BOARD STRUCTURE AND EXECUTIVECOMPENSATION IN THE PUBLIC SECTOR: NEW

ZEALAND EVIDENCE

STEVEN F. CAHAN, FRANCES CHUA AND ROBERT OCHOKI NYAMORI*

INTRODUCTION

Executive compensation is an economic and social issue that has attracted

academic, political, and media attention. Recently in New Zealand, there has

been a series of widely publicized examples of ‘excessive’ salaries and/or golden

handshakes in the public sector (e.g., Espiner, 1999; Hawkins, 1999; Kells, 1999;

Hubbard, 2000; The Daily News, 2000; Smith, 2000; The Evening Post, 2002; and

Langdon, 2002).1 This is seen by some politicians and media commentators as

resulting from weak oversight by boards of directors and has led to renewed

criticism of the corporate model for public sector entities (e.g., Kelsey, 1995; and

Kells, 1999). The Labour government elected in 1999 promised to make New

Zealand public sector entities more accountable (e.g., Edwards, 1999).2

However, whether public sector boards in New Zealand are effective and,

more importantly, what makes them effective are empirical questions.

While academic research on executive compensation is extensive (see

Murphy, 1998), as Brickley, van Horn and Wedig (2003) note, almost all of

this research focuses on private sector entities. Using an agency-based framework

(Jensen and Meckling, 1976), one line of research uses cross-sectional differences

in executive compensation to assess the effectiveness of boards of directors (e.g.,

Cyert, Kang, Kumar and Shah, 1997; Core, Holthausen and Larcker, 1999; and

Talmor and Wallace, 2000). Core et al. (1999) point out that executive com-

pensation can be used to assess board effectiveness because compensation

decisions are important, frequent and observable. Because boards of directors

should play a critical role in monitoring the CEO’s performance (e.g., Fama and

Jensen, 1983), Core et al. (1999) expect that ceteris paribus ineffective or weak

boards will pay higher CEO compensation than where board monitoring is

more effective.

* The authors are respectively, Professor of Financial Accounting at the University ofAuckland; Lecturer at Massey University; and Lecturer at Massey University. They thankseminar participants at the University of Tasmania, Massey University, and the AnnualConference of the Accounting Association of Australia and New Zealand for their helpfulcomments. The authors also wish to acknowledge the support of a grant from the MasseyUniversity Research Fund.

Address for correspondence: Steven Cahan, Department of Accounting and Finance,University of Auckland Business School, Private Bag 92019, Auckland, New Zealand.e-mail: s.cahan@auckland.ac.nz

Financial Accountability & Management, 21(4), November 2005, 0267-4424

#Blackwell Publishing Ltd. 2005, 9600 Garsington Road, Oxford OX4 2DQ , UKand 350 Main Street, Malden, MA 02148, USA. 437

Currently, not much is known about board structure or board decision making

in non-private sector entities.3 Yet, this is a critical issue because boards of

directors play a relatively more important role in public sector entities than private

sector entities. That is, lacking alienable residual claims (Alchian, 1977) in the

public sector, monitoring by owners is likely to be severely reduced, leaving the

board as the focal point in the governance process (see Brickley et al., 2003).

New Zealand has been a leader in reforming the public sector (e.g., see

Bollard and Buckle, 1987; The Economist, 1990 and 1991; and James, 1992).

For example, beginning in the mid-1980s New Zealand corporatised over one

hundred public sector entities in areas ranging from hospitals and education to

ports, airports and electricity distributors. While these entities operate under

various legislative acts (e.g., the State-Owned Enterprise Act 1986, Energy

Companies Act 1992, Port Companies Act 1988 and Health and Disability

Services Act 1993), all are incorporated under the Companies Act 1993,

and all have a board of directors. Furthermore, the objectives of the commer-

icalisation process were to improve the efficiency, effectiveness, and account-

ability of these entities. Lacking market-based control mechanisms, public sector

boards play a critically important role in ensuring that these objectives are met.

This involves monitoring CEO performance and remunerating him or her

appropriately.4

The purpose of this study is to examine whether board structure affects board

effectiveness in public sector corporations. We draw on the private sector

corporate governance research which finds that characteristics of board structure

(e.g., board size, percentage of inside or grey directors, proportion of busy

directors) are associated with board effectiveness (e.g., Cyert et al., 1997; Core

et al., 1999; and Talmor and Wallace, 2000). Thus, we examine whether these

same board characteristics are related to the level of CEO compensation in New

Zealand public sector corporations.

The logic of our tests is as follows. The purpose of public sector reforms in

New Zealand (and elsewhere) is to make public sector entities more like private

sector firms. This included using private sector-style boards as the primary

internal corporate governance mechanism. However, there is almost no empir-

ical evidence that shows whether private sector-style boards will be effective in a

public sector context. If we can show that board characteristics associated with

effectiveness in the private sector are also related to board effectiveness in the

public sector, that would provide evidence that private sector-style boards can

work in the public sector context. On the other hand, if board characteristics

associated with effectiveness in the private sector are not related to board

effectiveness in the public sector, that would suggest that adopting private

sector-style boards in public sector entities might not be optimal. Alternatively,

it would suggest that public sector boards might need to be structured differently

to be effective.

Using a sample of 80 New Zealand public sector companies, we find that

similar to private sector studies, board size, whether the CEO sits on the board,

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and director quality have an impact on CEO pay. Specifically, after controlling

for other factors affecting CEO pay levels, smaller boards, boards that do not

have the CEO as a member, and boards with higher quality directors are more

effective at constraining CEO pay. However, variables representing the percent-

age of busy directors, grey directors, and inside directors were not significantly

related to CEO pay. While this evidence is mixed, in further analyses, we

consider the overall impact of our board structure measures. We find that, out

of four categories of explanatory variables, our board variables have the second

highest incremental explanatory power after variables related to managerial

discretion and complexity. We also find that a composite measure of board

effectiveness is significantly related to CEO compensation. Thus, we conclude

that, similar to the private sector, board structure does affect board effectiveness

in public sector corporations in New Zealand. While we recognize that we look

at only one board decision (i.e., CEO remuneration), this finding is important

because it suggests that efforts to model public sector boards after private sector

boards are not unfounded.

The rest of this paper is organized as follows. The second section provides a

brief overview of the research on the private vs. public sector. The third section

reviews the literature on board effectiveness and compensation. The fourth

section describes the sample and method. The fifth section contains results,

and the last section is a conclusion.

PRIVATE VS. PUBLIC SECTOR RESEARCH

The comparative efficiency of public and private organisation has been exam-

ined theoretically by numerous authors, e.g., Alchian (1977), Sappington and

Stiglitz (1987), Schmidt (1996) and Hart, Shleifer and Vishny (1997). In any

organisation where ownership and control are separate, agency problems arise

because of a divergence of interests between the principal and agent (Jensen and

Meckling, 1976). In the private sector, these agency problems are minimized by

a variety of control mechanisms associated with capital markets; the legal,

political, and regulatory system; product and factor markets; and the internal

control system of the entity including the board of directors (Jensen 1993).

For various reasons, these control mechanisms will be weaker in public sector

entities. As Alchian (1977) points out, this is largely due to the lack of alienable

residual claims. Using Jensen and Meckling’s (1992) framework, Dyck and

Wruck (1999) analyse the shortcomings of public sector firms in three areas:

allocation of decision rights, performance measurement, and reward systems.

Regarding the allocation of decision rights, public sector entities are at a

disadvantage because governments find it difficult to credibly commit to a

permanent set of rules. This arises because in the absence of alienable residual

claims, there is no single, easily identifiable objective (e.g., to maximize firm

value). When under political pressure, governments may change organisational

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structures or contracts already in place, which has the effect of making objectives

in public sector entities ambiguous and unclear.5

In terms of performance measurement, the lack of alienable residual claims

reduces the incentive of the government and taxpayers (as well as outside analysts)

to monitor performance. The incentive to monitor is further reduced because of

diffused ownership (i.e., ultimately a public sector entity is owned by all citizens)

and free riding (e.g., Olson, 1971). Also, without tradable equity, there is no

market for corporate control (e.g., takeovers, buyouts) which is an important

disciplining mechanism for underperforming managers ( Jensen, 1993).

In terms of reward systems, in the absence of an externally determined share

price, it is more difficult to determine changes in the entity’s value. As a result, it

may be more difficult to design compensation systems that align the incentives of

owners and managers. The lack of an objective value also may make it harder to

assess managerial talent, and that could reduce the manager’s motivation and

make it harder to recruit superior talent.

Non-traded shares owned by the government also reduce the probability of

bankruptcy to zero or very close to zero because governments are unlikely to let

a public sector entity go bankrupt (New Zealand Business Roundtable, 1988).

This minimizes the effects of poor decision making on the part of management

(e.g., poor performance in product markets) and may increase risk-taking (i.e.,

moral hazard) and, at the same time, reduces the incentive of external creditors

to monitor the entity’s performance (New Zealand Business Roundtable, 1988).

Because control mechanisms are weaker in the public sector, it is expected that

in the long-run, private sector entities will outperform public sector entities, and

empirical research generally supports this (e.g., see Boardman and Vining’s, 1992,

meta-analysis of 90 studies). Many studies focus on the effects of privatisation. For

example, in a study of 61 companies from 18 countries in 32 industries,

Megginson, Nash and van Randenborough (1994, p. 403) find that after privatisa-

tion firms ‘increase real sales, become more profitable, increase their capital

spending, improve their operating efficiency, and increase their work forces’.

Galal, Jones, Tandon and Vogelsang (1994) examine 12 cases of privatisation

from the United Kingdom, Chile, Malaysia and Mexico. They focus on the net

welfare gain or loss and find that privatisation led to net welfare gains in 11 of the

12 cases. However, they note that ‘many of the gains commonly associated with

[privatisation] could also be achieved in theory through the effective implementa-

tion of public sector reforms’ (1994, p. 542). Likewise, Dewenter and Malatesta

(2001) find that post-privatisation performance for a sample of US firms was

superior to pre-privatisation performance. However, they find that much of the

improvement occurred in the 3 years prior to privatisation which suggests that the

process of ‘getting ready’ provides a powerful incentive to improve performance.

The work by Galal et al. (1994), Dewenter and Malatesta (2001) and Dyck

and Wruck (1999), among others, suggests that while public ownership may be

inferior to private ownership, it is possible to improve performance in the public

sector through properly designed organisational structures and contracts.

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The public sector reforms in New Zealand that began in the mid-1980s were

based on this assumption. The objective of the New Zealand reforms was to

improve the performance and efficiency of the government owned entities by

improving their organisational design (e.g., see Spicer, Emanuel and Powell,

1996, for a review of the reforms). Under the reforms, government trading

entities were corporatised. As Spicer et al. (1996) point out, this differs from

privatisation – privatisation changes both the organisational structure and ulti-

mate ownership, while corporatisation changes the organisational structure but

the government remains the ultimate owner.6 As part of the corporatisation

process, boards of directors were appointed. These boards were modelled after

private sector boards, and legally, directors on these boards have essentially the

same duties as directors of private sector entities as the public sector bodies were

incorporated using the existing private sector legislation (i.e., the Companies Act

1955 and later Companies Act 1993).7

CEO compensation in public sector entities is important because it affects the

entity’s ability to attract, motivate, and retain suitable managerial talent. Because

the public sector companies compete against similar organisations with private

ownership, if pay in the former is inadequate, selection and performance incen-

tive problems can arise (Eldenburg and Krishnan, 2003). On the other hand, if

public sector companies pay too much, they will be criticised and pressured by

politicians and the public because taxpayers will see their tax dollars being

wasted ( Jensen and Murphy, 1990; and Eldenburg and Krishnan, 2003).

Given this tension, the board’s role in setting CEO compensation is particularly

important, and whether the board’s structure affects its ability to make good

decisions is a key issue.

While it is generally assumed that structuring public sector boards in a similar

way to private sector boards will be effective, there is almost no evidence that this

is the case. One study that does is Brickley et al. (2003). They focus on nonprofit

hospitals and examine the relation between CEO compensation and board

structure. Using a sample of 308 nonprofit hospitals in the US, they find higher

levels of CEO compensation when the CEO is a voting member of the board.

They also find some evidence that CEO compensation is positively related

to board size and the percentage of inside directors (see Brickley et al., 2003,

p. 19).8

However, we are not aware of any studies that examine the relation

between board structure and CEO compensation in public sector corpora-

tions. Yet, as discussed above, in public sector corporations, the board is the

predominant control mechanism.9,10 Thus, whether public sector boards are

effective is particularly important because there are fewer substitute control

mechanisms compared with the private sector (e.g., private sector firms

with a weak board may also be subject to more market monitoring).

Consequently, we contribute to the literature by examining whether board

structure matters in the public sector in the same way it matters in the

private sector.

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BOARDS AND EXECUTIVE COMPENSATION

There is considerable research that examines the effectiveness of boards of directors

in the private sector. For example, it is widely believed that outside directors provide a

more objective view than inside directors, i.e., the CEO and other employees of the

firm (e.g., Fama, 1980; Pfeffer, 1981; and Fama and Jensen, 1983). Based on this

view, outside directors will want to limit CEO compensation in order to enhance

their reputations as effective and competent board members (e.g., Talmor and

Wallace, 2000). In the US, the California Public Employees Retirement System

(1998) and National Association of Corporate Directors (1996) have recommended

that boards be composed of a substantial majority of independent directors. The

alternative view is that outside directors are ineffective monitors because manage-

ment oversees the selection and reappointment of directors (Hermalin andWeisbach,

1998), and this reduces the independence of the outside directors.

Weisbach (1988) provides evidence that CEOs of poorly performing firms are

more likely to be removed if the board is dominated by outside directors rather

than inside directors. Evidence also suggests that outside dominated boards also

benefit shareholders in decisions related to tender offers (Byrd and Hickman,

1992), management buyouts (Lee, Rosenstein, Rangan and Davidson, 1992) and

poison pill adoptions (Brickley, Coles and Tory, 1994).11 Beasley (1996) finds

that the incidence of fraud and the number of outside board members are

inversely related. However, outside directors do not appear to be related to

long-term performance (e.g., Hermalin and Weisbach, 1991; Klein, 1998; and

Bhagat and Black, 1999) or firm value (e.g., Agrawal and Knoeber, 1996).

The number of directors on the board is also seen to be important (e.g.,

Lipton and Lorsch, 1992; and Jensen, 1993). When board membership is large,

it is difficult to form coalitions opposing the CEO and work productivity can

decline. As Steiner (1972) and Hackman (1990) find, large groups are more

difficult to coordinate, and free riding becomes more likely as group size

increases. Jensen (1993) suggests boards with more than eight members are too

big.12 Yermack (1996) provides evidence showing that firm value is higher when

board size declines. He also finds that CEO compensation is more sensitive to

performance and that dismissals of poor performing CEOs are more likely when

boards are small. Eisenberg, Sundgren and Wells (1998) provide evidence of a

negative association between profitability and board size for Finnish firms.

Vafeas (2000) finds that earnings are more informative for small boards.

The number of directorships held by each director may affect board effec-

tiveness. Fama and Jensen (1983) argue that multiple directorships can be

valuable because they add to the director’s experience and knowledge base

and expose the director to the market for directorial talent. However, limitations

on time as well as mental capacity can make a director holding too many

directorships less effective (National Association of Corporate Directors, 1996).

Additionally, boards may become ‘old boys clubs’ where directors receiving

multiple directorships have the best social connections and, not necessarily, the

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most expertise (e.g., Talmor and Wallace, 2000). Empirically, Shivdasani (1993)

and Talmor and Wallace (2000) find support for a positive relationship between

number of directorships and CEO compensation, while Core et al. (1999) find a

negative relationship.

Jensen (1993) argues that to improve monitoring effectiveness the CEO should not

also be the chair of the board. This is because the chair will set the agenda, configure

committees, decide on operating procedures, and communicate with other board

members. While Kesner, Victor and Lamont (1986) find no evidence of a CEO-

duality effect, Beatty and Zajac (1994) find that CEO-duality can be suboptimal.13

While the literature on executive compensation is extensive (Murphy, 1998), there

are fewer studies that have examined the effects of board characteristics on executive

compensation. Finkelstein andHambrick (1989) find that compensation is not related

to the percentage of outside directors on the board, but Lambert, Larcker and

Weigelt (1993) and Boyd (1994) find that CEO compensation increases with the

number of outsiders on the board. Lambert et al. (1993) also find a positive relation

between CEO pay and the number of directors they have appointed to the board.

More recently, Core et al. (1999) provide a more in-depth examination of the

CEO compensation-board effectiveness relationship by using a comprehensive

set of board related variables and by controlling for ownership structure. It is

important to control for the latter because ownership structure is another

important monitoring mechanism (e.g., Demsetz and Lehn, 1985) that either

may complement or substitute for board monitoring.

To capture board structure, they use variables related to board size, percent-

age of inside directors, percentage of outside directors appointed by the CEO,

grey outside directors, outside directors over age 69, number of other director-

ships, percentage of interlocked outside directors, and CEO duality. Using a

sample of 495 publicly traded US firms over a three year period, they find that

all of the board variables, except the percentage of interlocked directors, are

significant. Moreover, the coefficients are consistent with the interpretation that

decreases in board effectiveness lead to higher compensation. Their ownership

structure variables are also significant, indicating that ownership is an important

substitute for board monitoring.

More recently, Talmor and Wallace (2000) examine the CEO compensation

and board structure relationship in 160 US financial institutions. They also test

variables related to the CEO (e.g., tenure), performance (e.g., market return,

return on equity), and managerial discretion (e.g., firm size, risk, growth). For

their board variables, they find total CEO compensation increases with the

percentage of inside directors, the percentage of directors with multiple director-

ships, the presence of outside blockholder representation on the board, and

decreases with the percentage of board members who are retired. However,

variables such as board size, the percentage of affiliated directors, and the

percentage of directors over 65 are not significant. Importantly, they find their

board effectiveness variables (which include the board variables) have the second

highest amount of explanatory power after their managerial discretion variables.

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As noted above, there has been limited, if any, empirical research examining

the relationship between CEO compensation and board structure in the public

sector. However, as many countries go through the steps to corporatise public

sector entities (e.g., Dyck and Wruck, 1999; and Black, Kraakman and

Tarassova, 2000), politicians, regulators, public sector managers and researchers

need to better understand how private sector-style boards operate in the public

sector environment. In this study, we examine whether factors associated with

board effectiveness in the private sector are also related to board effectiveness in

the public sector. If so, this would provide evidence that private sector-style

boards can work in the public sector.

SAMPLE AND METHOD

To identify the population of public sector corporations in New Zealand, we

requested a list from the government’s Audit Office. This list contained 112

public sector corporations. We sent letters to all 112 entities requesting 1999

annual reports and subsequently received 83 responses.14 Of these, three were

summary reports and were dropped from the sample. The remaining 80 entities

comprise our sample. A list of sample firms is provided in the Appendix.

We use total compensation of the CEO as the dependent variable. We label

this COMP. We derive this information from the annual reports. In New

Zealand, all companies are legally required to disclose the number of employees

earning more than $100,000 in bands of $10,000 (Companies Act 1993,

s 211(1)(g)). This amount includes remuneration and any other benefits so it

represents the total compensation received by the CEO. In 37.5 percent of the

cases, the CEO’s band was explicitly identified. In the remaining cases, we

assume the highest paid employee is the CEO. For 12 companies (15 percent

of the sample), the CEO made less than $100,000. Because companies do not

have to disclose bands under $100,000, we arbitrarily set COMP equal to

$100,000 for all these observations.15

Based on Cyert et al. (1997), Core et al. (1999) and Talmor and Wallace

(2000), we classify our independent variables into four categories related to: (1)

board composition, (2) managerial discretion and task complexity, (3) firm

performance and (4) ownership. Because of the low explanatory power of the

CEO related variables in the Talmor and Wallace (2000) study and because of

the unavailability of data, we do not include these variables.

Consequently, we estimate the following OLS regression model:

COMP ¼�0 þ B �1BDSIZEþ �2CEOBDþ �3BUSY þ �4DIRREP

þ �5INSIDEþ �6GREY þ �7FSIZEþ �8NSUBþ �9NSEG

þ �10ROAþ �11ONEOWNþ �12LISTED þ Industry controls

where (with expected signs in parentheses):

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BDSIZE ¼ number of directors at end of year (þ);CEOBD ¼ 1, if CEO is on board; 0, otherwise (þ);BUSY ¼ number of directors with 3 or more directorships/number of directors

at end of year (þ);DIRREP ¼ 1, if supplemental information on directors is provided; 0, otherwise (�);INSIDE ¼ number of inside directors/number of directors at end of year (þ);GREY ¼ number of grey directors/number of directors at end of year (þ);FSIZE ¼ total assets (þ);NSUB ¼ number of subsidiaries (þ);NSEG ¼ number of segments (þ);ROA ¼ operating income/total assets;ONEOWN ¼ 1, if 100 percent owned by one owner; 0, otherwise (þ/�);LISTED ¼ 1, if listed on the NZSE; 0, otherwise (þ/�).

We discuss each of the independent variables below.

Board Composition

Our board variables are based largely on Cyert et al. (1997) and Core et al.

(1999), but we make minor modifications because not all of their measures are

appropriate for public sector entities. We use five board composition variables.

Board size is represented by the variable BDSIZE where BDSIZE is the

number of directors at the end of the year. Because large boards are seen as

less effective (e.g., Jensen 1993), we expect a positive relationship between

BDSIZE and COMP.

Because the public sector boards were set up to independently monitor

performance, relative to the private sector, it is rare to have a CEO who is

also the chair of the board. For example, in our sample, we find only one case

where the CEO is also the board chair. While CEO duality can be important

(e.g., Beatty and Zajac, 1994), we modify this and include the variable CEOBD

to represent whether the CEO is a member of the board. We code CEOBD

equal to 1 where the CEO is on the board, and 0 otherwise. We expect a positive

relationship between CEOBD and CEO compensation.

The third board variable is BUSY which we define as the percentage of

directors who serve on three or more boards. Because too many directorships

can reduce the director’s effectiveness (e.g., National Association of Corporate

Directors, 1996), we expect a positive relationship between BUSY and COMP.

We include two variables to capture the percentage of directors that have

direct or indirect ties with the firm. INSIDE is the number of internal board

members (i.e., employees) divided by the total number of board members. In

addition to inside directors, often outside directors (i.e., non-employees) have

dealings with the company that they were a director for (e.g., provides legal or

accounting advice to the firm). This information is disclosed either as part of a

related party footnote or as part of the disclosures of interests in the Directors’

Report. Consistent with prior research (e.g., Lee et al., 1992), we classify these as

affiliated or grey directors. Thus, we use GREY, which is the percentage of grey

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directors to total directors. Because inside and grey directors are typically viewed

as less objective than independent outside directors (e.g., National Association of

Corporate Directors, 1996), we expect a positive relationship between INSIDE

and CEO compensation and between GREY and CEO compensation.

Fama and Jensen (1983) argue that outside directors have incentives to

develop reputations for being effective monitors. Because not all directors are

of equal quality, signaling theory (Ross, 1973) suggests that firms with higher

quality directors would have incentive to make this information known in order

to differentiate themselves from other companies with lower quality directors.

While NZ companies are required to provide some information about their

directors (e.g., names, directors’ fees, shareholdings), some companies go beyond

the required disclosures and provide supplemental biographical information on

their directors (e.g., age, qualifications, experience). Thus, whether the company

disclosed supplemental information on their directors is used to proxy for

director reputation or quality. We code DIRREP as 1 if the company provided

this information and 0 if not. Accordingly, we expect a negative relation between

DIRREP and COMP because high quality directors should be better able to

constrain excessive CEO compensation.

Managerial Discretion and Task Complexity

Talmor and Wallace (2000) also note that managerial discretion and task com-

plexity are important measures of executive compensation. When managerial

discretion is high, managers have more influence over the firm’s performance

and value.

Rosen’s (1981 and 1982) work suggests that firm size is a determinant of CEO

compensation. Talmor and Wallace (2000) suggest that the CEO’s responsibility

and job complexity are likely to be positively related to firm size. They also note

that size may proxy for managerial discretion and uncertainty. Because managers

have more and larger decisions to make, they have more influence over the value

of the entity in absolute terms. Consequently, we include FSIZE, which is equal to

total assets, as one measure of managerial discretion and task complexity.

The decentralization and diversification of the entity is also likely to affect the

level of managerial discretion and task complexity. For example, Simunic (1980)

uses the number of subsidiaries and the number of industries a firm operates in

to measure complexity and control problems. Thus, we use the number of

subsidiaries, NSUB, and the number of industry segments the entity operates

in, NSEG, as two additional measures for managerial discretion and task com-

plexity.

Performance

As Core et al. (1999) point out, pay should increase with performance. They and

others (e.g., Lewellen and Huntsman, 1970; Sloan, 1993; and Joskow and Rose,

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1994) find significant positive relationships between accounting rate of returns

and CEO pay. Thus, we include the return on assets, ROA, as another eco-

nomic determinant. In addition to measures of firm size and return on assets,

both Cyert et al. (1997) and Core et al. (1999) include market-based measures of

risk, return, and investment opportunities. Because our public sector companies,

for the most part, do not have traded shares and any market data, we omit these

market-based variables.16

Ownership

Both Cyert et al. (1997) and Core et al. (1999) find that ownership structure is

also important in explaining levels of CEO compensation. They argue that

ownership structure not only affects the alignment of interests between the

CEO and owners but also affects the incentive of the owners to monitor the

managers’ performance. For example, Core et al. (1999) find that CEO com-

pensation is lower when there is a large external blockholder who owns at least 5

percent of the shares. While ownership in our setting differs from the private

sector, it could be important in two ways.

First, the number of owners may be important. In about 75 percent of the

sample, a single public sector entity (e.g., the national government or a regional

or local government unit) owns 100 percent of the shares. In the remainder,

there is more than one owner although in most cases the number of owners is

small (2–3). On one hand, more diffuse ownership will give more parties

incentive to monitor activity and this should increase the overall level of mon-

itoring. On the other hand, when one party owns all the shares and therefore

bears 100 percent of any change in value, this party should have increased

incentive to ensure the managers are acting in their best interest (e.g.,

Dewenter and Malatesta, 2001). We use an indicator variable to capture own-

ership structure. Where all shares are held by one entity, we code ONEOWN

equal to 1, and in all other cases, it is equal to 0. However, because the direction

of the relationship between ONEOWN and CEO compensation is not entirely

clear, we do not predict a sign for the coefficient of ONEOWN.

Second, in our sample, six companies are publicly listed on the New Zealand

Stock Exchange (NZSE). Though the majority of shares for these entities (five

ports and one airport) remain in the public sector, these companies do have non-

government owners and their shares are fully tradable. Because one of the

weaknesses associated with public sector ownership is the lack of alienable

residual claims (Alchian, 1977), owners of entities with listed shares may have

more incentive to monitor performance and constrain pay of the CEO. At the

same time, having traded shares may make the manager’s job more risky, and

managers would be compensated for this through higher levels of pay. Thus, we

include the variable LISTED which is coded 1 if the entity is listed and 0 if not.

While the traded firms are likely to be different, it is unclear how this will affect

CEO pay, and we do not predict a sign for its coefficient.

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Industry Controls

CEO compensation is also likely to have a significant industry component. As

Talmor and Wallace (2000) note, job complexity may be related to industry

concentration, competitiveness, and product differentiability. Like Core et al.

(1999), we include industry control variables for six industries in our sample

which are clearly identifiable (i.e., airports/aviation, forestry, health, power/

electricity, ports, and research institutes). Also, our industry variables recognise

that the different types of firms operate under different legislation (e.g., Energy

Companies Act 1992, Port Companies Act 1988, Health and Disability Services

Act 1993) and may have different performance objectives.

RESULTS

Table 1 contains the descriptive statistics for the variables. The mean CEO

compensation for public sector companies in New Zealand is $194,150, which,

not surprisingly, is vastly different from the NZ$1.87 million and NZ$2.03

million reported by Core et al. (1999) and Cyert et al. (1997) respectively, for

their samples of large, private-sector based companies in the US. For our

sample, the maximum compensation was $640,000.17 Thus, in addition to

examining public sector companies, our study examines a salary range that has

not been examined by prior research.

Table 1 also shows that there is considerable diversity in firm size with the

largest public sector company having $2.309 billion in total assets and the

smallest having $2.619 million in total assets. On average, these companies

earn a return on assets of 7.39 percent, and 76 percent are wholly owned by

the Crown or by a local/regional government body.

The average board size is 5.86 members. The CEO is a member of the board

in 13 percent of the cases, and 30 percent of the directors are classified as busy.

Additionally, 13 percent of directors are inside directors and another 17 percent

are grey directors. Conversely, 70 percent of directors can be classified as

independent outside directors which is much higher than the 51.1 percent for

a sample of New Zealand private sector firms reported by Cahan and Wilkinson

(1999).

Table 2 provides the Pearson pairwise coefficients among the explanatory

variables excluding the industry control variables. The highest correlation, �0.510,

is between ONEOWN and LISTED which is not surprising since listed firms

will have multiple owners. Of more interest, DIRREP and BUSY are signifi-

cantly related (r ¼ 0.385). This suggests director quality and director involve-

ment in more than three directorships are positively associated. To the extent

that high quality directors are demanded more than low quality directors, this

relation provides some empirical support for using DIRREP as a measure of

quality. We also find that DIRREP is significantly related to NSUB (r ¼ 0.252)

448 CAHAN, CHUA AND NYAMORI

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and NSEG (r ¼ 0.282) which suggests higher quality directors are associated

with wider scope and scale in our sample companies.

Also, BDSIZE is significantly related to FSIZE (r ¼ 0.242) and NSUB

(r ¼ 0.234) which suggests increases in scale and scope are associated with larger

boards. Likewise, BUSY is significantly correlated with FSIZE (r ¼ 0.343),

Table 1

Descriptive Statistics for CEO Compensation and the Explanatory Variables

Mean Std.Dev. Median Maximum Minimum

Panel A: Dependent VariableCOMP 194.15 115.14 170.00 640.00 80.00

Panel B: Explanatory VariablesBoard compositionBDSIZE 5.86 1.50 6.00 9.00 1.00CEOBD 0.13 0.33 0.00 1.00 0.00BUSY 0.30 0.32 0.21 1.00 0.00DIRREP 0.54 0.50 1.00 1.00 0.00INSIDE 0.13 0.21 0.00 0.86 0.00GREY 0.17 0.33 0.00 0.17 0.00

Discretion/complexityFSIZE 162027.45 350919.75 58331.00 2309791.00 2619.00NSUB 1.68 2.50 1.00 16.00 0NSEG 1.96 0.77 2.00 5.00 1.00

PerformanceROA 0.0739 0.0922 0.0765 0.5200 �0.0190

OwnershipONEOWN 0.76 0.43 1.00 1.00 0.00LISTED 0.08 0.27 0.00 1.00 0.00

Notes:

The descriptive statistics are based on a sample of 80 New Zealand public sector companies.

Variable definitions:

COMP ¼ total CEO compensation;

BDSIZE ¼ number of directors at end of year;

CEOBD ¼ 1, if CEO is on board; 0, otherwise;

BUSY ¼ number of directors with 3 or more directorships/number of directors at end of

year;

DIRREP ¼ 1, if supplemental information on directors is provided; 0, otherwise;

INSIDE ¼ number of inside directors/number of directors at end of year;

GREY ¼ number of grey directors/number of directors at end of year;

FSIZE ¼ total assets (in thousands);

NSUB ¼ number of subsidiaries;

NSEG ¼ number of segments;

ROA ¼ operating income/total assets;

ONEOWN ¼ 1, if 100 percent owned by one owner; 0, otherwise;

LISTED ¼ 1, if listed on the NZSE; 0, otherwise.

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Table 2

Pearson Pairwise Correlations Between the Explanatory Variables

BDSIZE CEOBD BUSY DIRREP INSIDE GREY FSIZE NSUB NSEG ROA ONEOWN LISTED

BDSIZE 1.000CEOBD �0.092 1.000BUSY 0.074 0.355** 1.000DIRREP 0.234* 0.047 0.385** 1.000INSIDE �0.158 0.043 0.115 0.014 1.000GREY 0.086 �0.063 �0.058 �0.080 �0.241* 1.000FSIZE 0.242* 0.237* 0.343** 0.072 �0.151 �0.081 1.000NSUB 0.234* 0.034 0.373** 0.252* �0.101 �0.137 0.385** 1.000NSEG 0.160 0.019 0.009 0.282* �0.015 0.059 0.063 0.243* 1.000ROA �0.027 0.146 0.103 0.033 �0.090 0.090 0.081 0.054 �0.027 1.000ONEOWN �0.150 �0.144 �0.134 �0.223 �0.068 0.040 �0.014 �0.014 �0.066 �0.154 1.000LISTED 0.217 0.179 0.132 0.169 �0.114 �0.132 0.077 0.094 0.262* 0.201 �0.510** 1.000

Notes:

See Table 1 for variable definitions. The correlations are based on a sample of 80 New Zealand public sector companies.

*Significant at the 0.05 level based on a two-tailed test.

**Significant at the 0.01 level based on a two-tailed test.

450

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NSUB (r ¼ 0.373) and CEOBD (r ¼ 0.355). Thus, busy directors are more

likely to be found on boards where the company is large, where the company

has numerous subsidiaries, and where the CEO is a member of the board.

Table 3 contains the results for a regression model where the dependent

variable is COMP and the independent variables include the board, discre-

tion/complexity, performance, ownership, and industry variables.18 The overall

model is significant (F ¼ 10.112, p ¼ 0.000) and has an adjusted R2 of 67.5

percent. Thus, the model explains 67.5 percent of the cross-sectional variation in

CEO compensation in our sample of New Zealand public sector entities. While

obviously not strictly comparable because of differences in the sample and

variables, our model’s R2 is in the same range as Cyert et al. (1997) and Core

et al. (1999). For example, Cyert et al.’s (1997, Table 4) adjusted R2s range from

51 to 58 percent while Core et al.’s (1999, Table 2) adjusted R2s are 62.1 percent

and 52.6 percent for their Cash and Salary subsamples respectively.

Of the board structure measures, we find that BDSIZE is significant at the

0.005 level based on a one-tailed test. This is consistent with Core et al. (1999)

and with Talmor and Wallace’s (2000) cash-based compensation results. The

significant positive coefficient on BDSIZE is consistent with the view that large

boards are less effective than small boards (Jensen 1993).

CEOBD is also significant with a positive coefficient at the 0.01 level. This is

consistent with the findings for the CEO-chair variables used by Cyert et al.

(1997) and Core et al. (1999). As Boyd (1994) suggests when the CEO is on the

board, board members may be less objective and critical which reduces board

oversight and control. Additionally, DIRREP is significant with a negative

coefficient at the 0.05 level. Thus, the market for directors and directors’

reputations appear to have an influence on directors’ effectiveness. In particular,

higher quality directors constrain excessive compensation paid to CEOs. This is

consistent with Fama and Jensen’s (1983) human capital argument.

Contrary to Core et al. (1999), we find that BUSY is not significant. Thus,

directors with three or more directorships do not appear to be any less effective

than other directors. As suggested above, a possible explanation is that BUSY

also proxies for the director’s reputation or expertise. That is, a director may be

on several boards because he or she has the knowledge and skills needed for the

position. This positive effect may counterbalance the negative effect of having

too little time.19

The coefficient on INSIDE is not significant. Contrary to expectations,

INSIDE has a negative coefficient, although this is consistent with Core et al.

(1999) who find a negative relation between inside directors and CEO compen-

sation.20 While GREY has a positive coefficient as expected, it is also not

significant. This is contrary to Core et al. (1999), but Talmor and Wallace

(2000) find that their grey directors variable is not significant in their full sample

tests. Also and more generally, as Core et al. (1999) point out, the past empirical

evidence for these measures of board independence has been mixed.

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Table 3

Regression of CEO Compensation on Board, Discretion/Complexity,

Performance, Ownership, and Industry Control Variables

Variable Expected Sign Coefficient t-value Significance F-statistic

Board compositionBDSIZE þ 17.563 2.859 0.003CEOBD þ 60.118 2.317 0.012BUSY þ 6.039 0.196 0.423DIRREP – �33.457 �1.814 0.038INSIDE þ �18.636 �0.447 0.329GREY þ 4.664 0.178 0.430

Discretion/complexity 2.418*

FSIZE þ 0.00015 5.793 0.000NSUB þ 12.678 3.266 0.001NSEG þ 20.175 1.648 0.052

Performance 6.352**

ROA þ 214.305 2.138 0.019

OwnershipONEOWN ? �8.548 �0.324 0.747LISTED ? 67.109 1.696 0.095

Industry 1.908*

AIRPORT ? �44.494 �1.144 0.257FOREST ? �40.545 �0.733 0.466HEALTH ? 12.369 0.390 0.698POWER ? �90.913 �3.359 0.001PORT ? �127.166 �3.059 0.003RESEARCH ? �47.932 �1.512 0.136

4.019**Constant ? 74.052 1.545 0.128

Model summaryAdjusted R2 0.675F-statistic 10.112F significance 0.000Observations 80

Notes:

See Table 1 for variable definitions except for industry variables. The industry variables are

indicator variables coded as 1 if the company is in the industry and 0 if not. Significance levels

are based on a one-tailed test where a sign is predicted and a two-tailed test otherwise.

*Significant at the 0.05 level.

**Significant at the 0.01 level.

452 CAHAN, CHUA AND NYAMORI

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Of all the independent variables, FSIZE is the most important determi-

nant of CEO compensation (t ¼ 5.793, p ¼ 0.000) – CEOs in larger

public sector companies get paid more than their counterparts in smaller

public sector companies. This is consistent with studies such as Cyert et al. (1997),

Core et al. (1999) and Talmor and Wallace (2000). In addition, NSUB and

NSEG are significant at the 0.001 and 0.05 levels respectively. Together, this

suggests that CEO compensation increases with complexity whether measured by

scale or scope.

Likewise, our performance variable, ROA, is significant with a positive coeffi-

cient. This indicates that for our sample CEO compensation increases with

profitability which is consistent with Cyert et al. (1997), Core et al. (1999) and

Talmor and Wallace (2000) and with numerous studies that examine the rela-

tionship between pay and performance (e.g., Ke, Petroni and Safieddine, 1999).

For the ownership variables, LISTED is significant at the 0.10 level. The

positive coefficient suggests that listed firms pay their CEO more than the non-

listed firms. Though this could suggest that boards of listed firms are less

effective, a more likely explanation is that the CEO is being compensated for

the higher risk associated with running a listed company. The second ownership

variable, ONEOWN, is not significant. Thus, whether the public sector com-

pany has one owner or several owners does not make a difference in CEO

compensation for our sample. While both Cyert et al. (1997) and Core et al.

(1999) find support for their ownership variables, their contexts are different as

they focus on private sector entities. As discussed above, the lack of alienable

residual claims in the public sector severely weakens the incentives of owners to

monitor, and even 100 percent ownership may not create powerful enough

incentives to closely monitor CEO compensation.

We also examine the explanatory power of each category of independent

variables by computing the F-statistic for the four categories with more than one

variable. These results are also reported in Table 3. We find that on a joint basis

each of the four categories – i.e., the board structure variables, the discretion/

complexity variables, the ownership variables, and the industry variables – have

significant incremental explanatory power at the 0.05 level or better.

Given the large number of variables, we examine the data for multicollinearity

by examining the variance inflation factor (VIF ) for each independent variable.

Neter, Wasserman and Kutner (1985) note that a VIF in excess of 10 is usually

seen as a sign of multicollinearity. For our variables, the highest VIF is 3.803

which suggests multicollinearity is not severe in our sample.21

Table 3 suggests that the incremental explanatory power of the different

classes of variables differs. To examine the relative explanatory power of these

classes, we use an approach used by Talmor and Wallace (2000) and compute

the adjusted R2 for the four categories of the independent variables, i.e., discre-

tion/complexity, performance, board composition, and ownership, on an indi-

vidual basis (because the industry variables are included for control purposes, we

include these in all the models we estimate).

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The results (untabulated) show that when the incremental explanatory power

of each category is considered individually (i.e., with no variables from other

categories in the model), the discretion/complexity variables explain 58.2 per-

cent of CEO compensation, the board composition variables explain 33.1

percent, the ownership variables explain 7.2 percent, and performance explains

3.1 percent. On this basis, the board effectiveness variables are clearly the second

most important category of variables after the discretion/complexity variables.22

We also compute the dollar effect on CEO compensation by multiplying a one

standard deviation change in CEO compensation by the standardized coeffi-

cients of each independent variable in the regression model in Table 3 similar to

Talmor and Wallace (2000). This allows us to assess the economic significance of

the individual variables.

The results are reported in Table 4. We find that FSIZE has the biggest dollar

effect on CEO compensation – an increase of $350,920 in total assets, which is

one standard deviation for that variable, is associated with a $53,540 increase in

compensation. A $53,540 increase represents 27.6 percent of the mean CEO

compensation. The next largest increase in CEO is due to NSUB ($31,778 for

every 2.5 segments), but two board variables – BDSIZE and CEOBD – are next

in line in terms of economic significance. A one standard deviation increase in

BDSIZE (1.50 board members) increases CEO compensation by $26,380, and a

one standard deviation increase in CEOBD increases CEO compensation by

Table 4

Economic Significance of the Explanatory Variables

Variable Standardised Coefficient Change in CEO Compensation

Board effectivenessBDSIZE 0.229 26,380CEOBD 0.174 20,034BUSY 0.017 1,958DIRREP �0.146 �16,810INSIDE �0.033 �3,800GREY 0.013 1,497

Discretion/complexityFSIZE 0.465 $53,540NSUB 0.276 31,778NSEG 0.135 15,544

PerformanceROA 0.172 19,804

OwnershipONEOWN �0.032 �3,684LISTED 0.154 17,732

Note:

See Table 1 for variable definitions.

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$20,034. A third board variable – DIRREP – is also economically significant if

one uses 5 percent of the mean CEO compensation ($9,708) as a cut-off for

economic significance. A one standard deviation change in DIRREP decreases

CEO compensation by $16,810. Thus, these three board variables appear to

have economic significance as well as statistical significance.

To provide further insight on our board composition variables, we divide the

five board variables into three sub-categories based on Milliron (2000). In her

study, Milliron identifies three sub-categories for her board variables – board

effectiveness, accountability, and independence.

Milliron’s (2000, p. 12) board effectiveness category focuses on the board’s

structural characteristics – e.g., board size, term limits on directors, number of

other directorships, and number of directors over 69 years of age. Accordingly,

we use BDSIZE, CEOBD and BUSY to represent board effectiveness.

Milliron (2000) sees independence as being related to the ties the director has

with the company. She uses the percentage of inside directors and grey directors

as measures that are inversely related to independence. Correspondingly, we

classify our INSIDE and GREY variables as independence measures.

Milliron (2000) defines accountability in terms of the alignment of the direc-

tors’ incentives and the firms’ incentives. She uses measures such as the percen-

tage of shares owned by the directors and whether part of the director’s

compensation is equity based to represent accountability. Because our compa-

nies, for the most part, lack tradable shares, it is not possible for them to use

equity shares as an alignment mechanism. In the absence of this mechanism,

accountability will be driven largely by human capital factors, i.e., as Fama and

Jensen (1983) posit, directors will want to develop reputations as effective

directors. Thus, we use our DIRREP variable to represent accountability.

Similar to Milliron (2000), we use a principle components analysis to identify

single measures for the board effectiveness sub-category and independence sub-

category. We first factor analyze BDSIZE, CEOBD and BUSY and then factor

analyze INSIDE and GREY. Each analysis yields only one factor with an

eigenvalue in excess of one, and we use the factor scores for these two factors

to represent board structure and independence. Since we have only one variable

in the accountability sub-category, we use DIRREP to represent accountability.

We include the three measures representing board structure, accountability, and

independence in place of the individual board variables in the regression model

shown in Table 3. These results are provided in Table 5. We find that the board

effectiveness and accountability sub-components are significant and correctly

signed, but the independence variable is not significant. While the latter result is

not surprising since the INSIDE and GREY are insignificant, one explanation is

that the relatively smaller percentage of inside and grey directors in the public sector

companies – 30 percent vs. 49.9 percent for Cahan and Wilkinson’s (1999) sample

of private sector companies in NZ – diminishes their influence.

As a final analysis, we compute a composite board measure. We do this by

first reverse coding the accountability (i.e., DIRREP) variable so 1 corresponds

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with low director quality and then standardizing the board structure, account-

ability, and independence variables used in Table 5 so each has a mean of 0 and

a standard deviation of 1. Next, we add the standardized values for three

variables for each observation. While this assumes that each factor is equally

important, lacking a more comprehensive theory of corporate governance, this

seems reasonable. Under this scoring system, a high score indicates a weaker

board while a low score suggests a stronger board.

Using this composite figure in place of the three sub-components, we find

(results not tabulated) that its coefficient is significant (t ¼ 2.188, p < 0.032) and

positively signed. This result indicates that weak boards pay more CEO com-

pensation than stronger boards after controlling for discretion/complexity, per-

formance, and industry variables, which confirms our earlier results.

In their paper, Core et al. (1999) note that finding weaker boards are asso-

ciated with higher compensation could be interpreted in two ways. Either weak

boards succumb to managerial power and pressure (i.e., management is

Table 5

Regression of CEO Compensation on Composite Board Variables, and

Discretion/Complexity, Performance, Ownership, and Industry Control

Variables

Variable Expected Sign Coefficient t-value Significance

Board compositionBOARD EFFECTIVENESS þ 13.213 1.456 0.075ACCOUNTABILITY � �29.536 �1.623 0.055INDEPENDENCE þ 8.522 1.031 0.153

Discretion/complexityFSIZE þ 0.00018 6.705 0.000NSUB þ 13.964 3.609 0.001NSEG þ 19.646 1.559 0.062

PerformanceROA þ 224.849 2.152 0.018

OwnershipONEOWN ? �13.284 �0.485 0.629LISTED ? 70.550 1.791 0.078

Model summaryAdjusted R2 0.642F-statistic 10.451F significance 0.000Observations 80

Notes:

See Table 1 for variable definitions. Industry control variables are not shown. Significance

levels are based on a one-tailed test where a sign is predicted and a two-tailed test otherwise.

456 CAHAN, CHUA AND NYAMORI

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entrenched) or high compensation is the result of efficient contracting where

CEOs with more skills and responsibilities are paid more. For example, a

positive and significant coefficient for CEOBD could arise if a CEO who is

also on the board and has more responsibility receives additional compensation

for that (i.e., an efficient response). Core et al. (1999, p. 391) examine these two

explanations by computing an excess compensation variable which they define

as the ‘predicted component of compensation arising from the board and own-

ership structure variables in excess of our controls for the standard economic

determinants of compensation.’ However, Talmor and Wallace (2000), in con-

ducting similar tests, use the residual from regressing performance, CEO, board

effectiveness, and discretionary variables on CEO total compensation as a

measure of excess compensation. We use the Talmor and Wallace measure

because if board structure is endogenous, board structure is determined by

firm characteristics and the Core et al. measure will reflect these characteristics

rather than the board’s monitoring ability.

While both Core et al. (1999) and Talmor and Wallace (2000) relate their

excess compensation measure to two-year ahead performance measured by

accounting ROA and stock returns, because we use current data, at the time

of our study we do not have two-year ahead data for our sample. Additionally,

aside from the six listed firms, we do not have stock returns.

Instead, we examine the relationship between excess compensation and

board turnover. We expect that in the worst case, both management and

the board are entrenched. When the board is entrenched, board members

are not effective monitors, and they can become puppets of the manage-

ment. Here, managers would have little incentive to push for changes in the

board. Thus, entrenched boards should have low turnover. Also, since

entrenched boards have weak control over management, CEO compensa-

tion is likely to be excessive in these cases. Accordingly, if management/

board entrenchment is driving our results, we expect that excess compensa-

tion will be high in companies where board turnover is low. However, if the

alternative hypothesis applies – i.e., low board turnover is an efficient

response (e.g., board members serve extended terms because they are

doing a good job), we expect excess compensation in low board turnover

companies will be equal to or lower than excess compensation in high board

turnover companies.

To test this, we use two measures of board turnover. First, we use the number

of new directors (i.e., directors appointed during the year) as a percentage of total

directors at the end of the year. Second, we use total board turnover which is

defined as the sum of number of new directors and the number of directors

leaving during the year divided by two times the total number of directors. This

number will differ from the first measure when the total board size changes as a

result of board turnover (e.g., if more new directors are appointed than the

number resigning). We classify observations into a low (high) turnover group if

the observation is below (above) the median.

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Table 6 provides these results. We use the undeflated excess CEO compensa-

tion and the excess CEO compensation deflated by CEO compensation in line

with Talmor and Wallace (2000). We find that for both measures, when board

turnover is low, excess compensation is high, and the four t-values are significant

at the 0.10 level or better. This supports the view that boards with low turnover

are weaker and are more likely to give in to management. Thus, our results are

consistent with Core et al. (1999) who find evidence of managerial entrenchment

in private sector firms.

CONCLUSION

We examine the association between several board characteristics used in prior

private sector-based research (e.g., Cyert et al., 1997; Core et al., 1999; and

Talmor and Wallace, 2000) and the level of CEO compensation. In addition, we

include three other categories of explanatory variables – i.e., managerial discre-

tion/task complexity, performance, and ownership variables – and industry

control variables.

Using a sample of 80 New Zealand public sector companies, we find that

similar to private sector studies, board size, whether the CEO sits on the board,

and director quality are related to CEO pay. However, variables representing

the percentage of busy directors, grey directors, and inside directors are not

significantly related to pay, but the prior evidence on these variables has been

mixed. Also, out of the four categories of explanatory variables, we find that our

Table 6

Results for t-Tests Comparing Excess CEO Compensation in Companies with

High and Low Board Turnover

Mean Excess CEO Compensation

Undeflated Deflated

New directors No new directors 0.2962 0.6018New directors 0.2307 0.4900t-value 1.512* 1.667*

Total turnover Below median 0.3056 0.6324Above median 0.2265 0.4650t-value 1.867** 2.593***

Notes:

*Significant at the 0.10 level based on a one-tailed test.

**Significant at the 0.05 level based on a one-tailed test.

***Significant at the 0.01 level based on a one-tailed test.

458 CAHAN, CHUA AND NYAMORI

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board variables have the second highest incremental explanatory power after

variables related to managerial discretion and complexity. This is similar to

Talmor and Wallace (2000) who use a much larger sample of US financial

sector firms. Lastly, we find boards with low turnover pay excessive compensa-

tion to their CEOs which suggests that managerial entrenchment, not efficient

contracting, is behind our results. In this way, our results are consistent with

Core et al. (1999).

The similarity between our results and those in prior research are striking,

particularly given dramatic differences in entity size, focus, and ownership and in

the way CEO compensation packages are structured (e.g., private sector CEO pay

packages often include stock-based compensation). However, this is reassuring as it

suggests that the academic theories on which the prior research is based are not

context specific and that it confirms that organisational form is important.

Our results suggest that board structure is important in the New Zealand

public sector. Public sector boards that exhibit characteristics that have been

shown to be associated with board effectiveness in the private sector are more

likely to constrain CEO pay, after controlling for other non-board factors

affecting CEO pay. That is, similar to the private sector, weaker boards pay

CEOs more.

Our research makes several contributions. First, we contribute to prior

academic research. Specifically, prior studies have not examined the relation

between board structure and CEO compensation in public sector compa-

nies, and Hermalin and Weisbach (2000) note that generally there is a lack

of empirical research examining corporate governance effectiveness in the

public sector. Second, our study has practical implications. While we

acknowledge that we examine only one type of board decision, we find

evidence that board structure matters in the public sector in the same way it

matters in the private sector. Thus, our results suggest that efforts to adopt

private sector-style boards in the public sector are not unfounded. Third,

our research adds directly to the policy debate regarding corporate govern-

ance in the public sector. For example, the OECD (2004) recently issued

draft guidelines on corporate governance in state-owned enterprises. Our

research provides evidence that may be useful in assessing the appropriate-

ness of the proposed guidelines for boards in these entities (e.g., see section

VI of OECD 2004).

APPENDIX

AgResearch Ltd

Airways Corporation of New Zealand

Ltd

Alpine Energy Ltd

Animal Control Products Ltd

Auckland Healthcare Ltd

BOARD STRUCTURE AND EXECUTIVE COMPENSATION 459

# Blackwell Publishing Ltd 2005

Auckland International Airport Ltd

Buller Electricity Ltd

Canterbury Health Ltd

Capital Coast Health Ltd

Central Electric Ltd

CentrePort Ltd

Christchurch International Airport Ltd

Citiworks Ltd

Counties Manukau Health Ltd

Counties Power Ltd

Crop and Food Research Ltd

Dunedin International Airport Ltd

Eastland Network

Electricity Ashburton Ltd

Electricity Invercargill Ltd

Environmental Science and Research Ltd

Good Health Wanganui Ltd

Government Property Services Ltd

Hawkes Bay Power Ltd

Health South Canterbury Ltd

Healthcare Hawkes Bay Ltd

Horticulture and Food Research

Institute of New Zealand Ltd

Housing New Zealand Ltd

Hutt Valley Health Ltd

Industrial Research Ltd

Institute of Geological and Nuclear

Services Ltd

Invercargill Airport Ltd

Landcare Research Ltd

Learning MediaLtd

Lyttleton PortCompany Ltd

MainPower New Zealand Ltd

Marlborough Electric Ltd

Meterological Service of New Zealand

Ltd

MidCentral Health Ltd

National Meteorological Service of

New Zealand Ltd

Nelson Marlborough Health Services

Ltd

New Zealand Forest Research

Institute Ltd

New Zealand Post Ltd

New Zealand Symphony Orchestra Ltd

Northland Health Ltd

Northland Port Corporation (NZ)

Ltd

Northpower Ltd

Orion New Zealand Ltd

Otago Power Ltd

Palmerston North Airport Ltd

Port of Auckland Ltd

Port of Gisborne Ltd

Port of Napier Ltd

Port of Nelson Ltd

Port of Tauranga Ltd

Port of Timaru Ltd

PowerNet Ltd

Queenstown Airport Corp Ltd

R Corporation Ltd

ScanPower Ltd

Selwyn Plantation Board Ltd

Solid Energy New Zealand Ltd

South Port New Zealand Ltd

Southern Health Crown Enterprise

Taranaki Healthcare Ltd

Tasman Energy Ltd

The Power Company Ltd

Timberlands West Coast Ltd

Top Energy Ltd

Transpower New Zealand Ltd

TVNZ Ltd

Vehicle Testing New Zealand Ltd

Waikato Regional Airport Ltd

Waipa Networks Ltd

Wairarapa Crown Health Ltd

Waitaki Power Ltd

Waitemata Health Ltd

Watercare Services Ltd

Westgate Transport Ltd

Westpower Ltd

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NOTES

1 Criticism over CEO pay is not limited to the public sector in New Zealand. Pay packages ofCEOs in private sector companies have also come under attack (e.g., Howie, 2000).

2 In December 2003, the Labour government introduced the Crown Entities Bill which includesprovisions that would curtail taxpayer-funded golden handshakes (Berry, 2003).

3 Hermalin and Weisbach (2000) and Brickley et al. (2003) among others have recently made callsfor more research on non-private sector boards.

4 In New Zealand public sector entities, the board has the primary responsibility for employing andremunerating the CEO although under various legislation the State Services Commissioner mayhave an oversight/consultative role (e.g., see www.ssc.govt.nz).

5 For example, Brockett (2000, p. 1) reports that the NZ government ‘is looking to raid the balancesheets of five key state-owned enterprises to free up cash for its big spending programme.’ Underthe plan, the government would force the state-owned enterprises to pay a special dividend to payfor social policies such as low-income housing (Brockett, 2000).

6 For example, shares in state-owned enterprises and crown-owned companies are held by ashareholding minister.

7 Boards are ultimately responsible to their government owners in the same way private boards areresponsible to their shareholders. In the New Zealand public sector, the Treasury, the CrownCompany Monitoring Advisory Unit, and the State Services Commissioner can also have over-sight roles.

8 Other recent studies examine CEO compensation in US nonprofit hospitals (e.g., Brickley andvan Horn, 2002; and Eldenburg and Krishnan, 2003) but do not explicitly examine the link withboard structure. Similarly, Baber, Daniel and Roberts (2002) examine CEO compensation incharitable organisations but do not examine board characteristics.

9 This does not mean boards are unimportant in the private sector. Indeed as Jensen (1993, p. 862)notes: ‘The board, at the apex of the internal control system, has the final responsibility for thefunctioning of the firm.’

10 While public sector boards have a significant control function, boards in the public sector alsosuffer from weaknesses that may counteract their effectiveness (e.g., see Herzlinger, 1996; andBrickley et al., 2003). The directors of public sector companies are agents of the governmentwhich results in agency problems. While the same agency problems arise in private sectorcompanies, the lack of alienable residual claims again puts the public sector entity at a disadvan-tage. For example, unlike private sector companies, directors cannot be given shares to align theirinterests with the shareholders. Likewise, to the extent that a director’s reputation and humancapital will be tied to the firm’s performance, it is more difficult to assess the firm’s performance inthe absence of traded shares. Thus, the incentive of directors to expend time and energy to closelymonitor the entity may be reduced in public sector settings resulting in weaker oversight (e.g., seeSmith, 2000).

11 In empirical tests, outside directors are often subdivided into independent outside directors andaffiliated or grey directors where the latter are outsiders who have close ties with the company(e.g., Lee et al., 1992).

12 However, Baysinger and Butler (1985) argue the opposite, i.e., large boards have more diverseskills which are useful in dealing with the various functions the board must fulfill.

13 Other factors which may impact on board effectiveness include the probability of bankruptcy(e.g., Jensen, 1993; and Cyert et al., 1997), the director’s age (e.g., Core et al., 1999), and thetenure of the CEO (e.g., Talmor and Wallace, 2000).

14 We examine the non-respondents and find no evidence of industry clustering.15 We ran sensitivity tests with COMP set at $90,000 and at $80,000, and with these 12 observations

omitted without any significant changes in the results.16 While Coughlan and Schmidt (1985) and Murphy (1985) find support for an association between

market-based rates of returns and CEO compensation and while stock options are an importantand useful part of an overall compensation measure, share prices are very noisy signals ofperformance (e.g., Talmor and Wallace, 2000). This is because share prices contain a significantmarket component and also are affected by changes in demand that may not be related tomanagerial performance.

17 The maximum is for Contact Energy Limited.18 We also ran the model using the natural log of COMP. The results are qualitatively the same.

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19 Talmor andWallace (2000) find that the results for their busy variable are inconsistent. For example,their busy variable is positive and significant in only three of the six models in their Table V.

20 Bhagat and Black (1999) find a negative relation between board independence and firm performance.21 We also examine the possible effects of multicollinearity by re-estimating two reduced models of

regression model in Table 3 similar to Talmor and Wallace (2000). Using the backward regres-sion procedure in SPSS, we estimate models with 12 and 9 independent variables. The coeffi-cients and t-values for the significant variables are very stable when compared with the resultsfrom the full model which suggests that over-identification is not a problem.

22 Our results are very similar to Talmor and Wallace (2000). They find that the discretion/complexity and board structure variable have the most explanatory power, followed by ownershipand then performance.

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