Journal of Contemporary Accounting & Economics 5 (2009) 20–33

Contents lists available at ScienceDirect

Journal of Contemporary
Accounting & Economics
journal homepage: www.elsevier.com/locate/jcae

The impact of audit committee quality on financial reporting quality

and audit fees
Elizabeth A. Rainsbury a,*, Michael Bradbury b, Steven F. Cahan c
a
Unitec New Zealand, Private Bag 92025, Auckland, New Zealand
b
Massey University, Private Bag 102-904 NSMC, Auckland, New Zealand
c
University of Auckland, Private Bag 92019, Auckland, New Zealand

a r t i c l e i n f o a b s t r a c t

Article history: This study examines the association between the quality of audit committees on financial
Received 10 March 2008 reporting quality and external audit fees in an environment where the formation of audit
Revised 19 December 2008 committees was unregulated. The study uses a sample of 87 New Zealand firms in 2001
Accepted 18 March 2009
when no regulations or listing rules existed for audit committees. The results show no sig-
Available online 30 July 2009
nificant association between the quality of an audit committee and the quality of financial
reporting. These results are robust to alternative measures of earnings quality. Similarly,
Keywords:
the quality of audit committees has little impact on the level of fees paid to external audi-
Audit committees
Auditing
tors. The results suggest that the benefits of ‘best practice’ audit committees may be less
Financial reporting quality than anticipated by regulators and policymakers.
Audit fees Ó 2009 Elsevier Ltd. All rights reserved.

1. Introduction

We examine firms that voluntarily adopt a high quality audit committee in an environment, New Zealand, where prior to
2003, the formation of audit committees was completely unregulated. Thus, compared to other countries such as the US
where New York Stock Exchange (NYSE) listing requirements have long required audit committees and the UK where the
high profile Cadbury Code published in 1992 strongly recommends audit committees with ‘at least three non-executive
directors’, prior to 2003, New Zealand companies had considerable leeway in deciding whether an audit committee should
be formed and its composition if one was formed. Thus, in the pre-2003 environment, the existence and composition of audit
committees in New Zealand varied widely, providing a unique opportunity to examine the benefits that might accrue to
firms that adopted what now would be considered ‘best practice’ audit committees. Since audit committee formation was
voluntary, the strength of the audit committee should be closely related to the expected benefits associated with the audit
committee as a firm would have no incentive to create a best practice audit committee unless it was the optimal choice. As a
result, our setting differs from the settings used in most prior studies where regulations or strong encouragement through
corporate codes could force firms to adopt best practice audit committees as a second-best option.
We examine whether New Zealand firms with high quality audit committees in 2001 have higher financial reporting
quality and lower external audit fees than New Zealand firms with a lower quality audit committee or no audit committee.
We measure audit committee quality based on the quality of its membership using guidelines that were issued by the New
Zealand Securities Commission (NZSC) in 2004. We find that, in our sample of New Zealand listed companies, firms that had
voluntarily adopted higher quality audit committees did not have higher quality earnings. We also find that having a higher
quality audit committee did not have an impact on audit fees. Since we do not find better quality financial reporting or lower

* Corresponding author.
E-mail address: erainsbury@unitec.ac.nz (E.A. Rainsbury).

1815-5669/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved.
doi:10.1016/j.jcae.2009.03.002
 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33 21

audit fees in a setting where firms were free to create a high quality audit committee, our results suggest that the benefits of
requiring firms to adopt a ‘best practice’ audit committee may be less than anticipated by policymakers and regulators.
This study contributes to the extensive literature on the effects of audit committee quality in two important ways. First,
rather than examine a market where audit committees have long been regulated (e.g., via listing rules in the US since 1978)
or included in corporate governance codes (e.g., in the UK’s Cadbury Code since 1992), we examine an environment where
firms faced little pressure to form audit committees. Thus, we can assume all firms choose their optimal audit committee
(which could be no audit committee) which is different from the US or UK where the audit committee choice could reflect
a second-best option. This allows us to provide a cleaner test of the benefits of high quality audit committees. Second, we
adopt Fields et al.’s (2001) recommendation, and in measuring financial reporting quality, we resort to a back-to-basic mea-
sure of earnings management similar to that used by Zmijewski and Hagerman (1981).
Our results are useful for informing policymakers. Even though we focus on an environment where only those firms with
the greatest benefits would be expected to voluntarily adopt the best practice guidelines, we find that high quality audit
committees do not constrain aggressive accounting choices and do not reduce fees paid to external auditors. This suggests
that the best practice guidelines are too simplistic to lead to real improvement or that the effectiveness of the audit com-
mittee is contingent on other corporate governance features, e.g., a high quality audit committee might only be effective
in the presence of a high quality board of directors. Alternatively, the effectiveness of audit committees may actually be a
function of their visibility in the public arena. In other words, having the importance of audit committees highlighted in cor-
porate codes or regulations such as the Sarbanes-Oxley Act (SOX Act ) (2002) may increase the pressure on these committees
to perform. This may explain why some US and UK studies (e.g., Beasley et al., 2000; Peasnell et al., 2001; Klein, 2002a; Far-
ber, 2005) find that audit committees can be beneficial.
The remainder of the study is organized as follows: Section 2 discusses prior empirical literature on the impact of audit
committee quality on financial reporting quality and audit fees. Section 3 discusses the variables, models, and data. Section 4
reports results for our analyses based on financial reporting quality. Section 5 reports our audit fee results. Section 6 provides
a conclusion.

2. Prior empirical literature

In this section, we examine the literature related to (1) the relation between audit committee quality and financial report-
ing quality, and (2) the relation between audit committee quality and audit fees.

2.1. Relation between audit committee quality and financial reporting quality

Research suggests that audit committees can strengthen the quality of financial reporting. Firms involved in fraudulent
financial reporting are less likely to have an audit committee (Dechow et al., 1996; McMullen, 1996). Fraudulent reporting
firms are also less likely to have audit committees that are active and independent (Beasley et al., 2000) or audit committees
that are active and have financial expertise (Farber, 2005). Firms with audit committees that are independent and active are
also less likely to experience other accounting irregularities (Dechow et al., 1996; McMullen and Raghunandan, 1996; Abbott
and Parker, 2000b; Peasnell et al., 2001). There is also evidence that audit committees with a majority of independent direc-
tors reduce earnings management (Klein, 2002a; Jenkins, 2003), and DeFond and Jiambalvo (1991) find that firms which
overstate their earnings are less likely to have an audit committee.
Thus, prior research suggests that audit committee quality can improve financial reporting quality by reducing the inci-
dence of fraudulent reporting, accounting irregularities, and earnings management. Therefore, we hypothesize that high
quality audit committees will lead to less aggressive accounting choices.

2.2. Relation between audit committee quality on the audit function and audit fees

Some studies suggest that independent and active audit committees with accounting expertise undertake activities that
enhance the audit function. High quality audit committees are more likely to support the internal audit function (Raghun-
andan et al., 2001), appoint industry specialist auditors (Abbott and Parker, 2000a), and are more likely to appoint high qual-
ity auditors when switching between auditors (Abbott and Parker, 2002). They are also less likely to have internal control
problems (Krishnan, 2005), and in accounting disputes with management, audit committee members with business back-
grounds are more likely to support the independent auditor (Knapp, 1987). Furthermore, DeZoort and Salterio (2001) find
audit committees with independent members and audit knowledge are more likely to support an independent auditor in
a substance-over-form dispute with management.
While a positive relation between higher quality audit committees and an enhanced audit function is widely supported
by prior studies, the relation between high quality audit committees and audit fees is less clear. From their meta-analysis,
Hay et al. (2006) conclude that evidence on the relation between corporate governance and audit fees is limited and the evi-
dence is mixed.
For example, Carcello et al. (2002) find that board independence, diligence and expertise are positively correlated with
the level of audit fees for 258 Fortune 100 firms. Audit committee independence and expertise are also positively correlated
22 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33

with the level of audit fees but not when the board independence and expertise variables are included. They argue that the
results are consistent with board of directors demanding a higher quality audit to protect their own interests (i.e., to main-
tain their reputational capital, avoid legal liability) and to promote shareholder interests. Similarly, in a UK based study,
Goddard and Masters (2000) find that audit committees meeting the Cadbury Report recommendations have no impact
on audit fees. In contrast, Abbott et al. (2003) find that audit committees with independence and expertise are positively
associated with audit fees in the US, and Collier and Gregory (1996) find a positive association between audit fee and audit
committees for a sample of firms in the UK.
In summary, prior research on the relation between audit committee quality and audit fees is mixed. However, if audit
committees are successful in reducing aggressive financial reporting as prior research suggests, we hypothesize that firms
with higher quality audit committees will have lower inherent risk and lower audit fees.

3. Variables, models and data

In this section, we describe how we measure audit committee quality, financial reporting quality, and audit fees. We also
describe the models and our sample.

3.1. Audit committee quality

Internationally, there is consensus that audit committees should comprise a majority of independent directors and have
at least one member with financial expertise (Commonwealth of Australia, 2002; European Commission, 2002; Financial
Reporting Council (FRC), 2003).
Until 2003, New Zealand had a regime where listed companies voluntarily formed audit committees and selected the
membership that was appropriate for the firm unlike the US and UK where the stock exchange listing rules and taskforce
committees (e.g., the Public Oversight Board and Blue Ribbon Committee in the US and the Cadbury Committee in the
UK) have long provided strong recommendations about audit committees. Following the overseas lead, in late 2003, the
New Zealand stock exchange (NZX) introduced requirements for audit committee membership.1 In 2004, NZSC developed
a set of corporate governance principles (NZSC, 2004). The NZSC’s principles (which are more stringent than the NZX’s require-
ments) recommend that (1) audit committees comprise all non-executive directors, (2) have a majority of independent direc-
tors, and (3) have a member who is an accounting expert. We refer to audit committees that satisfy these recommendations as
‘best practice’ audit committees.
Based on these guidelines, we determine whether each firm had a best practice audit committee in 2001. In other
words, we use the NZSC principles to define a best practice audit committee, but we are interested in firms that volun-
tarily formed audit committees meeting these criteria before the principles became known. That is, some firms would
have created audit committees that had no executive directors, a majority of independent directors, and had accounting
expertise because they required an effective audit oversight function. While these firms may have been aware of the over-
seas guidelines (e.g., the Cadbury Code, Blue Ribbon Committee report), they were under no obligation to comply with
these.
Thus, we use three membership variables to identify best practice audit committees. The first variable captures whether
the firm has a best practice audit committee (ACBP). ACBP is coded 1 if it comprises solely non-executive directors, the
majority are independent directors, and it includes an accounting expert. Otherwise, ACBP is coded 0. This definition is con-
sistent with the NZSC (2004) and Australian Stock Exchange Corporate Governance Council (2003) requirements but is
more stringent than the NZX’s (2003) best practice code and less rigorous than the SOX Act (2002) and FRC (2003)
requirements.
The second audit committee variable, ACIND, measures audit committee independence. ACIND is coded 1 if the commit-
tee has 51% or more independent directors and 0 otherwise. An independent director is defined as one who is not employed
or closely affiliated with the company. This definition excludes a non-executive director who is a past employee of the com-
pany and/or has significant or business relationships with the firm. A director with a substantial equity holding is not con-
sidered an independent director even if not active in the management of the company. The definition of an independent
director is consistent with that recommended by the NYSE and NASD (1999). We use annual report disclosures, in particular
the related party disclosures in the notes to the financial statements, to identify affiliated directors.
The third audit committee variable measures accounting expertise. The variable, ACEXP, is coded 1 if the audit committee
includes a member who is a qualified chartered accountant (i.e., a member of a professional accounting body). The definition
of accounting expertise is largely consistent with the NZSC (2004), but is narrower than that legislated in the SOX Act. In the
SOX Act, the definition of financial expertise was widened to include presidents and chief executive officers in response to
criticism that a narrow definition of financial expertise would limit the pool of qualified directors able to be appointed as
experts (DeFond et al., 2005). A narrow definition of an accounting expert is adopted in this study because of a lack of con-
sistency in the disclosures of directors’ backgrounds in company annual reports in New Zealand.

1
The NZX’s Best Practice Code requires issuers to establish audit committees consisting solely of non-executive directors. It does not refer to independent
directors or financial expertise.
 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33 23

3.2. Financial reporting quality

A number of the studies evaluating the effectiveness of audit committees have focused on non-typical situations, such as
fraudulent reporting, where evidence of poor quality reporting is very clear. Evidence on fraud cases is not publicly available
in New Zealand, and therefore, we restrict our examination to a cross-sectional analysis of non-fraudulent cases.
In studies of non-fraudulent reporting, the empirical measure of earnings quality most often adopted is the sign or level of
discretionary accruals, measured using various models (e.g., Jones, 1991; Dechow et al., 1995; Kothari et al., 2005). However,
questions have been raised about the low power of discretionary accruals models (Dechow et al., 1995; Thomas and Zhang,
2000). Fields et al. (2001) suggest that researchers avoid the limitations of discretionary accruals models and adopt either
new statistical techniques or revert to a back-to-basics approach such as that used by Zmijewski and Hagerman (1981).
We adopt an approach similar to Zmijewski and Hagerman (1981), i.e., we first select five accounting choices and we then
use these to create an accounting quality score.

3.3. Accounting choices

Regulatory bodies have emphasized the importance of auditors reporting to audit committees on the degree of aggres-
siveness or conservatism of accounting choices (The Advisory Panel on Auditor Independence, 1994; NYSE and NASD,
1999.) For example, the SOX Act (2002) requires that auditors of issuers must report to audit committees on:
(1) all critical accounting policies and practices to be used; (2) all alternative treatments of accounting information within
generally accepted accounting principles that have been discussed with management officials of the issuer, (3) ramifica-
tions of the use of such alternative disclosures and treatments, and (4) the treatment preferred by the registered public
accounting firm (section 204).

Accounting policy choices that fall within GAAP, range somewhere along a continuum from conservative to aggressive. An
aggressive accounting choice accelerates revenue recognition (e.g., accelerating the recognition of revenue in a multi-year
contract) or delays expense recognition (e.g., understating provisions for bad debts and loan losses). A conservative account-
ing choice postpones revenue recognition or accelerates expense recognition. The short-term impact of these choices is that
aggressive choices are income-increasing and conservative choices are income-decreasing.
At the date of our study, there were no New Zealand accounting standards on revenue recognition, but several standards
dealing with expense recognition.2 Therefore, we focus on accounting choices relating to expense recognition and ignore rev-
enue recognition. For the purposes of this study, an accounting policy or estimate is aggressive (conservative) if it delays (accel-
erates) the recognition of expenses in comparison with other policies or estimates permitted within generally accepted
accounting practice.
Three accounting estimates and two accounting policy choices are selected.3 The five choices are selected because their
impact on earnings is clear-cut and information about the choice or estimate is routinely disclosed in financial statements
(Hagerman and Zmijewski, 1979). This latter requirement severely limits the number of items to be tested. The three accounting
estimates relate to the estimated useful lives of non-current assets, and the two accounting policy choices concern the recog-
nition of deferred tax and inventory valuation.

3.3.1. The estimated useful life applied to buildings

Buildings are selected as they form a reasonably homogeneous group of assets. New Zealand Financial Reporting Standard
(FRS) 3 on accounting for property, plant, and equipment states that the depreciable amount of an item of property, plant,
and equipment must be charged over the asset’s useful life. The estimated useful life is defined as the ‘period of time over
which the future economic benefits embodied in an asset are expected to be consumed by the entity’. FRS 3 allows managers
to choose the useful life of an asset class, but the number of years chosen must be disclosed in the financial statements.
The tax code specifies a useful life of 50 years for non-specialized buildings with concrete, steel or timber framing (Inland
Revenue, 2000). The 50-year useful life allowed for taxation purposes is used as a benchmark in this study to distinguish
between aggressive and conservative accounting choices. A firm adopting a useful life of buildings greater than 50 years
is considered to be selecting an aggressive accounting choice.

3.3.2. The estimated useful life applied to motor vehicles

Motor vehicles are selected as they also form a reasonably homogenous group of assets. For financial reporting purposes,
the requirements of FRS 3 apply. Similarly, for taxation purposes, the Inland Revenue Department specifies an estimated use-
ful life of five years for general motor vehicles (Inland Revenue, 2000). Once again, the useful life for tax purposes is used as a
benchmark to differentiate between aggressive and conservative accounting choices. A firm disclosing in its financial state-
ments a useful life exceeding five years for motor vehicles is considered to be using an aggressive estimate.

2
The Accounting Standards Review Board announced in December 2002 that New Zealand entities would be required to apply international financial
reporting standards from 1 January 2007, with an option to adopt earlier on or after 1 January 2005.
3
The number of choices is more extensive than prior studies using this research method. Hagerman and Zmijewski (1979) use four accounting choices,
Skinner (1993) uses three, Bowen et al. (1995) two, and Bradbury et al. (2003) one.
24 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33

Table 1
Financial reporting quality scoring system.

Accounting choice Conservative Neutral accounting = 0.5 Aggressive accounting = 1

accounting = 0
Estimated useful life of Useful life of 50 years A range below and above 50 years is specified, e.g., Useful life greater than 50 years
buildingsa or less 40–70 years
Estimated useful life of motor Useful life of 5 years or A range below and above 5 years is specified, e.g., Useful life greater than 5 years
vehiclesa less 5–10 years
Goodwill amortization Amortize over 10 years – Amortize over periods greater
or less than 10 years
Tax effect accounting Comprehensive basis – Partial basis
Assigning costs to inventory Weighted average Specific identification or combination of both FIFO First-in, first-out (FIFO)
and weighted average
a
Some firms report the useful life as a range over several categories of assets (rather than separate categories such as buildings and motor vehicles). For
these cases, if the range includes the threshold specified, i.e., 50 years for buildings and 5 years for motor vehicles, a score of 0.5 is given.

3.3.3. Goodwill amortization

Statement of Standard Accounting Practice (SSAP) 8 on accounting for business combinations requires goodwill to be rec-
ognized and amortized on a systematic basis. The standard specifies that the period of amortization should generally not
exceed 10 years, but in no case should it exceed 20 years. For this study, a firm that writes off goodwill over a period of
ten years or more is considered to be using an aggressive choice.

3.3.4. Tax effect accounting

SSAP 12 Accounting for Income Tax permits a choice between a comprehensive or partial basis to account for the effect of
timing differences. Under the comprehensive method, tax expense includes tax payable for the period plus the estimated tax
effects of all timing differences, whereas under the partial method, tax expense includes only those timing differences that
are likely to become payable at a future date. Firms must provide evidence that any timing differences not recognized are
unlikely to reverse. This requirement limits the number of companies eligible to apply the method. The partial method is
defined as an aggressive accounting choice because it will tend to recognize less tax expense.

3.3.5. Assigning costs to inventory

When prices are rising, using a first-in, first-out (FIFO) cost flow assumption for inventory yields a higher reported income
than the weighted average method.4 Because prices were rising during the period selected for the study, FIFO is considered an
aggressive accounting choice and weighted average is considered a conservative choice.5

3.4. Financial reporting quality score

Our measure of financial reporting quality is the aggregate accounting choice score (FRQUAL) of the individual accounting
choice scores for each firm. The scoring system used to assess a company’s accounting choices is reported in Table 1.
A firm receives a score of 1 for each aggressive accounting choice (policy or estimate). A policy or estimate that is con-
servative receives a score of 0. A score of 0.5 is given when the useful life of non-current assets spans both aggressive
and conservative ranges. For example, a score of 0.5 is given when the useful life of buildings is specified as a range of
40–70 years, which is both above and below the 50 years benchmark used to distinguish between aggressive and conserva-
tive estimates. Similarly, for inventory valuation where a firm selects the specific identification method and/or a combina-
tion of FIFO and weighted average valuation methods, a score of 0.5 is given. If a financial reporting standard or estimate is
not applicable to a firm, no score is given.
The accounting choice scores are aggregated for each firm and divided by the maximum aggressive accounting choice
score possible. For example, if a company applies three out of the five estimates or policy choices, the maximum score pos-
sible for aggressive choices is three. If two of the three choices are aggressive, the overall score is 0.67. Thus, our measure of
accounting quality (FRQUAL) ranges from 0 to 1.
Zmijewski and Hagerman (1981) develop a reporting strategy using various weightings of individual accounting scores.
They note, however, that this approach is ad hoc. Our approach is to develop a continuous dependent variable that aggregates
the individual accounting choice scores. Accounting policies and estimates are weighted equally in calculating FRQUAL. This
approach is consistent with studies applying annual report disclosure indices. An unweighted approach is used to reduce
subjectivity in determining the appropriate weights to apply (Ahmed and Courtis, 1999).

4
FRS 4 on accounting for inventories does not permit the use of the LIFO method for inventories.
5
The percentage change in the Consumers Price Index for the March, June, September and December 2001 quarters compared with the same quarter of the
previous year were 3.1%, 3.2%, 2.4% and 1.8%, respectively (Statistics New Zealand, 2001).
 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33 25

3.5. The financial reporting quality model

The following regression model is used to test the relation between audit committee quality and financial reporting
quality:

FRQUALit ¼ b0 þ b1 ACQUALit þ b2 MTBit þ b3 LEVit þ b4 BONUSit þ b5 LOSSit þ b6 EXTFINit þ b7 SIZEit ð1Þ

FRQUAL is a measure of financial reporting quality. It is the aggregate accounting choice score for firm i at time t, as de-
scribed in Section 3.4. ACQUAL is a measure of audit committee quality, i.e., ACBP, ACIND or ACEXP as described in Section
3.1. The remaining variables are included to control for factors that may also impact financial reporting quality. We describe
the control variables below.

3.5.1. Growth opportunities (MTB)

Skinner (1993) finds that firms with lower market-to-book ratios (i.e., firms with more assets-in-place) have bonus and
debt contracts that are more directly related to accounting earnings. As such, the lower growth firms have a greater incentive
to select aggressive (income-increasing) accounting choices relative to other firms. Based on the expectation that the level of
growth opportunities affects the nature of a firm’s contracts, and thus the incentives to behave opportunistically, a negative
relation is expected between a firm’s market-to-book ratio (MTB) and the selection of aggressive accounting choices.

3.5.2. Leverage (LEV)

Agency costs are higher for firms with more debt. When debt exists, managers may shift resources away from debtholders
by increasing dividend payments, by issuing more debt, by under-investing, and by substituting high-risk assets for low-risk
assets after debt is issued. Debt issuers use debt covenants to monitor and limit such behavior. Because debt covenants are
often written in accounting terms and violating them is costly, managers have incentives to make accounting choices that
reduce the likelihood of debt covenant breaches (Watts and Zimmerman, 1986). Therefore, managers of firms with higher
debt-to-equity ratios will select aggressive accounting choices that shift reported earnings from the future to the present.
This is generally supported by prior research (e.g., Skinner, 1993; DeFond and Jiambalvo, 1994; Sweeney, 1994; Beatty
and Weber, 2002). In summary, a positive association between the ratio of debt to total assets (LEV) and the selection of
aggressive accounting choices is expected.

3.5.3. Management bonuses (BONUS)

Healy (1985) provides evidence that managers use income-decreasing accruals when earnings are above or well below
bonus thresholds. This behavior is considered consistent with the hypothesis of shifting income to future accounting periods.
In contrast, where expected earnings are within bonus thresholds, managers use income-increasing accruals. Holthausen
et al. (1995) provide evidence consistent with Healy (1985) that managers manipulate earnings downwards when their bo-
nuses are at a maximum. However, they do not find evidence that managers manipulate earnings downwards when earnings
are below the threshold. In contrast, Guidry et al. (1999) examine the earnings management behavior of business-unit man-
agers of a large company and find evidence consistent with Healy (1985). Therefore, a positive association between income
falling within management bonus thresholds and aggressive accounting choices is expected.
Because information on bonus plans is not available in the annual reports of New Zealand firms, the pre-tax return on
assets is used to proxy for managers’ bonuses, consistent with approaches used in other studies (see, e.g., McNicholls and
Wilson, 1988; Bowen et al., 1995; Bradbury et al., 2003). The pre-tax return on assets ratio is calculated for each firm and
ranked from highest to lowest. Firms with high ratios in decile 10 are expected to exceed bonus thresholds and firms with
low ratios in decile 1 are considered to be below bonus thresholds. Firms in the highest and lowest deciles are coded 0 as
they are considered to have incentives to select conservative accounting choices in order to reduce current earnings. Con-
versely, firms in deciles 2–9 are assumed to be within bonus thresholds. Managers of these firms have incentives to select
relatively aggressive accounting choices to increase reported earnings in a current period. These firms are coded 1. This var-
iable is labeled BONUS.

3.5.4. Performance (LOSS)

Accounting research has reported a discontinuity in the distribution of earnings around certain thresholds. Burgstahler
and Dichev (1997) use US data and find discontinuities in the distribution of earnings around losses and earnings decreases.
These findings suggest that firms manage earnings to avoid these psychological thresholds. In a later study, DeGeorge et al.
(1999) provide evidence supporting an analysts’ forecast threshold. A survey of 401 US executives confirms this evidence.
Executives report that meeting or beating benchmarks is important as it reduces uncertainty and maintains credibility in
the market place, which helps to maintain or improve share prices (Graham et al., 2005).
For the purposes of this study, consecutive firm losses proxy for incentives for firms to manage earnings to improve re-
ported financial performance and avoid losses.6 That is, LOSS is an indicator variable equal to 1 if the firm had consecutive
losses and 0 otherwise. It is expected that firms with consecutive losses are more likely to make aggressive accounting choices.

6
Analyst-following in NZ is not extensive and covers only major listed companies.
26 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33

3.5.5. Raising external finance (EXTFIN)

Dechow and Skinner (2000) argue that managers have incentives to increase earnings to improve the terms on which
shares are sold to the public and thus provide benefits to themselves and the firm. Thus, a positive association between rais-
ing external finance (EXTFIN) and aggressive accounting policy choices and estimates is expected where EXTFIN is an indi-
cator variable, equal to 1 if the firm issued equity or debt securities during the period.

3.5.6. Firm size (SIZE)

Large firms are subject to greater analyst following (Bhushan, 1999), and greater scrutiny can put pressure on managers
to manipulate earnings in order to meet analysts’ forecasts. Skinner and Sloan (2002) show that firms that do not beat ana-
lysts’ predictions experience severe negative share price reactions. Given this pressure, it suggests a positive relation be-
tween firm size (SIZE) and aggressive accounting choices.

3.6. The audit fee model

Simunic (1980) models audit fees as a function of size, audit risk, and complexity of the audit client. In a meta-analysis,
Hay et al. (2006) show that these variables are consistently significant in a large number of studies reflecting different coun-
tries and different contexts. The association between audit committee characteristics and audit fees is tested using an audit
fee model similar to the models used by Abbott et al. (2003) and Carcello et al. (2002):

AFEEit ¼ b0 þ b1 ACQUALit þ b2 TAit þ b3 RECINVit þ b4 SEGit þ b5 FORGNit þ b6 PROFITit þ b7 LOSSit þ b8 BIG4it ð2Þ

where AFEE is the audit fee for firm i at time t, ACQUAL is audit committee quality as described in Section 3.1, TA is total
assets (a proxy for client size), RECINV is the sum of accounts receivable and inventory scaled by total assets (a proxy for
the client’s inherent risk), SEG is the number of business segments and FORGN is the number of geographic segments (both
proxies for client complexity), PROFIT is earnings before interest and tax scaled by total assets and LOSS is an indicator equal
to 1 if the client had three consecutive loss years (both proxies for profitability), and BIG4 is an indicator equal to 1 if the
client had a Big 4 auditor (a proxy for auditor quality).

3.7. Sample and data

The population of interest is all NZ companies listed on the NZX main trading board in the 2001 Datex Investment Guide
(Datex Services Ltd., 2001). As discussed previously, we use data from 2001 because we want a period in which formation of
an audit committee was unconstrained so we can focus on firms that voluntarily adopted high quality audit committees.
Thus, while we use the NZSC (2004) guidelines to identify the parameters of a high quality audit committee, we are inter-
ested in firms that adopted these parameters before they became recommendations. We expect the early movers will be the
firms that derive the most benefits as they have a greater demand for the monitoring and control that a high quality audit
committee might provide. Similar to other countries where audit committees are more regulated (e.g., the US, UK), once the
NZSC recommendations were released in 2004, firms may have adopted the recommendations for high quality audit
committees in order to conform with industry peers or to avoid sending a signal that might be construed as a sign of weak
corporate governance. Thus, focusing on early movers eliminates firms that adopted high quality audit committees as a
second-best option.
Table 2 describes the effect of the sample selection procedure. The initial sample is 109 firms. We omit seven firms that
delisted, 14 firms that have insufficient audit committee details, and a unit trust since its financial structure and corporate
governance structure differs from other firms in the sample. This leaves a final sample of 87 firms.
Financial and audit committee membership data are hand collected from the 2001 annual reports of the sample firms. A
template was used to score the accounting choices described in Section 3.3. A second rater scored a subset of 23 firms (26.6%
of the sample) independently. Any differences in scores between the primary scorer and second rater were discussed and
amended once the two raters reached an agreement on how to handle the item.
The qualifications of directors are not always provided in company annual reports. In these cases, external sources such
as company press releases, internet searches, as well as searches of business newspaper and magazine databases, were used
to obtain the data. The NZICA website was used to determine if individuals were members of the national professional

Table 2
The effect of sample selection procedures.

Number of firms
All NZ firms on NZX in 2001 109
Less unit trust 1
Less delisted 7
Less firms with audit committees but no details on composition 14
Final sample 87
 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33 27

Table 3
Descriptive statistics of financial reporting quality scores.

Accounting choicesa N Mean Std dev Median Conservative Neutral Aggressive No policy
score = 0 score = 0.5 score = 1
# (%) # (%) # (%)
Panel A: Aggregate and individual accounting choice scores
Aggregate score (FRQUAL) 87 0.38 0.28 0.33
Buildings useful life 65 0.19 0.36 0.00 49 (56.4) 7 (8.0) 9 (10.3) 22 (25.3)
Motor vehicles useful life 58 0.47 0.48 0.50 28 (32.2) 5 (5.7) 25 (28.8) 29 (33.3)
Goodwill useful life 54 0.43 0.50 0.00 31 (35.7) – 23 (28.4) 33 (37.9)
Tax effect accounting 87 0.26 0.44 0.00 64 (73.6) – 23 (26.4) 0 (0.0)
Assigning costs to inventory 64 0.60 0.46 1.00 22 (25.4) 7 (8.0) 35 (40.2) 23 (26.4)

Panel B: Distribution of aggregate accounting choice score (FRQUAL)

FRQUAL Number %
0.00–0.25 35 40.2
0.26–0.50 33 38.0
0.51–0.75 11 12.6
0.76–1.00 8 9.2

Total 87 100.0
a
Not all firms applied all accounting choices. In these cases, no score was given. The aggregate score for each firm (FRQUAL) is the sum of the individual
scores, scaled by the number of applicable accounting policies for that firm. See Table 1 for scoring system.

accounting body. However, this process excludes any accounting certification received by directors from overseas profes-
sional accounting bodies. Where information on audit committee members was incomplete, a letter was sent to the listed
company requesting the information.7

4. Results for financial reporting quality

4.1. Univariate analyses

Table 3 shows the descriptive statistics of the aggregate and individual scores for accounting choices. Recall that the
accounting choice score ranges from 0 to 1. Panel A shows the mean (median) aggregate accounting score, across the five
accounting choices, is 0.38 (0.33). Panel B shows the distribution of the aggregate score, FRQUAL. Around 78% of the sample
have a score lower of 0.5. This reflects that most firms make accounting choices that are conservative. Based on Panel A, the
most conservative accounting choices are made when estimating the useful life of buildings and selecting tax effect account-
ing. The most aggressive accounting choices are made with respect to inventory valuation. Estimates of the useful life of mo-
tor vehicles and goodwill amortization are more evenly spread between conservative and aggressive estimates.
Table 4 reports the descriptive statistics and univariate tests for the explanatory variables in the financial reporting qual-
ity model (Eq. (1)). Of the final sample of 87 firms, 29 firms (33%) meet the best practice criteria (ACBP). Forty-six firms (53%)
have audit committees with at least a majority of independent directors (ACIND). This percentage is much lower than in
Klein’s (2002b) study where 88.7% of the sample of 808 US firm-years had audit committees with a majority of independent
directors which shows the New Zealand environment is much less constrained than in the US, i.e., New Zealand firms in our
sample had much more latitude in forming audit committees as expected. Fifty-three firms (61% of the sample) have a char-
tered accountant as an audit committee member (ACEXP). The average market-to-book ratio is one-and-a-half times the
book value of total assets. Total liabilities average 29% of firm size. Twenty percent of the sample (17 firms) had two years
of consecutive losses. In 2001, 34% of the firms (30 firms) raised debt or equity finance from the public. The mean firm size is
$862.4 million.
Table 4 also reports univariate tests of the relation between the explanatory variables and financial reporting quality. For
univariate tests only, we transform the financial reporting quality variable (FRQUAL) into a binary variable equal to 1 if
FRQUAL is greater than the median and zero otherwise. We label this binary variable as CHOICE. We examine the null
hypothesis that for each explanatory variable there is no difference between the sample of firms that adopt aggressive
accounting choices (i.e., CHOICE = 1) and those that adopt conservative accounting choices (CHOICE = 0). The means and
medians of the explanatory variables indicate that nonparametric tests are appropriate. We use a Mann–Whitney U test
where the variable is continuous and a chi-square test where the variable is a dummy variable.
The univariate tests indicate that LEV, BONUS, and SIZE are significantly related to CHOICE at the 0.10 level. This supports
the view that firms with higher leverage, firms within bonus thresholds, and large firms select relatively aggressive choices,
which is consistent with expectations.

7
Additional information was requested from 89 firms. A total of 54 usable responses 60.7% were received.
28 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33

Table 4
Descriptive statistics and univariate tests of explanatory variables for the financial reporting quality model.

Mean Std dev Median Minimum Maximum Testa p-Valuea

Accounting choices CHOICE 0.56 0.50 1.00 0.00 1.00
Best practice audit committee ACBP 0.33 0.47 0.00 0.00 1.00 v2 0.44
Audit committee independence ACIND 0.53 0.50 1.00 0.00 1.00 v2 0.32
Audit committee expertise ACEXP 0.61 0.49 1.00 0.00 1.00 v2 0.20
Growth opportunities MTB 1.55 1.25 1.09 0.29 7.86 MWU 0.16
Leverage LEV 0.29 0.37 0.23 0.00 3.11 MWU 0.00
Bonus BONUS 0.59 0.50 1.00 0.00 1.00 v2 0.08
Consecutive losses LOSS 0.20 0.40 0.00 0.00 1.00 v2 0.20
External finance EXTFIN 0.34 0.48 0.00 0.00 1.00 v2 0.48
Firm size ($million) SIZE 862.4 2,241.3 182.2 2.6 17,422.8 MWU 0.08
a
These columns report one-tailed p-values from either a Mann–Whitney U test (MWU) and chi-square test (v2). These tests examine the null hypothesis
of no relation between the explanatory variables and financial reporting quality. For the purpose of these univariate tests, the financial reporting quality
variable (CHOICE) is coded 1 if it is above the median FRQUAL and 0 otherwise.

Table 5
Spearman correlation coefficients.

FRQUAL ACBP ACIND ACEXP MTB LEV BONUS LOSS EXTFIN

ACBP 0.06
ACIND 0.02 0.67
ACEXP 0.11 0.52 0.38
MTB 0.18 0.02 0.09 0.00
LEV 0.32 0.00 0.04 0.06 0.05
BONUS 0.12 0.05 0.10 0.09 0.07 0.01
LOSS 0.02 0.10 0.17 0.02 0.00 0.03 0.53
EXTFIN 0.04 0.10 0.10 0.33 0.11 0.18 0.08 0.07
SIZE 0.20 0.21 0.31 0.22 0.08 0.34 0.16 0.43 0.28

Bold denotes significance at the 0.05 level.

Table 6
OLS Regressions of financial reporting quality (FRQUAL) on audit committee quality and control variables.

Coefficient (p-value)
Model 1 Model 2 Model 3
Intercept 0.52 (0.16) 0.50 (0.18) 0.51 (0.17)
Best practice audit committee ACBP – 0.07 (0.14)
Audit committee independence ACIND – 0.04 (0.28)
Audit committee expertise ACEXP – 0.08 (0.11)
Log growth opportunities logMTB – 0.09 (0.05) 0.08 (0.05) 0.09 (0.05)
Log leverage logLEV + 0.05 (0.07) 0.05 (0.05) 0.04 (0.08)
Bonus BONUS + 0.04 (0.25) 0.05 (0.25) 0.06 (0.20)
Consecutive losses LOSS + 0.13 (0.11) 0.12 (0.12) 0.14 (0.09)
External finance EXTFIN + 0.07 (0.15) 0.07 (0.14) 0.05 (0.25)
Log firm size logSIZE + 0.05 (0.00) 0.05 (0.00) 0.05 (0.00)
F-statistic (p-value) 1.87 (0.08) 1.73 (0.11) 1.93 (0.08)
Adjusted R2 (%) 6.6 5.6 7.0
Range of VIF values 1.1–1.9 1.1–1.9 1.2–1.6
N 87 87 87

Spearman correlations are reported in Table 5. As expected, there is a high correlation between the best practice audit
committees (ACBP) and audit committees meeting both independence (ACIND) and expertise (ACEXP) membership criteria.
Audit committee expertise (ACEXP) is positively correlated with external financing (EXTFIN). This suggests that additional
monitoring is employed when firms raise debt. As expected, there is a negative correlation between bonuses (BONUS)
and consecutive losses (LOSS). SIZE is positively correlated with independent and expert audit committees (ACIND and ACE-
XP), leverage (LEV), and external financing (EXTFIN) and negatively correlated with consecutive losses (LOSS).

4.2. Multivariate analysis

In Table 6, we report OLS regressions for the financial reporting quality variable (FRQUAL) with each of the audit commit-
tee quality variables (ACBP, ACIND, ACEXP) and control variables. Variables for growth opportunities (MTB), leverage (LEV),
and firm size (SIZE) are log transformed to improve the distributional properties of the variables. Results across the three
regressions are consistent. The F-statistic indicates the models are weakly significant around the 0.10 level with adjusted
R2s ranging from 5.6% to 7.0% which is close to the explanatory power reported by Zmijewski and Hagerman (1981).
 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33 29

While all of the coefficients are all in the direction predicted, none of the audit quality coefficients are significant. Size,
growth opportunities, and leverage are significant at the 0.10 level or better with the expected signs. Bonus, consecutive
losses, and external finance are not significant at conventional levels. In summary, the results Table 6 provide no support
for the hypothesis that audit committee quality limits aggressive accounting choices.
Additional tests were undertaken controlling for industry fixed effects with no change in the results. We also repeated the
test with audit committee variables relating to activity (the number of meetings) and audit committee size. Again, the results
are unchanged.

4.3. Sensitivity analysis

4.3.1. Alternative earnings quality measures

The weak results in Table 6 may be due to inherent limitations of the accounting choices selected. One limitation is that
they can have a long-term rather than a short-term effect on earnings quality. For example, the useful life of property, plant
and equipment is required to be reassessed annually, but the relevant accounting standard (FRS 3) notes that it is unlikely
that changes in useful lives would be made each year.
To overcome this long horizon limitation, we also adopt a financial reporting quality measure that better reflects short-
term accounting choices. We develop a composite measure of six earnings quality measures based on Francis et al. (2004).
Three of the earnings quality measures (timeliness, conservatism, and value relevance) are market-based measures and three
are accounting-based measures (smoothness, persistence, and accrual quality). A definition of each of the six measures along
with a brief explanation of why the attribute is considered desirable for reporting earnings is provided in the Appendix.
The composite earnings quality measure is calculated by ranking firms from the highest to the lowest value for each earn-
ings quality measure with the exception of accruals quality where the ranking is in reverse order. The firms are then clas-
sified into deciles. Firms with the highest earnings quality are ranked in the top decile.8 The composite measure is calculated
by summing the ranks for each earnings quality measure and then taking the deciles of the overall ranking. The earnings quality
measures are calculated for firm-specific years from 1990–2001. At least five years of data are required to estimate the firm-
specific regressions.9
Regressions are run for each of the audit committee quality variables (ACPB, ACIND, ACEXP) with the composite earnings
quality measure as the dependent variable. The results (untabulated) indicate that the models are weakly significant. The
adjusted R2s are lower compared with the accounting choice models in Table 6. None of the audit committee variables
are statistically significant at the 0.10 level.

4.3.2. Simultaneity
A potential issue with the research design we employ is that audit committee membership and accounting policy choice
may be determined simultaneously. In statistical terms, this means that the independent variable for best practice audit
committees may be correlated with the error term of the financial reporting quality model. If this is the case, the coefficient
of the best practice audit committee variable may be over-or under-estimated. The Hausman test (Gujarati, 2003) is applied
to assess simultaneity. In the first regression, the best practice audit committee variable is regressed on the control variables
as shown in Eq. (3):
ACBPit ¼ b0 þ b1 MTBit þ b2 LEVit þ b3 BONUSit þ b4 EXTFINit þ b5 LOSSit þ b6 SIZEit þ eit ð3Þ
In the second regression, accounting choice is regressed on the residual from Eq. (3) and other variables as shown in Eq. (4):
FRQUALit ¼ b0 þ b1 ACBPit þ b2 MTBit þ b3 LEVit þ b4 BONUSit þ b5 EXTFINit þ b6 LOSSit þ b7 SIZEit þ ^eit þ v it ð4Þ
If there is no simultaneity, the coefficient of the error term ê should not be different significant from zero (Gujarati, 2003).
The results of the Hausman test (untabulated) show that the coefficient of the estimated residual is not statistically sig-
nificant, suggesting that simultaneity is not a problem.

5. Results for audit fees

In this section, we examine the relation between audit committee quality and audit fees. The results are reported in Table
7. Consistent with prior research, audit fees are positively associated with total assets, accounts receivable/inventory, the
number of business and geographic segments. However, the coefficients for the audit committee quality variables (ACBP,
ACIND, and ACEXP) are not significant. This suggests the characteristics associated with audit committee quality have no
impact on the level of audit fees.
Griffin et al., 2008 argue that the models employed in prior studies to examine the relation between governance strength
and audit fees do not take into account the how auditing affects governance and vice versa. They extend Simunic’s (1980)
audit fee model by regressing audit fees on governance and audit risk, and include interaction variables to capture possible

8
Given the limited sample size, this avoids the need to delete observations that are extreme outliers (Francis et al., 2004) as well as reducing the impact of
measurement error in the earnings quality measures (Bushman et al., 2004).
9
The sample includes firms that remain listed over the five year period (n = 74). Thus, the sample is biased towards surviving firms.
30 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33

Table 7
OLS regression of audit fees on audit committee quality and control variables.

Coefficient (p-value)
Model 1 Model 2 Model 3
Constant 1.35 (0.13) 1.27 (0.14) 1.24 (0.15)
Best practice audit committee ACBP + 0.17 (0.17)
Audit committee independence ACIND + 0.12 (0.24)
Audit committee expertise ACEXP + 0.06 (0.36)
Log total assets logTA + 0.57 (0.00) 0.57 (0.00) 0.57 (0.00)
Accounts receivable and inventory scaled by total assets logRECINV + 0.33 (0.00) 0.32 (0.00) 0.33 (0.00)
Number of business segments logSEG + 0.86 (0.06) 0.81 (0.07) 0.74 (0.10)
Number of geographic segments logFORGN + 0.38 (0.04) 0.37 (0.05) 0.40 (0.04)
Earnings before interest and tax scaled by total assets logPROFIT + 0.07 (0.26) 0.05 (0.33) 0.04 (0.34)
Consecutive losses LOSS + 0.51 (0.20) 0.46 (0.23) 0.54 (0.17)
Big 5 auditor BIG5 + 0.17 (0.23) 0.14 (0.27) 0.12 (0.27)
F-statistic (p-value) 25.44 (0.00) 29.06 (0.00) 28.68 (0.00)
Adjusted R2 84.1 83.9 83.7
N 87 87 87

joint governance-auditing effects. They report that audit fees increase with improved corporate governance as a result of
more resources being invested in auditing. They also report a negative governance-audit risk interaction supporting the
argument that improved corporate governance enhances financial reporting leading to a reduction in audit risk and a de-
crease in audit fees.
Consequently, following Griffin et al., 2008, we also test for a possible negative interaction between the corporate gover-
nance and audit risk variables:

AFEEit ¼ b0 þ b1 ACQUALit þ b2 TAit þ b3 RECINVit þ b4 ACQUALxRECINVit þ b5 SEGit þ b6 FORGNit þ b7 PROFITit

þ b8 LOSSit þ b9 BIG4it ð5Þ

Our results (untabulated) show the interaction variable is not significant for any of the audit committee variables. In each
case, the explanatory power of the audit fee model is lower than the models in Table 7, although TA, RECINV, SEG, and
FORGN remain significant.

6. Conclusion

The corporate collapses in the early 2000s prompted regulators to improve the quality and oversight of financial reporting
by improving the effectiveness of audit committees. For example, best practice recommendations issued by the NZSC in 2004
affirm that audit committees should be structured with all non-executive directors, a majority of them being independent,
and include a director with financial expertise. However, before these recommendations were released, some New Zealand
firms already had audit committees that satisfied these best practice guidelines. The purpose of this study is to examine the
financial reporting quality and audit fees for firms that voluntarily formed high quality audit committees.
Using a sample of 87 New Zealand firms, including 29 that had adopted a high quality audit committee, we find no evi-
dence that best practice audit committees improved financial reporting quality. We also find no evidence that best practice
audit committees were associated with lower audit fees. Our results are somewhat surprising as we expect the early movers
to be the firms that would gain the greatest benefits from a high quality audit committee. Our results suggest that the ben-
efits of high quality audit committees may be less than anticipated by regulators and policymakers. If so, imposing ‘best
practice’ membership requirements on all firms is unlikely to lead to a significant improvement in financial reporting while,
at the same time, imposing unnecessary compliance costs.
Our results are also in contrast to prior studies in the US and UK that have shown independent audit committee can re-
duce earnings management (Klein, 2002a; Jenkins, 2003) and accounting irregularities (Dechow et al., 1996; Peasnell et al.,
2001), and that audit committees with financial expertise can reduce fraud (Farber, 2005). We offer two possible explana-
tions for the conflicting results. First, it is possible that prior studies in the US and UK are detecting a general corporate gov-
ernance effect. Specifically, regulations and corporate codes in those countries are aimed at improving corporate governance
generally so audit committee quality may be a proxy for the firm’s overall corporate governance strength. If so, this would
suggest that audit committee quality has to be part of a broader corporate governance package in order for the firm to realize
detectable benefits. Second, it is possible that having audit committee quality highlighted in regulations (e.g., stock exchange
listing rules, the SOX Act) or corporate codes (e.g., the Cadbury Code, Blue Ribbon Committee report) may put pressure on
audit committees to improve their performance.
Like all studies, this study has its own limitations. The study focuses on audit committee membership in terms of inde-
pendence and expertise, but a number of other audit committee attributes such as the business backgrounds of the audit
committee members and the number of years they have served on the audit committee have not been tested. The study
 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33 31

has focused on monitoring financial reporting quality and the cost of the external audit, but audit committees have a number
of roles and responsibilities which have expanded over the years. There may be significant benefits from the formation of
best practice audit committees from these other roles.

Acknowledgements

We thank Fedinand Gul, David Lont, Shane Moriarity, Asheq Rahman for their comments and Josefino San Diego for re-
search assistance. Thanks also to Andrew Fergusson and discussants at the half yearly Journal of Contemporary Accounting
and Economics Australasian symposium.
We gratefully acknowledge financial support from the New Zealand Institute of Chartered Accountants and support from
Unitec New Zealand.

Appendix. Earnings quality attributes included in composite earnings quality measure.

Description Measure applied Indicator of earning quality

Accounting based
Accrual quality The ability of earnings A regression of current accruals High standard deviation of the error
to map closely into cash (scaled by average total assets) term indicates low earnings quality
flows on prior period, current period
and future cash flows from
operations (scaled by average
total assets) (Dechow and
Dichev, 2002, model)
Earnings persistence The ability of earnings to The slope coefficient of a Low coefficient for prior period
continue, i.e., sustainable or regression of current earnings earnings indicates low earnings
core earnings (scaled by average total assets) quality
on prior period earnings (scaled
by average total assets)
Smoothness The variation in earnings The ratio of the standard Low ratio indicates low earnings
changes deviation of net profit (after quality
taxation scaled by average
assets) to the standard deviation
of cash flow from operations
(after tax scaled by average
assets)
Capital market based
Value relevance The ability of earnings to The explanatory power of a A low R2 indicates low quality of
explain variation in returns regression of returns (the 15- earnings
month stock return ending three
months after balance date) on
earnings (before interest and tax
scaled by average total assets)
Timeliness The extent to which earnings The explanatory power of a A low R2 indicates low quality of
measure changes in the regression of earnings (before earnings
market value of equity interest and tax scaled by
average total assets) on returns
(the 15-month stock return
ending three months after
balance date)
Conservatism The ability of earnings to In a regression of earnings Low ratio indicates low earnings
explain economic losses (before interest and tax scaled quality
(negative returns) as by average total assets) on
compared with economic returns (15-month return 3
gains (positives returns) months after balance date), the
slope coefficient of negative
returns (bad news) to the slope
coefficient on positive returns
(good news)

Sources: Schipper and Vincent, 2003 and Francis et al., 2004.

32 E.A. Rainsbury et al. / Journal of Contemporary Accounting & Economics 5 (2009) 20–33

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