corporate governance and stock option vesting conditions ... · corporate governance attributes and...

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*




Fax: +61 7 3735 3719

Fang Hu




Fax: +61 7 3735 3719

Jenny Stewart




Fax: +61 7 3735 3719

June 2014

*Corresponding Author

mailto:[email protected]





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

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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).

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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

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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 (pre-

and post- 2005) to reflect changes resulting from the adoption of International Financial

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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

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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.

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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

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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

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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)

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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).

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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.

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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.

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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,

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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

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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).

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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

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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.

18

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

19

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

20

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

21

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.

22

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

23

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 <

24

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.

25

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

26

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

27

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

28

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

29

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

30

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.

31

Appendix A

An example of stock option grants and vesting conditions data for the CEO of Australian

Agricultural Company, fiscal year 2005.

32

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

33

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36

Table 1: Sample selection procedures

Original Observations 1250

Less:

1. Companies not in the top 250 for the whole test period 700

2. Financial companies 115

3. Companies not using ESOs in a given year 223

4. Missing data 8

Final Sample 204

Table 2: Industry distribution of samples using the Two-digit GICS Code

Industry

Option-

year obs. Long vesting

Accounting

hurdles

Stock

hurdles Both hurdles

Energy 19

(9.31%)

11

(7.86%)

2

(1.72%)

17

(10.18%)

2

(3.45%)

Materials 47

(23.04%)

27

(19.29%)

9

(7.76%)

39

(23.35%)

15

(25.86%)

Industrials 33

(16.18%)

20

(14.29%)

18

(15.52%)

29

(17.37%)

9

(15.52%)

Consumer

Discretionary

53

(25.98%)

36

(25.71%)

20

(17.24%)

37

(22.16%)

19

(32.76%)

Consumer Staples 18

(8.82%)

30

(21.43%)

45

(38.79%)

24

(14.37%)

7

(12.07%)

Health Care 22

(10.78%)

10

(7.14%)

16

(13.79%)

9

(5.39%)

4

(6.90%)

Information

Technology

3

(1.47%)

2

(1.43%)

0

(0.00%)

3

(1.80%)

1

(1.72%)

Telecommunication

Services

4

(1.96%)

4

(2.86%)

1

(0.86%)

4

(2.40%)

1

(1.72%)

Utilities 5

(2.45%)

0

(0.00%)

5

(4.31%)

5

(2.99%)

0

(0.00%)

Total 204 140 116 167 58

(100%) (100%) (100%) (100%) (100%)

Variable Definitions:

Firm-year obs. Firm-year observations

Option-year obs. Firm-year observations with ESOs

Long vesting Firm-year observations with ESOs that have vesting duration longer than

the median of the sample vesting duration

Accounting hurdles Firm-year observations with ESOs that have accounting-based performance

hurdles

Stock hurdles Firm-year observations with ESOs that have stock-based performance

hurdles

Both hurdles Firm-year observations with ESOs that have both types of performance

hurdles

37

Table 3: Vesting conditions summary statistics

Panel A: Vesting periods

Variable Mean Min 25th Pctile Median 75th Pctile Max Std.

Deviation

Vest_Period 2.664 0.000 2.000 3.000 3.000 6.000 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


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


Hurdle_Acct An indicator variable equal to 1 if the ESO grant is attached with accounting-based


Hurdle_Stock An indicator variable equal to 1 if the ESO grant is attached with stock-based


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 Difference T-test Significance

Hurdle_Acct 0.422 0.495 -0.319 -6.475 0.000**

Hurdle_Stock 0.740 0.440

38

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

Ownership_Concentration 0.162 0.000 0.064 0.106 0.212 0.634 0.160

CG_Index 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

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

Expensing_Effect 0.392 0.000 0.000 0.000 1.000 1.000 0.489

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 in the ‘post-adoption period’, and 0

otherwise

39

Table 5: Pearson correlation matrix for variables

40

Table 6: Results from regression of corporate governance determinants on the length of the

vesting period

Variable (1) Designit =

Vest_Durationit

(2) Designit =

Vest_Longit

(3) Designit =

Vest_Earlyit

OLS model Logistic model Logistic model

(Constant) -0.550 -0.200 1.127

(-0.381) (-0.241) (2.690)

CG_Indexit-1 0.060 -0.011 -0.034

(0.718) (-0.223) (-1.400)

Board_Sizeit-1 0.051 0.049 -0.024

(1.168) (1.969*) (-1.883**)

Independenceit-1 0.011 0.008 -0.001

(2.439**) (3.070***) (-0.524)

CEO_Dualityit-1 -0.443 -0.503 -0.109

(-1.105) (-2.183**) (-0.935)

CEO_Ageit-1 0.658 0.349 -0.022

(2.446**) (2.259**) (-0.286)

CEO_Ownershipit-1 0.000 0.020 0.011

(-0.007) (1.425) (1.521)

CEO_Powerit-1 -0.062 -0.070 0.041

(-0.631) (-1.235) (1.427)

Big4it-1 1.496 0.370 -0.479

(4.441***) (1.913*) (-4.903***)

Ownership_

Concentrationit-1 0.006 -0.001 -0.002

(1.350) (-0.271) (-1.567)

LogAssetsit-1 0.024 -0.007 -0.005

(0.335) (-0.165) (-0.230)

ROAit-1 0.174 0.162 -0.152

(0.139) (0.225) (-0.419)

Stock_Returnit-1 0.020 -0.002 0.028

(0.118) (-0.018) (0.575)

Debtit-1 -0.639 -0.341 -0.204

(-1.010) (-0.937) (-1.113)

Cash/Assetit-1 -4.000 -1.306 1.334

(4.853***) (-2.757***) (5.581***)

Growthit-1 0.109 -0.088 -0.101

(0.660) (-0.932) (-2.113***)

FCF/TAit-1 0.248 0.154 -0.220

(0.359) (0.388) (-1.100)

Expensing_Effectit-1 0.079 0.077 0.094

(0.228) (0.389) (0.945)

Year_Dummy Included Included Included

Industry_Dummy Included Included Included

No. of observations 204 204 204

Significance F 0.000*** 0.001*** 0.000***

Adjusted R2

0.315 0.144 0.375

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 7: Results from logistic regression of corporate governance determinants on the

propensity to use performance conditions

Variable (4) Designit = Hurdle_Useit (5) Designit = Hurdle_Bothit

(Constant) -0.299 1.037

(-0.565) (1.492)

CG_Indexit-1 0.071 0.107

(2.327**) (2.665***)

Board_Sizeit-1 0.020 0.012

(1.240) (0.547)

Independenceit-1 0.001 0.001

(0.834) (0.586)

CEO_Dualityit-1 -0.227 -0.246

(-1.546) (-1.274)

CEO_Ageit-1 -0.397 -0.190

(-4.025***) (-1.465)

CEO_Ownershipit-1 -0.016 0.007

(-1.823*) (0.571)

CEO_Powerit-1 -0.006 -0.025

(-0.164) (-0.528)

Big4it-1 0.093 0.362

(0.756) (2.234**)

Ownership_

Concentrationit-1 0.004 -0.003

(2.117**) (-1.234)

LogAssetsit-1 0.024 -0.075

(0.905) (-1.175)

ROAit-1 -0.337 -0.833

(-0.733) (-1.382)

Stock_Returnit-1 -0.007 0.000

(-0.106) (-0.001)

Debtit-1 -0.114 0.191

(-0.493) (0.626)

Cash/Assetit-1 -0.877 0.282

(-2.900***) (0.711)

Growthit-1 -0.016 0.003

(-0.258) (0.044)

FCF/TAit-1 -0.029 -0.501

(-0.115) (-1.507)

Expensing_Effectit-1 0.169 0.073

(1.336) (0.443)

Year_Dummy Included Included

Industry_Dummy Included Included

No. of observations 204 204

Significance F 0.000*** 0.001***

Adjusted R2

0.264 0.292

Notes:



*** = 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

Table 8: Results from logistic regression of corporate governance determinants on the use of

a particular type of performance hurdle

Variable (6) Designit = Hurdle_Stockit (7) Designit = Hurdle_Acctit

(Constant) -0.575 0.907

(-0.820) (1.210)

CG_Indexit-1 0.094 0.067

(2.322**) (1.551)

Board_Sizeit-1 0.014 0.007

(0.638) (0.294)

Independenceit-1 0.004 -0.004

(1.857*) (-1.539)

CEO_Dualityit-1 -0.144 -0.327

(-0.739) (-1.570)

CEO_Ageit-1 -0.348 -0.264

(-2.663***) (-1.892*)

CEO_Ownershipit-1 -0.016 0.009

(-1.360) (0.691)

CEO_Powerit-1 -0.055 0.059

(-1.153) (1.144)

Big4it-1 0.096 0.398

(0.586) (2.276**)

Ownership_

Concentrationit-1 0.002 -0.003

(0.899) (-1.286)

LogAssetsit-1 0.033 -0.049

(0.942) (-1.327)

ROAit-1 -0.765 -0.481

(-1.257) (-0.740)

Stock_Returnit-1 0.005 0.014

(0.067) (0.160)

Debtit-1 -0.308 0.144

(-1.002) (0.438)

Cash/Assetit-1 -0.478 -0.060

(-1.195) (-0.141)

Growthit-1 0.028 -0.028

(0.348) (-0.329)

FCF/TAit-1 -0.262 -0.404

(-0.781) (-1.128)

Expensing_Effectit-1 0.172 0.023

(1.030) (0.130)

Year_Dummy Included Included

Industry_Dummy Included Included

No. of observations 204 204

Significance F 0.000*** 0.001***

Adjusted R2

0.230 0.309

Notes:



*** = significance at 0.01 level (two-tailed test), ** = significance at 0.05 level (two-tailed test), *

= significance at 0.10 level (two-tailed test)

corporate governance and stock option vesting conditions ... · corporate governance attributes and...

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