Corporate Governance and Stock Option Vesting Conditions: Evidence from Australia
Xin Qu
Department of Accounting, Finance and Economics
Griffith Business School, Griffith University
Email: [email protected]
Majella Percy*
Department of Accounting, Finance and Economics
Griffith Business School, Griffith University
Email: [email protected]
Fax: +61 7 3735 3719
Fang Hu
Department of Accounting, Finance and Economics
Griffith Business School, Griffith University
Email: [email protected]
Fax: +61 7 3735 3719
Jenny Stewart
Department of Accounting, Finance and Economics
Griffith Business School, Griffith University
Email: [email protected]
Fax: +61 7 3735 3719
June 2014
*Corresponding Author
Corporate Governance and Stock Option Vesting Conditions: Evidence from Australia
Abstract
This paper investigates the role of corporate governance in designing the vesting conditions of
executive stock options. Using observations from the 250 largest non-financial Australian firms
during 2003-2007, we find that a number of observable features of strong corporate governance are
positively associated with the length of the vesting period, including board independence, CEO
duality, CEO age, and the use of Big 4 auditors. The result suggests that better-governed firms
prefer longer time-vesting options to extend the incentive horizon of executives. We also find that
stronger corporate governance leads to a higher propensity to employ performance-based vesting
conditions, with the aim to provide greater incentives in improving firms’ accounting and stock
market performance. In particular, well-governed firms use stock-based performance hurdles to a
greater extent than accounting-based hurdles, unless a Big Four auditor is employed. These results
hold after controlling for other firm characteristics, and also stay robust with respect to additional
tests. Overall, our study agrees with the predictions of agency theory, and indicates that corporate
governance plays a vital role in the design of stock option vesting conditions.
Key words: Executive stock options; Vesting conditions; Corporate governance
JEL classification: M40, M41
Corporate Governance and Stock Option Vesting Conditions: Evidence from Australia
1. Introduction
Stock options are often granted to senior executives as a means of aligning managers’
incentives with shareholders’ wealth. Typically, executive stock options (hereafter ESOs) are
subject to certain vesting conditions that restrict executives from exercising their rights (to
receive company shares) until specific requirements are satisfied.1 Traditionally, firms impose
restrictions on the length of executives’ service period ranging from a few months to several
years, which represents the minimum period over which the option grant provides incentives.
ESOs are, hence, perceived as ‘golden hand-cuffs’ due to this contract feature of employee
retention (Taylor, 1994). Over the past decade, performance-based vesting conditions have
been increasingly implemented to make option vesting conditional on the achievement of
performance targets. This type of vesting condition provides executives with strong incentives
and enhances the link between pay and performance.
The association between corporate governance and executive compensation has been
studied in various institutional settings (Conyon, 1997; Core et al., 1999; Kang et al., 2006;
Ozkan, 2007; Sapp, 2008; Bebchuk et al., 2010). The main objective of this study is to
investigate corporate governance determinants in setting the specific design features of ESOs,
in particular, the vesting conditions. Some studies have claimed that poorly-governed firms are
more likely to design equity contracts that favour their top executives (Brown and Lee, 2010;
Sautner and Weber, 2011). As such, weaker governance gives executives relatively more power
vis-à-vis the board, allowing them to influence the design of compensation. As suggested by
the Australian Securities Exchange (ASX) (2014), strong corporate governance encourages
optimisation of firm performance and increases accountability by restricting opportunistic
managerial behaviour. It is expected that stronger corporate governance could lead to better
1
Vest means to become an entitlement (AASB, 2013).
1
goal alignment of managers and shareholders when designing ESO contracts. Accordingly, this
study attempts to answer three research questions: (1) Are firms with stronger corporate
governance more likely to design ESOs with longer time-vesting features? (2) Are firms with
stronger corporate governance more likely to attach performance hurdles to ESOs? (3) What
particular type of performance hurdle is preferred by firms with stronger corporate governance?
These research questions are of significant interest to corporate stakeholders concerned with
executive incentives and firm performance.
Our research is motivated from three dimensions. Firstly, stock option compensation has
become increasingly important in providing executive incentives. Though ESOs have been
used substantially, investors and regulators have expressed concerns that such contract
mechanisms may encourage managerial self-serving behaviour (Bebchuk and Fried, 2003;
Cheng and Warfield, 2005; Bergstresser and Philippon, 2006). As a practical matter, in our
sample of the 250 largest Australian firms during 2003-2007, all the ESO grants are
time-vesting and more than 80 per cent have performance hurdles attached. These vesting
conditions specifically extend the horizon of incentives, which may lead to improvements in
firm performance. In parallel, researchers are motivated to focus on the theoretical impetus in
regard to this matter. Secondly, the design of vesting conditions has drawn increasing attention
from the academic community. In Australia, AASB 2 Share-based Payment (2004) has
required firms to expense the fair value of ESOs over the vesting period. A concern has been
expressed that ESO vesting conditions might not provide sufficiently strong financial
incentives since AASB 2 directly links vesting features to recognised compensation expense.
However, only a few recent studies in the United States (US) and United Kingdom (UK) have
considered the design of vesting conditions with regard to various firm determinants (Cadman
et al., 2013; Bettis et al., 2010; Qin, 2012). Our study aims to provide extended and/or
comparable evidence with the focus on corporate governance determinants. Thirdly, we are
2
also motivated to explore the design features of ESOs in an Australian context. Most
compensation research has been based on US data where little variation exists in the use of
ESOs. US firms generally offer some form and level of ESOs, as one of the four fundamental
components of executive compensation (Hall and Liebman, 1998). In comparison, a
considerable number of Australian firms do not grant ESOs consistently in every year and the
time-vesting patterns are relatively stable. Furthermore, Australia survived the Global
Financial Crisis much better than the US or Europe, which has been partially attributed to
control systems or to corporate governance strength (Moloney and Hill, 2012). Accordingly,
Australia provides an interesting institutional environment to study the link between corporate
governance and the design of ESOs.
Using a sample of the Australia’s 250 largest listed companies from 2003 to 2007, our
study provides evidence that corporate governance plays an important role in the design of
ESO vesting conditions. The major findings include: (1) firms that have independent boards,
separation of the roles of chief executive officer (CEO) and board chair (CEO duality), older
CEOs and Big 4 auditors are more likely to design longer time-vesting options; (2) firms with
stronger corporate governance, older CEOs and Big 4 auditors are more likely to attach
performance hurdles to their option grants; and (3) well-governed firms prefer stock-based
hurdles more than accounting-based hurdles; however, using a Big Four auditor is associated
with greater use of accounting-based hurdles. The findings suggest that firms with stronger
governance mechanisms are more likely to extend the incentive horizon and to use ESOs to
help improve the firms’ accounting and stock-based performance. These practices are
principally designed to enhance goal alignment of managers and shareholders, which is
consistent with the predictions of agency theory. To examine the robustness of our results, we
also estimate our models with (a) an option grant-level sample, and (b) two sub-samples (preand post- 2005) to reflect changes resulting from the adoption of International Financial
3
Accounting Standards (IFRS). The results remain consistent.
This study contributes to the literature on executive compensation and corporate
governance. While previous studies investigate the form and composition of executive
compensation, explaining managerial power in design of compensation structures, for example,
to expropriate funds (Perry and Zenner, 2000); to build an empire (Bebchuk and Fried, 2003);
or to consume perquisites (Bebchuk and Fried, 2006), direct evidence relating corporate
governance determinants to ESOs design is limited. Our study provides the first Australian
evidence on how various corporate governance mechanisms influence the setting of ESO
vesting conditions.
In contemporaneous work on time-vesting conditions, Chi and Johnson (2009) and
Cadman and Sunder (2014) examine vesting periods using US data. These studies incorporate
the vesting periods of ESOs along with the mix of other share-based compensation to compute
a time-vesting measure. However, our study examines ESO vesting terms exclusively to isolate
this dimension of the ESO contract. Furthermore, some earlier studies provide evidence on the
prevalence of performance-vesting ESO grants based on UK data, since the publication of
Greenbury report (1995) promoted the linkage of performance targets to share-based
compensation. For example, Qin (2012) examines the influence of firm and executive
characteristics on the use of performance-vested ESO grants from 1999 to 2004. Kuang and
Qin (2009) and Carter et al. (2009) examine the incentive effect of performance-based vesting
conditions. Other studies focus on the nature of the option contracts, and the influence that the
vesting conditions have on firm performance and financial reporting (Bettis et al., 2010; Kuang,
2008). Our study provides extended and comparable evidence on the association between
corporate governance attributes and the use and the type of ESO performance-based vesting
conditions in an institutional context of Australia. The study also has important implications
for regulators, accounting professionals, investors and shareholders. By demonstrating the role
4
of corporate governance in the design of ESO grants, this study directly informs investors and
shareholders about implementing vesting conditions strategically for the better alignment of
executive incentives with shareholders’ wealth.
The remainder of the paper is organised as follows. The next section outlines the
institutional background of ESOs. Section 3 reviews relevant prior literature. Section 4
develops the hypotheses of the study. Section 5 outlines the research methods. Section 6
presents empirical results, followed by robustness tests in Section 7. Finally, Section 8
concludes the study, notes its limitations and offers directions for future research.
2. Institutional Background
Following the corporate collapses of the early 2000s, stock options have become one of the
most controversial forms of executive compensation. The issue surrounding the accounting
treatment of ESOs is related to whether the cost of issuing options should be recognised as an
expense in the income statement. Australia was one of the first countries to apply mandatory
recognition of cost of ESOs. Prior to this, the accounting regulation for ESOs was restricted to
presentation and disclosure issues. 2 With the adoption of IFRS, the Australian equivalent
standard, AASB 2, came into force in 2005. The standard, which deals with the recognition and
measurement of share-based payment transactions, has greatly reduced the disparity in the
accounting treatment of ESOs. Paragraph 10 of AASB 2 states:
‘For equity-settled share-based payment transactions, the entity shall measure the goods or
services received, and the corresponding increase in equity, directly, at the fair value of the
goods or services received, unless that fair value cannot be estimated reliably. If the entity
cannot estimate reliably the fair value of the goods or services received, the entity shall
measure their value, and the corresponding increase in equity, indirectly, by reference to the
2
AASB 1028 Employee Benefits in 1994; AASB 1017 Related Party Disclosures in 1997.
5
fair value of the equity instruments granted.’
There is a general presumption that transactions with employees cannot be reliably
measured on the basis of the value of the services being provided. Transactions with employees
are therefore to be measured by reference to the fair value of the equity instruments granted.
Furthermore, the introduction of vesting conditions has implications for when the associated
expense is to be recognised. For instance, for the ESOs that vest immediately, the whole
transaction is to be recognised at the grant date as the option holders are not required to
complete a specified period of service. The company assumes that the employee has rendered
services in full in return for the options granted. On the other hand, if the options do not vest at
grant date, in cases when vesting conditions are involved, the standard indicates a presumption
that they are a payment for services to be received during the vesting period, and therefore, the
cost is recognised during the period.
Under AASB 2, there is now a general requirement that clarifies the recognition of ESOs in
the firm’s financial statements, though it may further complicate the requirements in
accounting for ESOs considering a firm’s choice of vesting conditions. The imposition of this
accounting rule shows the success of the regulators in improving the relevance, reliability and
comparability of publicly reported financial information, provides transparent financial
statements and high quality ESOs disclosures, and helps users of financial information to
understand better the economic transactions (Fisher and Wise, 2006).
3. Literature Review
3.1 Executive stock options literature
ESOs are popular and constitute a substantial component of Australian executive pay
(Coulton and Taylor, 2002). Firms have praised their effectiveness in aligning the goal of
managers and shareholders, attracting and retaining key talents, and encouraging top
6
management to take appropriate risks in the new economy (Ittner et al., 2003; Oyer and
Schaefer, 2005; Coles et al., 2006). However, following the failure of firms such as Enron in
the US and HIH Insurance in Australia, researchers have raised concerns about ESOs.
Evidence reported includes the association between ESOs and misreporting issues (Burns and
Kedia, 2006), earnings management (Baker et al., 2003) and manipulation of ESO exercising
strategies (Collins et al., 2009).
Most of the concerns stem from the fact that firms have not paid enough attention to the
potential dysfunctional consequences when designing ESOs. Inappropriate design is likely to
accentuate the downside of ESOs and reduce their potential benefits. Regarding ESO design
features, much research has focused on the magnitude of ESO grants (Gaver and Gaver, 1993;
Bryan et al., 2000), ESO pricing and exercising patterns (Hall and Murphy, 2000), and some
ownership issues (Brandes et al., 2003). Careful consideration of these issues should improve
the efficiency of option-based incentives that promote strategic goals, enabling firms to recruit,
motivate, and retain valued employees, and to increase firm value (Brandes et al., 2003).
More recently, the design of vesting conditions, as another vital aspect of ESO design
features, has gained increasing attention in compensation research. A limited number of studies
based on US data have investigated the determinants of ESO vesting periods and have provided
evidence on how firms actively choose vesting periods. For example, Cadman et al. (2013)
examine the economic determinants of ESO vesting schedules using 7,412 firm-year
observations over the period 1997-2008. They tested several economic and reporting
motivations and found that growth firms prefer longer vesting periods to provide long horizon
incentives and defer reporting costs, while shorter vesting periods are used in firms with
weaker governance and more powerful executives. These results are consistent with Laux
(2012), who found that option grants with longer vesting periods are viewed as an effective
means to link CEO pay to long-term firm performance and to alleviate short-termism
7
behaviour.
Further incentive research is focused on the consequences of the design of time-vesting
conditions. The arguments for longer vesting periods are primarily driven by the desire to
extend the horizon of the incentives and to retain executives (Cadman and Sunder, 2014;
Walker, 2010). Lengthening the time to sell equity holdings could influence the value of ESOs
and executive risk-taking incentives. As shown in Hodge et al. (2009), the subjective value of
options from the executives’ perspective is decreasing in the length of the vesting period. Also,
longer time-vesting ESOs are designed to increase managerial risk-taking incentives by
extending the term to exercise options; however, Brisley (2006) found that longer time-vesting
ESOs could induce executives to behave in a more risk-averse manner, arguing that flexibility
with respect to selling can help restore risk-taking incentives. In this circumstance, firms
design shorter vesting periods when ESOs are mainly used as a method of compensating
employees rather than providing incentives.
Prior studies mostly focus on the traditional time-vesting ESOs, however, recent trends
have put more emphasis on performance-vesting ESO grants. The discussion, so far, indicates
that performance-vesting ESOs provide greater incentives than traditional stock options that
simply vest upon the passage of time (Johnson and Tian, 2000; Kuang, 2008). Performance
hurdles link vesting not only to elapsed time, but also to improvements in the stock market,
accounting, or other performance measures. Gerakos et al. (2007) examine the determinants of
the design of performance vesting conditions using 128 US firms. They document that two of
the strongest determinants are stock return volatility and market-to-book ratio, and both are
negatively associated with greater use of performance hurdles. Bettis et al. (2010) extended
their study using 983 equity-based awards, and found that the use of performance hurdles is
positively associated with new CEO appointments and the proportion of outside directors, and
negatively associated with prior stock performance. In addition, a recent study by Qin (2012)
8
found that, in the UK (1999-2004), both firm and executive characteristics could influence the
likelihood of using performance-vesting ESOs, such as corporate governance structures,
managerial power, CEOs approaching retirement, and CEO ownership of equity.
In terms of the consequences of performance vesting conditions, Kuang and Qin (2009)
investigate the effect of performance vesting conditions in aligning management interests and
shareholders’ wealth based on UK data sets over the period of 1999-2004. They found that the
propensity to use performance hurdles is positively associated with greater interest alignment.3
The results are supported by Bettis et al. (2010) who argue that the use of performance-vesting
options is associated with perceived stronger governance structures and less agency problems.
However, the implications of such compensation design on managerial behaviour are the
subject of debate. Theoretical evidence argues that this reward mechanism may have
undesirable consequences: basing executives’ compensation on performance targets induces
managerial game-playing at the expense of shareholders (Jensen, 2003; Kuang, 2008).
Powerful executives could opportunistically influence the setting of performance targets by
increasing their achievability (Conyon and Murphy, 2000).
3.2 Corporate governance literature
Corporate governance has received increasing emphasis both in practice and in academic
research, it influences the setting and achievement of firm objectives, monitoring and
assessment of risks, and optimisation of firm performance (ASX, 2014). It is argued that strong
governance structures can increase the market valuation of firms, improve financial
performance, and raise confidence in investors (ASX, 2014). The key roles of corporate
governance raised in prior research include optimising firm value (Gompers et al., 2003;
Bebchuk et al., 2009), mitigating agency problems (Bédard et al., 2004; Davidson et al., 2005),
3
The level of interest alignment is measured by pay-performance sensitivity as suggested in Murphy and Jensen (1998).
9
and increasing transparency of financial reporting (Cohen et al., 2004). Some studies provide
empirical evidence that executive compensation structure is strongly influenced by factors that
represent governance mechanisms (Core et al., 1999; Cyert, et al., 2002; Kang, et al., 2006).
Chalmers et al. (2006) examine corporate governance attributes as one of the three groups of
determinants (governance, ownership and economic determinants) of executive contract
mechanisms in Australia. They found that strong governance ensures that the determination of
the cash salary and share-based compensation reflect a firm’s demand for a high-quality CEO,
and prevent them from extracting rent.4
ESO grants are perceived to represent an aspect of corporate governance because they tie
managers’ personal wealth to their firm’s stock price performance, and reduce the possibility
that managers take suboptimal actions that harm shareholders (Shleifer and Vishny, 1997).
However, many practitioners believe that, rather than being an effective governance
mechanism, equity grants are a manifestation of poor corporate governance (Brown and Lee,
2010). There is also conflicting evidence reported in this strand of literature. From an
opportunistic perspective, some studies suggest that powerful executives are more likely to
influence the design of ESOs in firms with relatively weak corporate governance. For example,
Bebchuk et al. (2010) present US evidence that weaker corporate governance is associated with
‘lucky’ option grants,5 not only to executives, but also to independent directors.
Furthermore, some studies concentrate on the efficiency perspective of agency theory that
would suggest that executives focus on maximisation of long-term firm value. Companies with
strong corporate governance are more likely to design ESOs that are less influenced by
executives. Shareholders typically depend on CEO compensation, especially the option
schemes, to solve agency problems and ensure profit sustainability. Evidence has been found
4
The rent extraction view posits that if the effectiveness of firms’ governance mechanisms is questionable, this could
enable managers to extract compensation in excess of the optimal compensation from shareholders (Bebchuk et al., 2002).
5
‘Lucky’ options are grants given at the lowest price of the month.
10
that better governed firms pay their CEO less for luck (Bertrand and Mullainathan, 2001).6 A
US study by Petra and Dorata (2008) also indicates a positive association between the level of
performance-based incentives and good corporate governance structure, such as effective
board composition and the presence of a compensation committee.
4. Hypothesis Development
Consistent with agency theory, the vesting conditions of ESOs have an important role in
aligning the incentives of top management with shareholders’ wealth. However, only a limited
number of extant studies have examined the determinants of the design of ESO contract
features (Bettis et al., 2010; Qin, 2012; Cadman et al., 2013). To extend the literature on
managerial incentive alignment, it is essential to investigate the effect of various corporate
governance attributes on the design of the vesting conditions. Senior managers have the
potential to design ESOs for their own benefits due to self-interested incentives. Some studies
have argued that CEOs attempt to maximise their ESO awards by making opportunistic
voluntary disclosure decisions (Aboody and Kasznik, 2000) and by timing the exercise of
ESOs with inside information (Carpenter and Remmers, 2001). The choice of a longer vesting
period restricts executives’ abilities to gain personal benefits from exercising ESOs in the
short-term, and extends the period over which the ESOs provide incentives. However, the
extended vesting period imposes higher costs on executives, as the value of ESOs from the
executive’s perspective is decreasing in the length of the vesting period (Hodge et al., 2009).
Hence, shareholders prefer longer vesting periods to increase the effectiveness of ESO grants,
whereas executives are in favour of the flexibility of a shorter vesting period.
Corporate governance has a vital role in determining the ESO vesting conditions. Prior
research, based on an opportunistic perspective, suggests that companies with relatively weak
6
Luck means observable shocks to performance beyond the CEO’s control.
11
corporate governance are more likely to design ESOs that are favoured by their executives.
Core and Guay (1999) indicate that executives of firms with lower levels of internal control
potentially receive more equity grants than predicted by economic and firm determinants.
Using a large US sample from 1998 to 2006, Brown and Lee (2010) suggest that more poorly
governed firms grant favourable ESOs that usually have short-term provisions. Corporate
governance attributes, such as the independence of the board and associated committees, CEO
characteristics and external auditing are important mechanisms that potentially constrain the
opportunistic behaviour of executives in terms of rent extraction through compensation. Thus,
well-governed firms contract with their executives in a manner that more closely aligns CEO
compensation with the long-term value of the firm. Therefore, to maintain the effectiveness of
equity incentive alignment, it is expected that ESO vesting periods are longer when firms have
stronger corporate governance.
H1: There is a positive relationship between strong corporate governance and the length of the
vesting period.
Under performance-based vesting conditions, ESO grants vest only if specified
performance hurdles are met. This type of ESO aims to link option vesting to accounting-based
(e.g., earnings per share growth) and/or stock-based (e.g., total shareholder return)
performance hurdles. These vesting conditions are potentially useful for providing substantial
managerial incentives to alleviate the agency conflicts resulting from the separation of
ownership and management (Shleifer and Vishny, 1997). They are also widely perceived to
help motivate senior managers to improve financial performance in the long-term interests of
the firm (Jensen and Murphy, 2010).
The effectiveness of a firm’s corporate governance structure potentially influences the
likelihood of using performance hurdles, as well as the design features. Corporate governance
mechanisms are put in place to mitigate agency problems and to optimise shareholders’ wealth,
12
while poorly governed firms may allow CEOs to extract greater benefits at the expense of the
firm value (Core et al., 1999). Careful design of performance hurdles restricts the opportunistic
behaviour of self-interested managers, and is in line with the fundamental purpose of corporate
governance mechanisms. A US study by Bettis et al. (2010) investigates the relationship
between performance-based conditions and the board and CEO characteristics using a large
number of randomly selected companies over the period from 1995 to 2001. They document
that the propensity to use performance hurdles is positively related to the arrival of a new CEO
and the proportion of outsiders on the board of directors. Also, performance-vesting firms have
significantly better subsequent operating performance. More recently, Qin (2012) provides
fairly comparable evidence using multi-level modelling and reports consistent results that good
corporate governance structures facilitate the use of ESO performance hurdles. In addition, a
European study by Sautner and Weber (2011) supports the notion that when governance
structures are weak, ESO plans are more likely to be designed in a way that is desired by
executives. For instance, they are usually less likely to contain performance targets or use
lower target rates that are more easily achieved.
The efficiency perspective of positive accounting theory suggests that well-governed firms
would prefer ESOs to closely align the incentives of executives with firm value, and help
ensure the sustainability of financial performance in the long run. As the use of performance
hurdles could lead to greater monitoring of managerial activities and restrict managerial ability
to use resources inefficiently, firms would design their contractual arrangements with this type
of vesting condition on an upfront basis to tie executives’ compensation to performance targets.
Therefore, it is expected that firms with stronger corporate governance structures and less
agency conflicts are more likely to use performance hurdles to improve incentive alignment.
H2: There is a positive relationship between strong corporate governance and the propensity
to use performance hurdles.
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5. Research Design
5.1 Sample description and data sources
The original sample consists of the largest 250 Australian listed companies, based on their
market capitalisation from 2003-2007. These years are selected due to environmental changes
in the years around 2005 when Australia first adopted IFRS (Australian equivalent standard –
AASB 2). Therefore, 2005 represents a ‘transition period’ to accept the new regulation and
recognise the changes required. The years of 2003-2004 constitute a ‘pre-adoption period’ as
they represent the period before the adoption. The years of 2006-2007 are considered as the
‘post-adoption period’, and they are expected to capture the greater part of the regulatory effect.
To be included in the study, these firms must satisfy four criteria. They must be: (1) listed on
the ASX during 2003-2007; (2) continuously maintained in the top 250 companies during
2003-2007; (3) non-financial firms (excluding Banks, Diversified Financials, Insurance, and
Real Estate industry sectors); and (4) firms that issue CEO stock options. Large firms are
selected because they tend to use ESOs extensively and are of most concern to stakeholders. If
the study fails to detect a material effect for this group of firms, then it is likely to be immaterial
for all but a few firms. A total of 140 companies were eliminated because they were not listed
continuously in the top 250 during the test period. In addition, 23 financial companies were
excluded because their accounting and reporting requirements and capital structure vary
greatly from other companies (Singhchawla, et al., 2011). Furthermore, 223 firm-year
observations were eliminated because there were no ESO grants issued in the given year. This
is consistent with the findings in Matolcsy and Wright (2007) that the unique institutional
setting makes Australia different to the US, with not all Australian companies using ESOs
every year. Finally, eight firm-year observations were removed due to missing data. Overall,
the final sample consists of 204 firm-year observations (380 grant-level observations) pooled
14
for the financial years 2003-2007.7 Table 1 outlines the sample selection procedures based on
firm-year observations.
[Insert Table 1]
Three main data sets were collected for the analysis. First, CEO compensation data were
obtained by manually searching the compensation reports and notes to the financial
statements.8 The annual reports were acquired from the Connect 4 online database. Second,
financial data were extracted from the Aspect Fin Analysis database. Third, corporate
governance data were extracted from the SIRCA Corporate Governance database, and the
composite corporate governance index was obtained from the Horwath Corporate Governance
Reports.9 This is the best known corporate governance scoring system in Australia, and has
been widely used in extant research (Linden and Matolcsy, 2004; Beekes and Brown, 2006).
The index independently assesses and ranks corporate governance structures and policies of
the largest 250 Australian companies, based upon a combination of factors identified in
national and international best practice guidelines.10
5.2 Research models
Two regression models are developed to examine the association between the corporate
governance attributes and the design of vesting conditions. An ordinary least squares (OLS)
regression model is used to estimate the continuous dependent variables (i.e., Vest_Duration,
and Vest_Period), and a logistic regression model is to predict the dichotomous dependent
variables (i.e., Vest_Long, Vest_Early, Hurdle_Use, Hurdle_Both, Hurdle_Stock, and
7
For the companies that granted ESOs, they may award ESOs with several instalments that vest during the vesting period.
The grant-level observations are analysed in additional tests.
8
Appendix A contains an example of a part of a compensation report regarding the ESO grants and related details.
9
The 2004 Horwath report provides data for 2003 and 2004; The 2008 Horwath report provides data for 2006 and 2007.
The data for 2005 is not available, which is calculated by taking the average of the 2004 and 2006 data.
10
These include the USA Blue Ribbon Committee Report (1999), the UK Hampel Report (1999), the OECD Report (2004),
the UK Higgs Report (2003), the Australian Ramsay Report (2001), Investment and Financial Services Association of
Australia Corporate Governance Guide (2003) and the ASX Corporate Governance Council Principles and
Recommendations (2007).
15
Hurdle_Acct). In the following models, the lagged values of variables are included on the
right-hand side of the equations to reflect the backward effect of corporate governance
measures on the design of vesting conditions. The basic form of the empirical model is as
follows:
Designit = β0 + β1CG_Indexit-1 + β2Board_Sizeit-1 + β3Independenceit-1 +
β4Ownership_Concentrationit-1 + β5CEO_Ageit-1 + β6CEO_Dualityit-1 +
β7CEO_Ownership it-1 + β8CEO_Powerit-1 + β9Big4it-1 + βnControlsit-1 + ε
5.3 Variables and measurements
The first dependent variable, the length of vesting period, is measured in four ways. Since
firms may issue more than one grant of ESOs in a year or issue one grant that settled in several
instalments, the primary measure is the vesting duration (Vest_Duration), calculated as the
weighted average vesting time in a given year (Cadman et al., 2013). The original vesting
period (Vest_Period) for each ESO grant is used in the robustness tests for grant-level analysis.
To capture the notion of early vesting, an indicator variable (Vest_Early) is constructed if the
ESO grant vests within one year from the grant date (Cadman et al., 2013). To further explore
whether the vesting features are designed to provide long-term incentives, an indicator variable
(Vest_Long) takes the value of one if the vesting duration is longer than the median of the
sample vesting duration, and zero otherwise. The second dependent variable, the use of
performance hurdles is primarily measured by an indicator variable (Hurdle_Use), which takes
the value of one if any type of performance hurdle is used, and zero otherwise (Bettis et al.,
2010). To further capture the design of performance vesting conditions, another two indicator
variables are used to test the individual effect of the two most popular performance hurdles,
stock-based hurdle (Hurdle_Stock) and accounting-based hurdle (Hurdle_Acct). An indicator
variable (Hurdle_Both) is used to measure if the option grant is attached with both types of
16
performance hurdles.
Our main variables of interest are the attributes of corporate governance, which are
expected to influence the design of ESOs. We employ a composite corporate governance index
(CG_Index) developed in the Horwath Corporate Governance Reports, which is measured on a
scale of one to five, with five meaning the strongest level of corporate governance and one
meaning the weakest level.
Extant studies have suggested that board size (Board_Size) is an influential factor in
corporate governance. Some argue that the larger the board size, the less effective the board, as
too many board members could complicate the decision process and increase agency costs
(Yermack, 1996); however, Kiel and Nicholson (2003) provide Australian evidence that a
larger board has a higher level of competence and brings greater opportunity for more links to
the economy and access to resources. Board independence (Independence) is measured as the
percentage of outside directors on the board. Previous studies support the perception that a high
degree of board independence contributes to good corporate governance structures (Adams et
al., 2008). Ownership concentration (Ownership_Concentration) is measured as the
percentage of total outstanding shares owned by the largest substantial shareholder. Bettis et al.
(2010) suggest that the higher the level of ownership concentration, the better separation of
ownership and control, and the more efficient the ESOs used to improve managerial incentives.
The age of CEOs (CEO_Age) is an influential aspect of corporate governance. It is
measured as an indicator variable that equals one if the CEO is older than sixty years of age,
and zero otherwise (Linck et al., 2008). While age could indicate more experience as a CEO,
Dechow and Sloan (1991) have used this to measure closeness to retirement. There is a
tendency towards an intensive use of vesting conditions to compensate older CEOs to reduce
the decision horizon problem. Using Australian data does not allow us to collect data on the
CEO characteristic, length to retirement, as there is no mandatory retirement age in Australia.
17
We have used the age of the CEO as a proxy for length to retirement. CEO duality
(CEO_Duality) compromises the independence of the board and has been considered as a
weakness of corporate governance structure (Petra and Dorata, 2008). It is measured as a
dummy variable equal to one if the CEO of a firm is also the chairperson of the board, and zero
otherwise. CEO ownership (CEO_Ownership) is measured as a percentage of total outstanding
shares held by the CEO. Greater ownership could indicate a decreased degree of separation of
ownership and control, and therefore greater interest convergence with shareholders and lower
agency costs (Bebchuk et al., 2010). However, some studies find that large CEO ownership is
related to weak corporate governance, suggesting that CEOs intend to increase their own stock
returns by manipulating earnings (Klein, 2002). CEO power (CEO_Power) is measured as the
difference between the total cash compensation of the CEO and the next highest paid executive
divided by the total cash compensation of the next highest paid executive (Cadman et al., 2013).
Chatterjee and Hambrick (2007) find that CEOs with relatively greater power have the
potential to engage in more rent extraction actions, and thus reduce the strength of corporate
governance.
The use of a Big Four auditor (Big4) is measured as an indicator variable given the value of
one if a Big Four auditor is employed, and zero otherwise. This variable is generally used as a
measure of strong external monitoring (Goodwin-Stewart and Kent, 2006). High-quality
external auditing may help to improve internal decision-making as well as encourage the
careful recording of financial information.
To control firm-specific effects, we use six variables to reflect the factors that have shown
in prior research to be related to executive compensation. One of the main influential factors
found across virtually all published studies is firm size (Core et al., 1999). Size is measured by
the natural logarithm of total assets (LogAssets). Financial profitability is also a critical
influencing factor in the design of ESOs (Cyert et al., 2002). In this study, accounting
18
profitability is measured by return on assets (ROA). It is calculated as earnings before interest
and tax divided by total assets (Davila and Penalva, 2006). Stock market profitability is
measured by the annual stock return (Stock_Return) (Bebchuk et al., 2010). The extent of
leverage in the firm could also impact on our results. The debt ratio is measured as total
liabilities divided by total assets (Debt) (Brown and Lee, 2010). The variable for the cash
position (Cash/Asset) is proxied by total cash divided by total assets. Since granting ESOs
requires no cash outlays, firms that face liquidity problems are more likely to rely on ESO
compensation to conserve cash (Kang et al., 2006). Growth opportunity is measured as the
growth in total sales revenue (Growth) (Ozkan, 2007). Also, a measure of free cash flow (FCF)
divided by total assets (FCF/TA) is included, as Core and Guay (1999) argue that high free cash
flow poses a problem for firms with low growth opportunities, as managers may invest the
excess cash in negative net present value projects or engage in empire-building acquisitions.
Lastly, a measure of the regulatory effect (Expensing_Effect) is constructed as an indicator
variable. It takes the value of one if the observation is in the ‘post-adoption’ period (after 2005)
of IFRS, and zero otherwise. The year (Year_Dummy) and industry effects (Industry_Dummy)
are also considered in the analysis.
6. Empirical Results
6.1 Descriptive statistics
Table 2 presents the industry distribution of the firm-year sample with various vesting
features. The industry is classified based on the two-digit GICS (Global Industry Classification
Standard) code. The majority of the sample is in the Consumer Discretionary and Materials
industry sectors. In addition, most of the firm years that have a longer vesting period are in the
Consumer Discretionary industry, followed by Consumer Staples, while none are in the
Utilities sector. The industry distribution of observations that use stock-based performance
19
hurdles, as well as the distribution for both hurdles use, has a large proportion in the Materials
and Consumer Discretionary sectors. Interestingly, the accounting-based hurdles are most
widely used in the Consumer Staples sector.
[Insert Table 2]
Table 3 provides summary statistics for the dependent variables. In Panel A the vesting
period of each ESO grant ranges from zero to six years, with a mean of approximately 2.7 years.
The vesting duration provides similar findings. Only a small number of observations are
early-vested within one year, while more than half of the sample prefers long vesting period
with more than three years. In some cases, ESOs are granted with several instalments (or
tranches) and become partially vested in increasing amounts over the vesting period (‘graded
vesting’). Other ESOs may vest entirely at one time at the end of the vesting time (‘cliff
vesting’). The tranche row shows that more than half of the ESO grants are cliff vesting. For
those graded vesting ESOs, the vesting periods between different tranches are not highly
diversified, which is unlike the findings in the US study by Cadman et al. (2013). Panel B
describes the percentage of the vested ESOs to the total number of ESOs at yearly intervals.
More than 50 per cent of the ESOs vest at the third anniversary of the grant date and about 25
per cent vest at the second anniversary. This indicates that the design of vesting period in
Australia is relatively stable. Panel C and Panel D display the summary statistics and a t-test for
the design of performance hurdles. Performance hurdles are extensively used in our sample
firms (87.75%). However, only a small number of observations use two types of performance
hurdles, with both accounting and stock market targets (28.43%). In particular, stock-based
performance hurdles are more frequently used than accounting-based performance hurdles, as
supported by the findings in the t-test (t = -6.475, p < 0.01).
[Insert Table 3]
Table 4 displays summary statistics for independent and control variables. In Panel A, the
20
mean corporate governance score for sample companies is 3.5, ranging from a minimum of one
to a maximum of five. Thus, the overall level of corporate governance of the sample is above
average. Specifically, on average, the sample companies have around eight board members,
viewing that board size is large enough to exercise their power diligently. Most companies have
a majority of independent directors on their boards, and CEO duality appears at a
comparatively smaller average rate of 2.5 per cent compared to the US.11 Also, about half of
the CEOs in the sample are below sixty years old. On average, the CEOs only hold 1.1 per cent
of total outstanding shares, while they still have relatively high managerial power indicated by
the cash compensation they received. Most of the sample companies (95.1 per cent) employ
Big Four audit firms during 2003-2007. In addition, the ownership concentration is 16.2 per
cent on average, showing the shares owned by the largest substantial shareholder.
Panel B displays the descriptive statistics for control variables. The sample covers a range
of large listed companies, with a mean LogAssets of 20.996. In terms of profitability, on
average, the sample companies have an ROA of 0.089 and an annual stock return of 0.263
respectively. Further, sample companies have on average total liabilities of approximately 24.2
per cent of their assets, and total cash of 7.7 per cent of assets. As for growth opportunities, the
companies have increased sales revenue on average by approximately 17.2 per cent in each
year. Also, a relatively low average FCF rate of 5.1 per cent indicates that the companies do not
retain excess cash.
[Insert Table 4]
Table 5 presents the Pearson correlation matrix.12 Although there are some significant
relationships between the corporate governance variables, no correlation exceeds 60 per cent,
11
Statistics show that 63 percent of the S&P 500 companies do not have separate chair positions in 2009 (and 61 per cent in
2008) (Stuart, 2009).
12
Specifically, the measures of the vesting period have significant relationships with a majority of the corporate governance
variables, including the corporate governance index, board size, CEO duality, CEO age, CEO ownership, and the use of a Big
Four auditor. In addition, the measures for the performance hurdles have relationships with the corporate governance index,
board size, board independence, CEO age, CEO ownership, and the use of a Big Four auditor. Most of the signs of the
coefficients are consistent with the predictions.
21
which suggests that there is no multicollinearity issue in the models. For example, some of the
corporate governance attributes are correlated with the composite corporate governance index.
Board independence is significantly related to CEO attributes, because CEOs sometimes could
directly influence the efficiency of the board. Further, firm size is significantly related to some
other financial attributes, because larger firms generally have higher accounting or stock
returns, and also a higher level of debt.
[Insert Table 5]
6.2 Regression results
To control for common effects and test for the explanatory power of each independent
variable, multivariate regressions are applied in this study. Table 6 presents the regression
results for hypothesis one. Model (1) reports the results of the OLS model in which the length
of vesting period is measured as vesting duration. At the firm level, the board independence
(t-statistics = 2.439, p < 0.05) coefficient is positive and significant at the 5% level. This
finding is consistent with the notion that a high level of board independence can constrain
opportunistic managerial behaviour, by using time-vesting conditions to align compensation
contracts with shareholders’ long-term objectives. Also, the vesting duration is positively
associated with CEO age (t-statistics = 2.446, p < 0.05). The finding is consistent with the
prediction that firms grant ESOs with longer vesting periods to extend the incentive horizon for
older CEOs. The lengthened vesting period helps to encourage CEOs who are approaching
retirement to undertake long-term value enhancing projects (Murphy and Zimmerman, 1993).
From a retention perspective, firms would grant longer time-vesting ESOs to keep experienced
and valued CEOs. Furthermore, the use of a Big Four auditor (t-statistics = 4.441, p < 0.01) is
positive and significant at the 1% level. This result supports the prediction that a strong
external monitoring mechanism helps to enhance firms’ compensation decisions in improving
long-term sustainability, and mitigate the agency problems that result from divergence in
22
incentive horizons between the CEO and shareholders (Fan and Wong, 2005). The study finds
insufficient evidence to demonstrate an association between the vesting duration and other
corporate governance attributes; however, the signs of their coefficients are consistent with
expectations. In terms of the control variables, cash-to-assets ratio is found to have a negative
association with the vesting duration (t-statistics = -4.853, p < 0.01). This is inconsistent with
the US evidence provided in Cadman et al., (2013).
Model (2) provides logistic regression results for an indicator variable - long time-vesting
period. Results for board independence (t-statistics = 3.070, p < 0.01), CEO age (t-statistics =
2.259, p < 0.05), and the use of a Big Four auditor (t-statistics = 1.913, p < 0.10) are broadly
consistent with those for Model (1). Additionally, the test provides a weak result for board size
(t-statistics = 1.969, p < 0.10). Beiner et al. (2004) argue that board size is an independent
internal governance mechanism. The finding is consistent with Kiel and Nicholson (2003) who
argue that larger board size leads to better governance structure and firm performance using
Australian data. However, it is in contrast to Yermack (1995) who reports that small boards are
better monitors. CEO duality is significantly and negatively correlated with long time-vesting
(t-statistics = -2.183, p < 0.05). This is consistent with the notion that firms having the same
person serve as CEO and board chair concentrate power in the CEO’s position, potentially
allowing for more management discretion in the design of compensation (Cornett et al., 2008).
Hence, these powerful CEOs are more likely to receive ESOs that favour themselves with
shorter vesting periods.
Model (3) explores the early vesting feature. Its predicted relationships with corporate
governance determinants are expected to have opposite signs of coefficients. The test provides
consistent and significant results for two governance variables, board size (t-statistics = -1.883,
p < 0.05) and the use of a Big Four auditor (t-statistics = -4.903, p < 0.01). Additionally, firms’
growth in sales revenue is negatively associated with early vesting (t-statistics = -2.113, p <
23
0.05), which supports the prediction that firms with more growth opportunities are less likely to
use early-vested ESOs. In particular, they prefer longer vesting periods to extend the
investment horizon (Frydman and Jenter, 2010).
[Insert Table 6]
Tables 7 and 8 present logistic regression results to test hypothesis two. Model (4) provides
strong evidence that the use of performance hurdles is positively associated with the overall
strength of corporate governance (t-statistics = 2.327, p < 0.05). As in Brisley (2006),
performance targets generate significant incentives and increase the sensitivity of managerial
wealth to firm performance. Firms with stronger corporate governance are expected to use
performance hurdles to incentivise performance growth. However, the result is counter to the
findings in Gerakos et al. (2005), which suggest that performance hurdles associated with
exceptionally large ESO grants are more often used in firms with weak governance structures.
Interestingly, CEO age is negatively associated with the use of performance hurdles
(t-statistics = -4.025, p < 0.01). The result is consistent with the findings in Qin (2012), which
argues that firms are more reluctant to use performance-vested ESOs for older or retiring
managers, from managerial power approach, the performance observability perspective and the
informativeness principle. 13 However, this finding is contrary to with the view that when
CEOs approach retirement, the incentive conflict is greater and thus stronger alignment is
expected (Murphy and Zimmerman, 1993). As expected, CEO ownership is negatively
associated with the use of performance hurdles (t-statistics = -1.823, p < 0.10). The finding is
consistent with previous evidence in Core and Larcker (2002) and Bettis et al. (2010), which
report that firms with lower levels of CEO ownership are more likely to use performance
hurdles. Furthermore, ownership concentration is positively associated with the use of
13
Managerial power approach predicts that older CEOs could exercise more managerial discretion in influencing the design
of ESOs for their own benefits. Performance observability perspective predicts that older managers usually have longer
performance tracks with enhanced observability, which reduces the need of performance hurdles. Informativeness principle
predicts that granting performance-vested ESOs to retiring managers could increase the noise in performance measurement.
24
performance hurdles (t-statistics = 2.117, p < 0.05). The finding is consistent with the notion
that higher levels of institutional ownership concentration increase the pay-for-performance
sensitivity of managerial compensation (Hartzell and Starks, 2003). Cash-to-assets ratio is
found to be negatively associated with the use of performance hurdles (t-statistics = -2.900, p <
0.01). Other financial attributes have little explanatory power.
In Model (5), the result shows that the composite corporate governance index has a positive
relationship with the simultaneous use of both types of hurdles (t-statistics = 2.665, p < 0.01).
Well-governed firms are more likely to adopt both types of performance hurdles to improve the
interest alignment of the CEOs with both accounting and stock market performance. The use of
a Big Four auditor shows significant and positive evidence (t-statistics = 2.234, p < 0.05),
which suggests that stronger external corporate governance prevents rent-extracting behaviour
and monitors the design of executive compensation (Frydman and Saks, 2010).
[Insert Table 7]
Table 8 presents logistic regression results for the use of a particular type of performance
hurdle. Model (6) shows that the composite corporate governance index is positively
associated with the use of stock-based performance hurdles (t-statistics = 2.322, p < 0.05). This
type of performance hurdle is favoured by well-governed companies to motivate executives to
improve stock market performance (Kuang and Qin, 2009). The results also provide weak
evidence for board independence (t-statistics = 1.805, p < 0.10). Since the board of directors
ultimately makes the decision whether to use performance hurdles, ESOs with stock-based
hurdles are used more frequently the higher the proportion of outside directors on the board
(Kuang, 2008). CEO age has a negative relationship with the use of stock-based hurdles
(t-statistics = -2.663, p < 0.01). A potential interpretation is that when older CEOs are
approaching retirement, firms are less likely to depend on stock-based performance hurdles,
because the CEOs may opportunistically inflate their short-term stock returns (Dechow and
25
Sloan, 1991).
In Model (7), the regression on accounting-based hurdles provides two empirical findings.
Firstly, CEO age is negatively associated with the use of accounting-based hurdles (t-statistics
= -1.892, p < 0.10). Secondly, the use of a Big Four auditor is positively associated with the use
of accounting-based hurdles (t-statistics = 2.276, p < 0.05). Cohen et al. (2004) report that the
big audit firms are perceived to provide auditing services with higher quality, and thus the
companies would have higher-quality financial reporting. The finding implies that firms are
more likely to depend on accounting-based performance hurdles when their financial accounts
are audited by Big Four audit firms. In summary, empirical evidence is found to support the
view that firms with stronger corporate governance are more likely to use stock-based hurdles
rather than accounting-based hurdles. The reason might be that the performance hurdles based
on the stock market conditions are considered to be fairer and more objective (Lambert and
Larcker, 1987); whereas it could be argued that linking compensation with accounting profit
may encourage managers to manipulate reported earnings (Kuang, 2008). However,
well-governed firms still use accounting-based performance hurdles if a Big Four auditor is
employed, since the reported financial profitability is perceived to be more accurate and
reliable.
[Insert Table 8]
7. Robustness checks
7.1 Estimation of grant-level sample
The descriptive statistics have shown that sample observations have approximately two
tranches per ESO grant in a given year, ranging from one tranche to twelve tranches. Consistent
with previous studies (Bettis et al., 2010; Cadman et al., 2013), both hypotheses are
re-examined using the grant-level sample, which consists of 380 grant-level observations. The
26
results (untabulated) for hypothesis one, show that vesting period measurements produce
consistent results: the length of the vesting period is significantly and positively associated
with the strong corporate governance attributes. The evidence includes the composite corporate
governance index (positive), CEO duality (negative), CEO power (negative), the use of a Big
Four auditor (positive), and ownership concentration (positive).
Furthermore, hypothesis two is also re-examined using the grant-level sample. The results
(untabulated) provide consistent evidence that companies with stronger corporate governance
are more likely to use performance hurdles, which include the composite corporate governance
index (positive), board size (positive), board independence (positive), CEO duality (negative),
CEO age (negative), CEO ownership (negative), CEO power (negative), the use of a Big Four
auditor (positive) and ownership concentration (positive). Overall, the results for the two
hypotheses are robust with respect to this alternative assessment of the sample.
7.2 Effect of the adoption of IFRS in 2005
Prior literature states that accounting regulations play a significant role in compensation
contract design. For example, Hall and Murphy (2002) suggest that one reason for the increase
in stock option grants in the early 2000s is due to the favourable accounting treatment of stock
options under SFAS 123 in the US. Choudhary et al. (2009) find that firms accelerate the
vesting of outstanding options in anticipation of the new requirement to expense options,
presumably to avoid recognising the expense of the previously granted options that had not yet
vested. With the adoption of IFRS in 2005, Australia reduces the reporting benefits of ESOs,
while the rule increased the importance of ESOs grant vesting conditions on recognised
expenses. Therefore, the robustness test is used to assess whether the regulatory effect
impacted on the results.
The total firm-year sample is divided into two sub-samples, including pre-2005
27
sub-samples (124 observations) and post-2005 sub-samples (80 observations). The results
(untabulated) indicate that (1) board independence and the use of a Big Four auditor are found
to show significant results in both sub-samples, using all three measures; (2) board size, CEO
duality, and CEO age provide significant evidence in post-2005 sub-sample; and (3) CEO
power has a significant negative relationship with the length of the vesting period in the
pre-2005 sub-sample. In sum, regardless of the adoption of IFRS, the length of the vesting
period remains positively associated with the strength of corporate governance.
Furthermore, with regard to hypothesis two, several governance measures (untabulated)
show significant results, and most of them have consistent signs of the direction, such as the
composite corporate governance index, board independence, CEO age, the use of a Big Four
auditor, and ownership concentration. The results support hypothesis two that strong corporate
governance has a positive effect on the propensity to use performance hurdles. The tests for the
use of a particular type of performance hurdle also provide consistent results. Overall, the
results are robust with respect to the consideration of the regulatory effect in 2005.
8. Summary and conclusion
While research on executive compensation is substantial, there is limited evidence on the
design of specific contract features of ESOs. Based on a sample of the 250 largest firms in
Australia from 2003-2007, this study examines the association between various corporate
governance characteristics and the design of ESO vesting conditions. It is noted that stronger
corporate governance is significantly associated with longer vesting periods and a higher
propensity to use performance hurdles. The results suggest that corporate governance is an
important influencing factor in designing contract features of option-based compensation.
To our knowledge, our study is the first to focus on the determinants of the design of
vesting conditions in Australia. The study considers various proxies for corporate governance
28
structures, such as board attributes, CEO characteristics, external auditing and ownership
concentration. Controls for broad influential variables, consisting of financial indicators,
regulatory effect, year effect and industry effect, are also included in the models, with the aim
of separating the predictive power of corporate governance from other firm individual
characteristics.
The study provides several novel and interesting results. Firstly, firms with good corporate
governance structures prefer longer vesting periods. Particularly, more independent boards
encourage the use of longer time-vesting option grants to extend the horizon of executive
incentives. The vesting period is longer for older CEOs. As older CEOs approach retirement, a
longer vesting period is desired to reduce the horizon conflict between the firm and the CEO. In
addition, the results show that if the CEO is also the board chair, shorter time-vesting options
are expected. The individual with a dual role may be able to exert a significant influence over
pay-setting to receive ESO grants with a flexible shorter vesting period. The use of a Big Four
auditor is significantly and positively associated with the length of the vesting period,
suggesting that stronger external governance structures help monitor the compensation
decisions to improve the sustainability of firm value.
Furthermore, the study also reports a positive association between strong corporate
governance attributes and the use of performance hurdles. The propensity to use performance
hurdles is positively associated with the overall strength of corporate governance. This result
implies that well-governed firms use performance-vesting ESOs to make executive
compensation more sensitive to performance and to tighten the principal-agent relationship.
The use of performance hurdles is also associated with strong board independence, the use of a
Big Four auditor, and higher levels of ownership concentration, which are consistent with the
notion that strong internal and external governance enhances the improvement in firm financial
performance. Interestingly, the result also presents that older CEOs are less likely to receive
29
ESOs with performance hurdles attached. The use of an accounting-based hurdle is found to be
significantly and positively related to the use of a Big Four auditor. Thus, firms that have higher
financial reporting quality could be more likely to base performance hurdles on the reported
accounting profitability.
This study has a number of limitations which should be borne in mind when interpreting
the results. The sample consists of 204 firm-year observations from large firms in non-financial
industries. These firms may not be representative of the overall population of Australian listed
firms and so our results may lack generalisability. Additionally, the results may not be
generalisable to other jurisdictions as country differences exist and also legal enforcement
differs across countries. Also, since defining and measuring corporate governance have always
been problematic in previous research, our study has a limitation in the selection of certain
governance measures. Further, we do not identify differences in the economic characteristics of
firms that may influence the use of ESOs and other characteristics such as the business cycle
and length of current projects in place. Another limitation of using Australian data is that a
CEO characteristic, such as length to retirement, cannot be determined as there is no mandatory
retirement age in Australia. We have used the age of the CEO as a proxy for length to
retirement. Finally, our study is limited to CEO options and does not consider ESOs granted
to other members of senior management. Future research could address these limitations by
focusing on small- and medium-sized firms, including additional explanatory variables and
exploring ESOs issued to executives other than the CEO. In addition, our study focuses on the
test period from 2003-2007 and an extended research study is likely to provide further evidence
for the years thereafter. For example, future research may highlight the importance of the
financial crisis for a better understanding of managerial behaviour.
30
Appendix A
An example of stock option grants and vesting conditions data for the CEO of Australian
Agricultural Company, fiscal year 2005.
31
Appendix B
Measurement of key variables
Variable
Measurement
Dependent variables – design of stock options
Vest_Duration
The weighted average vesting period of the annual stock option grants
Vest_Period
The time it takes for the entire option grant to vest
Vest_Long
An indicator variable equal to 1 if the vesting duration is longer than the
median of the sample vesting duration, and 0 otherwise
Vest_Early
An indicator variable equal to 1 if the option grant vests within one year,
and 0 otherwise
Hurdle_Use
An indicator variable equal to 1 if the option grant is attached with any
performance hurdles, and 0 otherwise
Hurdle_Both
An indicator variable equal to 1 if the option grant is attached with both
accounting-based and stock-based performance hurdles, and 0 otherwise
Hurdle_Stock
An indicator variable equal to 1 if the option grant is attached with
stock-based performance hurdles, and 0 otherwise
Hurdle_Acct
An indicator variable equal to 1 if the option grant is attached with
accounting-based performance hurdles, and 0 otherwise
Independent variables - corporate governance characteristics
CG_Indexit
A composite corporate governance index ranging from 1-5, with a higher
score representing better corporate governance
Board_Size
The total number of board members
Independence
Percentage of board members defined as outsiders
CEO_Duality
An indicator variable equal to 1 if the CEO is also the chairperson of the
board, and 0 otherwise
CEO_Age
An indicator variable equal to 1 if the CEO is older than sixty years, and 0
otherwise
CEO_Ownership
The percentage of outstanding shares held by the CEO to the total
outstanding shares
CEO_Power
The difference between the total cash compensation of the CEO and the
next highest paid executive divided by the total cash compensation of the
next highest paid executive
Big4
An indicator variable equal to 1 if a Big Four auditor is employed, and 0
otherwise
Ownership_Concentration The percentage of outstanding shares owned by the largest substantial
shareholder to the total outstanding shares
Control variables – firm characteristics, regulatory effect, industry and year dummies
LogAssets
The natural log of total assets
ROA
Return on assets, earnings before interest and tax divided by total assets
Stock_Return
The annualised stock return
Debt
The ratio of total liabilities to total assets
Cash/Asset
The ratio of total cash to total assets
Growth
The difference between the total revenue of the current year and the
previous year divided by the total revenue in the earlier year
FCF/TA
Free cash flow divided by total assets, where free cash flow equals gross
cash flow minus gross investment
Expensing_Effect
An indicator variable equal to 1 if the observation is from 31 December
2005, and 0 otherwise
Year_Dummy
An indicator variable for each sample year
Industry_Dummy
An indicator variable for each industry identified by the common
two-digit GICS code
32
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35
Table 1: Sample selection procedures
Original Observations
Less:
1. Companies not in the top 250 for the whole test period
2. Financial companies
3. Companies not using ESOs in a given year
4. Missing data
Final Sample
1250
700
115
223
8
204
Table 2: Industry distribution of samples using the Two-digit GICS Code
Industry
Energy
Materials
Industrials
Consumer
Discretionary
Consumer Staples
Health Care
Information
Technology
Telecommunication
Services
Utilities
Total
Variable Definitions:
Firm-year obs.
Option-year obs.
Long vesting
Accounting hurdles
Stock hurdles
Both hurdles
Optionyear obs.
19
(9.31%)
47
(23.04%)
33
(16.18%)
53
(25.98%)
18
(8.82%)
22
(10.78%)
3
(1.47%)
4
(1.96%)
5
(2.45%)
204
(100%)
Long vesting
11
(7.86%)
27
(19.29%)
20
(14.29%)
36
(25.71%)
30
(21.43%)
10
(7.14%)
2
(1.43%)
4
(2.86%)
0
(0.00%)
140
(100%)
Accounting
hurdles
2
(1.72%)
9
(7.76%)
18
(15.52%)
20
(17.24%)
45
(38.79%)
16
(13.79%)
0
(0.00%)
1
(0.86%)
5
(4.31%)
116
(100%)
Stock
hurdles
17
(10.18%)
39
(23.35%)
29
(17.37%)
37
(22.16%)
24
(14.37%)
9
(5.39%)
3
(1.80%)
4
(2.40%)
5
(2.99%)
167
(100%)
Both hurdles
2
(3.45%)
15
(25.86%)
9
(15.52%)
19
(32.76%)
7
(12.07%)
4
(6.90%)
1
(1.72%)
1
(1.72%)
0
(0.00%)
58
(100%)
Firm-year observations
Firm-year observations with ESOs
Firm-year observations with ESOs that have vesting duration longer than
the median of the sample vesting duration
Firm-year observations with ESOs that have accounting-based performance
hurdles
Firm-year observations with ESOs that have stock-based performance
hurdles
Firm-year observations with ESOs that have both types of performance
hurdles
36
Table 3: Vesting conditions summary statistics
Panel A: Vesting periods
Variable
Mean
Min
25th Pctile
Median
75th Pctile
Max
Vest_Period
2.664
0.000
2.000
3.000
3.000
6.000
Std.
Deviation
1.059
Vest_Duration
2.614
0.000
2.000
3.000
3.000
5.000
0.919
Vest_Early
0.093
0.000
0.000
0.000
0.000
1.000
0.291
Vest_Long
0.588
0.000
0.000
1.000
1.000
1.000
0.493
Tranches
1.858
1.000
1.000
1.000
3.000
12.000
1.277
Vest_First
2.080
0.000
1.625
2.000
3.000
4.000
0.953
Vest_Last
3.394
0.000
3.000
3.000
4.000
6.000
0.951
Variable Definitions:
Vest_Period
The time it takes for the entire ESO grant to vest
Vest_Duration
The weighted average vesting period of the annual ESO grants
Vest_Early
An indicator variable equal to 1 if the ESO grant vests within one year, and 0 otherwise
Vest_Long
An indicator variable equal to 1 if the vesting duration is longer than the median of the
sample vesting duration, and 0 otherwise
Tranches
The number of tranches over which the grants vests
Vest_First
The vesting period of the first tranche in the grant
Vest_Last
The vesting period of the last tranche in the grant
Panel B: Percent that vest at yearly intervals
Variable
Mean
Min
25th Pctile
Median
75th Pctile
Max
Std. Deviation
% Immediate
0.063
0.000
0.000
0.000
0.000
1.000
0.227
% Vest Year 1
0.060
0.000
0.000
0.000
0.000
1.000
0.177
% Vest Year 2
0.251
0.000
0.000
0.000
0.333
1.000
0.359
% Vest Year 3
0.524
0.000
0.000
0.500
1.000
1.000
0.421
% Vest Year 4
0.086
0.000
0.000
0.000
0.000
1.000
0.215
% Vest Year 5
0.019
0.000
0.000
0.000
0.000
1.000
0.092
% Vest > Year 5
0.000
0.000
0.000
0.000
0.000
0.008
0.001
Panel C: Performance hurdles
Variable
N
Yes
%
No
%
Hurdle_Acct
204
86
42.16
118
57.84
Hurdle_Stock
204
151
74.02
53
25.98
Hurdle_Use
204
179
87.75
25
12.25
Hurdle_Both
204
58
28.43
146
71.57
Variable Definitions:
Hurdle_Acct
An indicator variable equal to 1 if the ESO grant is attached with accounting-based
performance hurdles, and 0 otherwise
Hurdle_Stock
An indicator variable equal to 1 if the ESO grant is attached with stock-based
performance hurdles, and 0 otherwise
Hurdle_Use
An indicator variable equal to 1 if the ESO grant is attached with any performance
hurdles, and 0 otherwise
Hurdle_Both
An indicator variable equal to 1 if the ESO grant is attached with both
accounting-based and stock-based performance hurdles, and 0 otherwise
Panel D: Test of the difference between the use of accounting-based hurdles and stock-based
hurdles
Variable
Mean
Std. Deviation
Hurdle_Acct
0.422
0.495
Hurdle_Stock
0.740
0.440
Difference
T-test
Significance
-0.319
-6.475
0.000**
37
Table 4: Descriptive statistics for regression variables
Panel A: Corporate governance characteristics (independent variables)
Variable
Mean
Min
25th
Pctile
Median
75th
Pctile
Max
Std.
Deviation
CG_Index
3.498
1.000
3.000
3.500
4.250
5.000
0.970
Board_Size
7.756
4.000
6.000
8.000
9.000
13.000
1.968
Independence
0.630
0.111
0.500
0.667
0.800
0.917
0.196
CEO_Duality
0.025
0.000
0.000
0.000
0.000
1.000
0.155
CEO_Age
0.059
0.000
0.000
0.000
0.000
1.000
0.235
CEO_Ownership
0.011
0.000
0.000
0.001
0.007
0.202
0.029
CEO_Power
0.778
0.000
0.242
0.619
1.105
4.398
0.678
Big4
0.951
0.000
1.000
1.000
1.000
1.000
0.216
0.162
0.000
0.064
0.106
0.212
0.634
0.160
Ownership_Concentration
CG_Index
Board_Size
Independence
CEO_Duality
CEO_Age
CEO_Ownership
CEO_Power
Big4
Ownership_Concentration
A composite corporate governance index ranging from 1-5, with a higher score
representing better corporate governance
The total number of board members
Percentage of board members defined as outsiders
An indicator variable equal to 1 if the CEO is also the chairperson of the board,
and 0 otherwise
An indicator variable equal to 1 if the CEO is older than sixty years, and 0
otherwise
The percentage of outstanding shares held by the CEO to the total outstanding
shares
The difference between the total cash compensation of the CEO and the next
highest paid executive divided by the total cash compensation of the next highest
paid executive
An indicator variable equal to 1 if a Big Four auditor is employed, and 0
otherwise
The percentage of outstanding shares owned by the largest substantial
shareholder to the total outstanding shares
Panel B: Firm characteristics and regulatory effect (control variables)
Variable
Mean
Min
25th
Pctile
Median
75th
Pctile
Max
Std.
Deviation
LogAssets
20.996
17.155
19.899
20.895
21.794
24.902
1.562
ROA
0.089
-0.049
0.052
0.072
0.098
0.561
0.074
Stock_Return
0.263
-0.608
0.036
0.225
0.412
2.373
0.372
Debt
0.242
0.000
0.168
0.248
0.341
0.556
0.128
Cash/Asset
0.077
0.000
0.017
0.039
0.076
0.726
0.108
Growth
0.172
-0.822
0.012
0.127
0.256
3.246
0.377
FCF/TA
0.051
-0.479
0.014
0.056
0.100
0.762
0.115
0.392
0.000
0.000
0.000
1.000
1.000
0.489
Expensing_Effect
LogAssets
ROA
Stock_Return
Debt
Cash/Asset
Growth
FCF/TA
Expensing_Effect
The natural log of total assets
Return on assets, earnings before interest and tax divided by total assets
The annualised stock return
The ratio of total liabilities to total assets
The ratio of total cash to total assets
The difference between the total revenue of the current year and the previous year
divided by the total revenue in the earlier year
Free cash flow divided by total assets, where free cash flow equals gross cash flow
minus gross investment
An indicator variable equal to 1 if the observation is in the ‘post-adoption period’, and 0
otherwise
38
Table 5: Pearson correlation matrix for variables
39
Table 6: Results from regression of corporate governance determinants on the length of the
vesting period
Variable
(Constant)
CG_Indexit-1
Board_Sizeit-1
Independenceit-1
CEO_Dualityit-1
CEO_Ageit-1
CEO_Ownershipit-1
CEO_Powerit-1
Big4it-1
Ownership_
Concentrationit-1
LogAssetsit-1
ROAit-1
Stock_Returnit-1
Debtit-1
Cash/Assetit-1
Growthit-1
FCF/TAit-1
Expensing_Effectit-1
(1) Designit =
Vest_Durationit
OLS model
-0.550
(-0.381)
0.060
(0.718)
0.051
(1.168)
0.011
(2.439**)
-0.443
(-1.105)
0.658
(2.446**)
0.000
(-0.007)
-0.062
(-0.631)
1.496
(4.441***)
(2) Designit =
Vest_Longit
Logistic model
-0.200
(-0.241)
-0.011
(-0.223)
0.049
(1.969*)
0.008
(3.070***)
-0.503
(-2.183**)
0.349
(2.259**)
0.020
(1.425)
-0.070
(-1.235)
0.370
(1.913*)
(3) Designit =
Vest_Earlyit
Logistic model
1.127
(2.690)
-0.034
(-1.400)
-0.024
(-1.883**)
-0.001
(-0.524)
-0.109
(-0.935)
-0.022
(-0.286)
0.011
(1.521)
0.041
(1.427)
-0.479
(-4.903***)
0.006
-0.001
-0.002
(1.350)
0.024
(0.335)
0.174
(0.139)
0.020
(0.118)
-0.639
(-1.010)
-4.000
(4.853***)
0.109
(0.660)
0.248
(0.359)
0.079
(0.228)
Included
Included
204
0.000***
0.315
(-0.271)
-0.007
(-0.165)
0.162
(0.225)
-0.002
(-0.018)
-0.341
(-0.937)
-1.306
(-2.757***)
-0.088
(-0.932)
0.154
(0.388)
0.077
(0.389)
Included
Included
204
0.001***
0.144
(-1.567)
-0.005
(-0.230)
-0.152
(-0.419)
0.028
(0.575)
-0.204
(-1.113)
1.334
(5.581***)
-0.101
(-2.113***)
-0.220
(-1.100)
0.094
(0.945)
Included
Included
204
0.000***
0.375
Year_Dummy
Industry_Dummy
No. of observations
Significance F
Adjusted R2
Notes:
For variable definitions see Appendix B
The number in the parentheses is the t-statistics
*** = significance at 0.01 level (two-tailed test), ** = significance at 0.05 level (two-tailed test),
* = significance at 0.10 level (two-tailed test)
40
Table 7: Results from logistic regression of corporate governance determinants on the
propensity to use performance conditions
Variable
(Constant)
CG_Indexit-1
Board_Sizeit-1
Independenceit-1
CEO_Dualityit-1
CEO_Ageit-1
CEO_Ownershipit-1
CEO_Powerit-1
Big4it-1
Ownership_
Concentrationit-1
LogAssetsit-1
ROAit-1
Stock_Returnit-1
Debtit-1
Cash/Assetit-1
Growthit-1
FCF/TAit-1
Expensing_Effectit-1
(4) Designit = Hurdle_Useit
(5) Designit = Hurdle_Bothit
-0.299
(-0.565)
0.071
(2.327**)
0.020
(1.240)
0.001
(0.834)
-0.227
(-1.546)
-0.397
(-4.025***)
-0.016
(-1.823*)
-0.006
(-0.164)
0.093
(0.756)
1.037
(1.492)
0.107
(2.665***)
0.012
(0.547)
0.001
(0.586)
-0.246
(-1.274)
-0.190
(-1.465)
0.007
(0.571)
-0.025
(-0.528)
0.362
(2.234**)
0.004
-0.003
(2.117**)
0.024
(0.905)
-0.337
(-0.733)
-0.007
(-0.106)
-0.114
(-0.493)
-0.877
(-2.900***)
-0.016
(-0.258)
-0.029
(-0.115)
0.169
(1.336)
Included
Included
204
0.000***
0.264
(-1.234)
-0.075
(-1.175)
-0.833
(-1.382)
0.000
(-0.001)
0.191
(0.626)
0.282
(0.711)
0.003
(0.044)
-0.501
(-1.507)
0.073
(0.443)
Included
Included
204
0.001***
0.292
Year_Dummy
Industry_Dummy
No. of observations
Significance F
Adjusted R2
Notes:
For variable definitions see Appendix B
The number in the parentheses is the t-statistics
*** = significance at 0.01 level (two-tailed test), ** = significance at 0.05 level (two-tailed test), *
= significance at 0.10 level (two-tailed test)
41
Table 8: Results from logistic regression of corporate governance determinants on the use of
a particular type of performance hurdle
Variable
(Constant)
CG_Indexit-1
Board_Sizeit-1
Independenceit-1
CEO_Dualityit-1
CEO_Ageit-1
CEO_Ownershipit-1
CEO_Powerit-1
Big4it-1
Ownership_
Concentrationit-1
LogAssetsit-1
ROAit-1
Stock_Returnit-1
Debtit-1
Cash/Assetit-1
Growthit-1
FCF/TAit-1
Expensing_Effectit-1
(6) Designit = Hurdle_Stockit
(7) Designit = Hurdle_Acctit
-0.575
(-0.820)
0.094
(2.322**)
0.014
(0.638)
0.004
(1.857*)
-0.144
(-0.739)
-0.348
(-2.663***)
-0.016
(-1.360)
-0.055
(-1.153)
0.096
(0.586)
0.907
(1.210)
0.067
(1.551)
0.007
(0.294)
-0.004
(-1.539)
-0.327
(-1.570)
-0.264
(-1.892*)
0.009
(0.691)
0.059
(1.144)
0.398
(2.276**)
0.002
-0.003
(0.899)
0.033
(0.942)
-0.765
(-1.257)
0.005
(0.067)
-0.308
(-1.002)
-0.478
(-1.195)
0.028
(0.348)
-0.262
(-0.781)
0.172
(1.030)
Included
Included
204
0.000***
0.230
(-1.286)
-0.049
(-1.327)
-0.481
(-0.740)
0.014
(0.160)
0.144
(0.438)
-0.060
(-0.141)
-0.028
(-0.329)
-0.404
(-1.128)
0.023
(0.130)
Included
Included
204
0.001***
0.309
Year_Dummy
Industry_Dummy
No. of observations
Significance F
Adjusted R2
Notes:
For variable definitions see Appendix B
The number in the parentheses is the t-statistics
*** = significance at 0.01 level (two-tailed test), ** = significance at 0.05 level (two-tailed test), *
= significance at 0.10 level (two-tailed test)
42