
(0.415) (0.321)
Leverage -0.167*** -0.166***
(-19.917) (-19.744)
Firm size 0.008*** 0.009***
(3.358) (3.873)
LnFirm age 0.023* 0.024*
(1.670) (1.718)
Lsharerholder -0.013 -0.012
(-0.803) (-0.742)
ROA 0.326*** 0.338***
(14.943) (15.454)
Constant 0.032 -0.022
(0.147) (-0.099)
Observations 17,849 17,849
Adjusted R-squared 0.072 0.073
Industry-Year FE Yes Yes
80
5. Essay three
Managerial pay disparity and firm decision-making and output: Asia-
Pacific study
5.1 Introduction
Corporate governance mechanisms influence firm decision-making and output.
Managerial pay disparity has become one of the most significant and hot corporate
governance topics in recent years. Prior literature focuses on whether and how pay
disparity between the CEO and other top executives plays a role in firm performance
and behaviours, while inconclusive evidence is presented so far. Besides, most of the
existing studies in this area are conducted utilising data from Western industrialised
societies, especially the US market. This essay will examine the influence of managerial
pay disparity on firm decision-making and output by conducting a cross-country study.
The economies I intend to investigate include China, Japan, South Korea, and
Singapore.
The impact of corporate governance mechanism on firm outcomes could be shaped by
institutional settings of the countries where the firms come from. It is suggested that
the pay disparity between the CEO and non-CEO executives reflects a firm’s leadership
style: team leadership or dominant leadership (Bebchuk et al., 2011). Thomas (2004)
argues that the CEOs are more powerful and be paid more in firms with dispersed
ownership structure than the CEOs in shareholder-control dominated firms in the US.
Aoki (1990) documents that the company's decision-making depends more on the co-
operation of all senior managers than the CEO himself in Japanese firms. On the
contrary, the CEOs could play a more important role than other executives in decision-
making in US firms. This is due to the fact that US firms’ ownership structure is more
separated, while the Japanese firms have relatively higher ownership concentration
(Aoki, 1990). Thus, the efficiency of managerial pay disparity could be subject to the
ownership structure in different countries.
Corporate compensation structure is mainly decided by the independent remuneration
committees of the board (Bebchuk & Fried, 2003). In particular, the independent
remuneration committee is mainly composed of independent directors. Thus, outsiders
could play an important role in reviewing and monitoring the compensation of top
81
executives. A large managerial pay disparity reflects the strong bargaining power of a
CEO relative to the board (Bebchuk & Fried, 2003; Dai, Kong, & Xu, 2017). It is
expected that the role of managerial pay disparity is subject to the effectiveness of the
board. For example, corporate boards in the US are outsider-dominated, which focuses
on the monitoring and advising role of independent directors. Whereas Japanese
corporate boards are insider-dominated, and one potential reason is their top
management team might be afraid to hear the suggestions and criticism from outside
directors (ASFRC, 2018). In this situation, powerful CEOs could lead to more agency
problems in firms that the monitoring roles of boards are not very effective. China has
many state-owned listed firms thus the government would affect the decision-making
of firms in different ways. China is similar to many other emerging-market countries in
that it has a concentrated corporate ownership structure (Jiang et al., 2010), and the
corporate governance is significantly weaker than that in the U.S. and other developed
countries (Allen et al., 2005). What’s more, Korea’s corporate governance is very poor
such as the collusive ties between businessmen and bureaucrats and politicians, and
unfair business transactions and practices (ASFRC, 2017). In particular, more than 95%
of Korean listed firms are controlled by families including the Chaebols. The powerful
Chaebol families can control the allocation of corporate resources even if they just hold
small stake‐holdings in the groups. Singapore is very unique among Asian countries.
According to Transparency International (2013), Singapore’s corporate governance
system has been consistently rated as one of the most political transparent and least
corrupt governments in the world. As a result, the effect of managerial pay disparity on
firm decision-making and output could be subject to different institutional settings.
In addition, the legal system is another important aspect to be considered when
researching the effectiveness of corporate governance mechanisms. China, Korea, and
Japan belong to the Civil Law System, while Singapore belongs to the Common Law
System. Porta, Lopez-De-Silanes, Shleifer, & Vishny (2002) suggest that strong legal
protection for investors (shareholders and creditors) could effectively improve
corporate governance. In particular, the valuation of companies in countries with better
shareholder protection is higher than those with a lower level of shareholder protection.
Given the fact that investor protection is poor in the Chinese market (Feng et al., 2011;
Firth et al., 2006), the efficiency of managerial pay disparity could subject to the
investor protection as well. Overall, a cross-economy study could address how
82
institutional settings and legal systems affect the role of managerial pay disparity, which
is still a research challenge in the relevant literature.
5.2 Literature review and hypothesis development
Prior studies mainly focus on the relation between managerial pay disparity and firm
performance. The inconclusive evidence is driven by the national settings. For example,
Bebchuk et al. (2011) document that CEO pay disparity measured as CPS is negatively
associated with firm performance and value in US. A high CPS reflects the relative
power and dominance of CEOs to other top executives. With larger CEO pay disparity,
the CEO has more incentives to protect their self-interests such as financial wealth and
career security. Thus, a powerful CEO is associated with more CEO entrenchment and
more agency problems that harm shareholders’ benefits (Adams et al., 2005; Landier et
al., 2012).
In contrast, large pay disparity between the CEO and non-CEO executives may not
reflect the CEO power but the CEO managerial talents. CEOs with outstanding abilities
and skills can be rewarded relatively higher salary within the top management team.
For instance, Al-Najjar et al. (2016) find that CPS is positively associated with
corporate performance in UK listed firms from 2003 to 2009. They document that CPS
is higher in firms with better corporate governance disclosure, indicating that well-
governed companies attract high talented CEOs. This is the evidence showing the
influence of institutional background on the role of managerial pay disparity. UK public
listed firms developed strengthened internal governance and established relative
independent remuneration committees. Thus, high CEO pay disparity measured as CPS
reflects the managerial talents of CEOs in UK.
In addition, managerial pay disparity is reflective of the tournament effects. Kale et al.
(2009) find that the compensation gap between the CEO and other top executives is
significantly and positively associated with firm value and accounting performance. It
is consistent with the tournament theory that a large CEO pay disparity provides
promotion-based tournament incentives for non-CEO executives, leading to greater
efforts to increase the promotion chances of becoming the next CEO (Lazear & Rosen,
1981). What’s more, Burns et al. (2017) conduct a cross-country sample to examine the
CEO tournament structure. A positive relationship is found between CEO pay disparity
and firm value after controlling for endogeneity. It is suggested that the tournaments
83
are an essential incentive mechanism to incentivise top executives and further lead to
enhanced corporate performance. However, the roles of tournament incentives are
systematically driven by firm and country cultural characteristics (Burns et al., 2017).
Therefore, it is expected that the effects of managerial pay disparity on firm decision-
making and output vary from the institutional settings and legal systems. The above
discussions lead to my hypothesis:
H1: The effects of managerial pay disparity on firm decision-making and output
vary across countries.
84
6. Proposed timeline for the completion of Dissertation
Schedule Task
July 2020
August 2020 – December 2020
January 2021 – October 2021
November 2021 – August 2022
September 2022
October 2022
Ph.D. confirmation
Complete essay one
Complete essay two
Complete essay three
Submit draft copy of the dissertation
Submit final bound copy of dissertation
85
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