lee et al - 2006 - auditor conservatism and audit quality - evidence from ipo earnings forecasts

Taylor3 1 University of Sydney, Australia 2 University of Melbourne, Australia 3 University of New South Wales and Capital Markets CRC Ltd, Australia We investigate the relation between

Auditor Conservatism and Audit

Quality: Evidence from IPO

Earnings Forecasts

Philip J Lee,1Sarah J Taylor2and Stephen L Taylor3

1 University of Sydney, Australia

2 University of Melbourne, Australia

3 University of New South Wales and Capital Markets CRC Ltd, Australia

We investigate the relation between a proxy for differential audit quality and both the (ex post) accuracy and conservatism

of audited earnings forecasts provided in Australian initial public offering (IPO) prospectuses For the period we examine, most Australian IPO prospectuses include an earnings forecast (i.e., disclosure is not ‘voluntary’), and the auditor must be satisfied prior to signing off on the prospectus After controlling for other factors associated with forecast error, there is some evidence that forecasts audited by Big 6 auditors prove more accurate than those audited by a non-Big 6 auditor, although this result is not robust across alternative measures of forecast accuracy In contrast, our finding of significantly less optimistic bias for forecasts associated with Big 6 auditors is robust to alternative measures of forecast bias We interpret these results as being consistent with the argument that the economic demand for differential audit quality reflects the same factors that underlie the demand for conservative financial reporting.

Key words: audit quality, initial public offering, management

earnings forecasts, conservatism

SUMMARY

Audit quality is not easily observed, and as a result

researchers have increasingly relied on measurable

attributes of audited financial statements This is

premised on the assumption that the quality of

financial statement data is a joint function of

management representations and the audit process

However, we observe that many prior studies rely

on the assumption that higher quality financial

statement data (and by inference, higher quality auditing) will be reflected in greater accuracy One such example is the attempt to link proxies for differential audit quality (e.g., Big 6 auditors) with the absolute value of unexpected accruals On the other hand, extant research also suggests that higher quality auditors may be associated with more conservative financial reporting We draw attention to the potential conflict between the accuracy and conservatism of audited financial data, as conservatism implies a directional bias Such a bias implies that attempts to link audit quality with accuracy may be confounded

Correspondence to: Stephen L Taylor, School of Accounting,

University of New South Wales, NSW 2052, Australia Email:

S.Taylor@unsw.edu.au

ISSN 1090-6738

© 2006 The Author(s)

We test our theory on a relatively unique setting,

namely the quasi-compulsory provision of audited

earnings forecasts by Australian initial public

offerings (IPOs) By comparing the forecast result

with the actual result subsequently reported, we

are able to directly test the competing theories that

high quality auditing (in this case, Big 6 auditors)

are associated with either more accurate or more

conservative earnings forecasts We control for

several other factors expected to be associated with

forecast accuracy and/or bias Our evidence also

extends prior research which has relied on

measuring attributes of earnings forecasts made by

IPOs in environments where the provision of a

forecast is voluntary, rather than mandatory By

examining mandatory forecasts, we effectively

control for factors that may be associated with

forecast accuracy and/or bias but which are also

determinants of the decision to voluntarily provide

such a forecast in the first place

Our results support the view that high quality

auditing is associated with more conservative

reporting Although we find some evidence that

forecasts audited by Big 6 auditors are more

accurate than forecasts audited by non-Big 6

auditors, this result is not robust to alternative

ways of measuring the forecast error On the other

hand, evidence that forecasts audited by Big 6

auditors are more conservative proves to be highly

robust We interpret our evidence as providing

support for the argument that the derived demand

for conservative financial reporting is also reflected

in the demand for high quality auditing, and so

audit quality is associated with conservative

reporting

1 INTRODUCTION

It is widely accepted that auditors add value to

financial statements by reducing the likelihood of

deliberate misreporting (Watts & Zimmerman,

1986) However, although this suggests that higher

quality auditing should be associated with more

accurate (i.e., less biased) financial reporting, we

also note that at least one form of bias in financial

reporting, namely conservatism, has also been

argued to be associated with the quality of financial

reporting (Watts, 2003) Because conservative

accounting can facilitate the monitoring role of

financial reporting data (Ball & Shivakumar, 2005),

it is not surprising that the application of

conservatism within financial reporting has been

argued to have evolved in conjunction with the demand for independent verification by external auditors (Watts, 2003) Indeed, recent criticisms

of the accounting profession (e.g., Levitt, 1998), and especially the controversy over auditor independence, focus almost exclusively on alleged

overstatements of periodic results (Ruddock et al.,

2006) This further highlights the extent to which auditors are presumed to ensure a certain degree of conservatism in audited financial reports

We investigate the extent to which a widely used proxy for differential audit quality (i.e., Big 6 versus non-Big 6) is associated with more precise and/or less optimistically biased financial data.1 Our analysis is motivated by recognition that accuracy (i.e., precision) and conservatism (i.e., less optimistic or ‘downward’ bias) are not the same, and in fact are competing, rather than complementary attributes of financial reporting data Put simply, if higher quality auditing is associated with relatively more accurate financial reporting, we would not expect to observe an association between a proxy for audit quality and

a consistent conservative bias Following the arguments in Watts (2003), we expect that conservatism associated with the use of Big 6 auditors is particularly valuable (and hence, most likely to occur) where significant informational asymmetries are present, and where audited financial information is likely to be relied on We therefore examine the association between a proxy for audit quality and both the accuracy and bias (conservatism) in financial reporting data in such a setting

The setting we examine is the provision of earnings forecasts in the prospectuses of Australian initial public offerings (IPOs) Earnings forecasts provided in Australian IPO prospectuses provide

a unique setting in which to examine the effect

of differential audit quality Securities regulations and the threat of litigation result in almost

no disclosures of forward looking financial information by United States IPOs In contrast, relevant Australian securities regulations, operative since 1991, are widely viewed as making the provision of earnings forecasts ‘de facto’ mandatory for the majority of Australian industrial IPOs (i.e., excluding mining IPOs), despite the relatively imprecise wording of the legislation.2 This influence is exacerbated by the relatively severe penalties imposed by the Corporations Law for the omission of ‘material information’ known

to the issuer For the sample of IPOs we initially

identify, almost 85% provide an explicit forecast of

expected earnings This reduces the extent to which

any endogenous disclosure decision potentially

affects our tests relative to those that utilize less

frequent, voluntary disclosures.3

Auditors also have less flexibility in reporting

on prospectus data than for periodic audits Even

when the auditor does not provide an explicit

attestation to an earnings forecast, Australian

professional standards prohibit (and regulatory

guidelines reinforce) the auditor from signing the

prospectus if there are reservations about any

aspect of this document They cannot provide a

‘qualified’ response.4 We expect that the inability

to issue a qualified audit opinion (and thereby

signal uncertainty) will exacerbate the role of

conservatism as an attribute of audit quality

Our expectation is that Big 6 auditors are at

least as concerned with avoiding reputation

costs that arise when forecasts (or, more generally,

assumptions implicit in historic audited results)

prove to be optimistic as they are with ensuring the

precision of the information to which they attest

Likewise, we expect that the demand for audit

quality incorporates at least some expectation of

increased conservatism Hence, attempts to identify

a relation between use of a Big 6 auditor and

forecast accuracy (i.e., the unsigned forecast error)

may be inconsistent with the underlying demand

for audit quality, and may be confounded by the

expected greater conservatism of Big 6 auditors

Conversely, we would unambiguously expect to

find that forecasts audited by Big 6 auditors prove

to be more conservative, ex post, than those audited

by non-Big 6 auditors

Our results are broadly consistent with these

predictions Univariate tests show significant

differences when comparing measures of both

forecast accuracy and bias for Big 6 and non-Big

6 auditees After controlling for other factors

expected to be associated with forecast accuracy we

find some evidence that forecasts attested to by Big

6 auditors are more accurate However, this result

is not robust to alternative measures of forecast

accuracy In contrast, we find consistent evidence of

greater conservatism (i.e., a lower optimistic bias)

among forecasts issued by IPO firms with Big 6

auditors, irrespective of the forecast error metric

used

Our paper contributes in a number of ways First,

we provide additional evidence of how auditors,

and differential audit quality, may add value

specifically in the IPO process Although it has been

argued that the choice of a Big 6 auditor can serve

as a signalling mechanism for IPO firms (Datar

et al., 1991; Titman & Trueman, 1986), the process

by which auditors add value in such a setting has been subject to relatively little empirical analysis.5 Although a few studies examine earnings forecasts voluntarily provided by Canadian IPOs (Davidson

& Neu, 1993; McConomy, 1998; Clarkson, 2000),

we argue that the conflicting results in these studies reflect a failure to consider the incentives which high quality auditors face in attesting to accounting projections The results of these studies are inconsistent and sensitive to the exact model

of forecast error used (Clarkson, 2000) More importantly, our sample largely avoids the potential problem of endogenous voluntary disclosure faced by these studies

Second, we provide additional evidence consistent with conservatism being one element

of auditor behaviour that underlies product differentiation in auditing Although a limited number of studies examine the relation between proxies for differential audit quality (i.e., Big 6) and the output from the accrual accounting process, these studies are limited to observing unusual (i.e., unexpected) accruals, or rely on proxies for identifying news dependent conservatism in accounting.6 In contrast, our use of audited earnings forecasts allows us to directly measure the

extent of ex post accuracy and conservatism, and

consider the extent to which these are competing objectives We also examine the association between audit quality and attributes of audited information in an environment where expected litigation costs are likely much lower than in the United States Although expected litigation costs may be an important factor in creating a demand

for differential audit quality (Basu et al., 2001), we

also expect that the value of reputation effects, and the underlying economic demand for conservatism will result in evidence of an association between audit quality and conservatism in a relatively low litigation environment

The remainder of the paper proceeds as follows Section 2 reviews prior evidence on the relation between differential audit quality and conservative financial reporting, and generates testable hypotheses Section 3 describes our data sources,

as well as providing evidence on the accuracy and bias of earnings forecasts provided in IPO prospectuses Section 4 reports our primary results, while Section 5 summarizes additional sensitivity analysis Section 6 concludes

2 BACKGROUND AND HYPOTHESES

2.1 Evidence of a link between audit quality

and reporting conservatism

As we have already noted, the underlying

contracting and informational demand for financial

reporting is also consistent with a demand for

conservatism, at least in so far as that conservatism

is a reflection of how the financial reporting

process reacts to new (or revised) information

This is what Basu (1997) terms ‘news based’

conservatism, and what Ball & Shivakumar (2005)

describe as ‘conditional’ conservatism At the same

time, it is logical to expect that the external

verification process (i.e., external auditors) will pay

heed to this demand for conservative reporting

Although the auditor does not bear legal

responsibility for compiling the accounts, it is

beyond dispute that they are expected to influence

the outcome Hence, it is expected that at least one

dimension of what is perceived as audit quality will

be the extent to which an ‘appropriate’ level of

conservatism is enforced by external auditors

Evidence consistent with the conjecture that audit

quality is associated with increased conservatism

can be found in a number of forms

First, there is evidence that the accrual

component of earnings, or at least the unexpected

component thereof, is inversely related to the

common auditor size-based proxy for audit quality

Several studies focus on the link between audit

quality (proxied by Big 6) and the accrual

component of earnings.7 Francis et al (1999)

demonstrate that the decision to use a Big 6 auditor

is positively related to firms’ endogenous

propensity to generate accruals, as proxied by the

length of their operating cycle (current accruals)

and their capital intensity (non-current accruals)

Among studies that examine the link between Big 6

auditor choice and accruals, the most consistent

result is that Big 6 auditors are more conservative

than their non-Big 6 counterparts Becker et al.

(1998) show that firms using Big 6 auditors typically

have lower unexpected accruals than other firms.8

DeFond & Subramanyam (1998) report that firms

switching from a Big 6 to a non-Big 6 auditor appear

to implement more liberal accounting, as evidenced

by higher unexpected accruals However, the

method used for estimating unexpected accruals

has been shown to have relatively low power in

identifying the unexpected component (Dechow

et al., 1995; McNicholls, 2001) As neither paper

identifies any specific incentive for managers to exercise their discretion, interpretation of the results is problematic

Second, evidence of auditor conservatism is evident in auditor reporting decisions Francis & Krishnan (1999) examine the relation between audit firms’ propensity to issue modified audit reports and the extent of accruals They model the decision

to issue a modified report, and find that the probability of a modified report increases with the (absolute) level of accruals However, the result is strongest for firms with large positive accruals When firms are partitioned into those with Big 6 auditors and others, the relation between accruals and the propensity to issue modified audit reports

is confined to Big 6 auditors This is consistent with Big 6 auditors being more conservative than non-Big 6 auditors

Third, there are studies that examine the extent

to which earnings incorporate economic losses on a

more timely basis than economic gains Basu et al.

(2001) show that the asymmetric timeliness of bad news in earnings, as reflected in unexpected stock returns, is significantly greater for Big 6 auditees than others.9This result largely reflects the effect of more conservative operating accruals, rather than extraordinary items or discontinued operations

Basu et al also show that negative earnings changes

are less persistent for Big 6 auditees than other firms, which is consistent with greater conservatism by Big 6 audit firms However, tests such as these rely on the identification of news based conservatism from either contemporaneous share price movements or from the time series behaviour of earnings We adopt a broader, but nevertheless related perspective of conservatism, and expect that forward looking financial information attested by high quality auditors will

prove ex post to be relatively more conservative than

otherwise This is consistent with the view that conservative forecasts will be less likely to anticipate gains than losses, and so by deliberate understatement of the forecast and/or delayed recognition of gains (or even expected gains) until the first post-forecast result, the forecast result may

prove to be ex post conservative Whether this

results in reduced accuracy is an empirical question that we also address

2.2 IPO earnings forecasts and audit quality

Apart from the various methods discussed above

of identifying conservatism as one dimension of

audit quality, there are also a small number of

studies that examine properties of Canadian IPO

earnings forecasts and their relation to either the

type of audit requirement and/or the identity of

the auditor These studies reflect the frequent

voluntary provision of earnings forecasts at the

time of an IPO McConomy (1998) argues that

auditing is expected to reduce the extent of any

positive bias which (otherwise unaudited)

information is likely to display McConomy

compares the ex post accuracy and bias of earnings

forecasts prior to a 1989 requirement that the

forecasts be audited, rather than reviewed, and

finds a significant reduction in optimistic bias, but

relatively little improvement in accuracy Our

interpretation of these results is that auditors adopt

a more conservative approach as their degree of

responsibility increases, although it is also possible

that firms most likely to provide optimistic

forecasts elected not to do so after the introduction

of the audit requirements

Using a sample of Canadian IPOs from 1983–87,

Davidson & Neu (1993) show that earnings

forecasts reviewed by Big 6 auditors are

significantly less accurate than those reviewed by

non-Big 6 auditors They explain this result as a

product of less post-listing earnings management

by Big 6 auditees In effect, Davidson & Neu

assume that differential audit quality has no direct

effect on the quality of earnings forecasts, but at the

same time does act to constrain opportunistic

earnings management in the period following the

IPO Exactly why auditors would not care about

earnings forecasts, yet actively intervene to

constrain accounting policies is not clear, except

that the review (as distinct from audit) requirement

that applied to Canadian IPO earnings forecasts

may effectively reduce the significance of auditor

reputation

Another explanation for the result reported by

Davidson & Neu (1993) is that the relation between

differential audit quality and forecast properties

may be sensitive to the choice of variables used

to control for firm-specific and period-specific

uncertainty Clarkson (2000) examines forecast

accuracy and bias in both the review (1984–87) and

audit (1992–95) regimes, and shows that Davidson

& Neu’s primary result is sensitive to the choice

of variables used to control for business risk, which

in turn is expected to affect forecast accuracy

When a similar test is performed on the audit

regime sample, earnings forecasts audited by Big

6 auditors are significantly more accurate than

others For a measure of forecast bias, Clarkson finds no significant difference between those audited by Big 6 and non-Big 6 auditors, in either the audit or review regimes.10

However, while the results reported by Clarkson (2000) suggest that forecasts audited by Big 6 auditors are significantly more accurate but not significantly less biased, we note that the decision

by Canadian IPO firms to provide an earnings forecast is voluntary Canadian IPO firms that hire non-Big 6 auditors are typically riskier (Clarkson & Simunic, 1994), and auditors may be relatively less willing to face possible adverse effects of attesting

to forecasts by risky firms Hence, the endogenous forecast decision potentially biases Clarkson’s tests towards finding that forecasts audited by Big 6 auditors are significantly more accurate A better specified test is possible in an environment where the earnings forecasts are a ‘routine’ part of the prospectus, as they are for the Australian IPOs we examine.11

2.3 Hypotheses

Based on the evidence outlined above, we adopt the view that differential audit quality acts to constrain, or at least delay, relatively aggressive reporting practices Hence, the primary evidence of audit quality effects is most likely to occur as greater conservatism, rather than improved accuracy If high quality auditing results in the application of relatively conservative constraints, then users have less concern at possible

‘overstatements’ than otherwise In the context of IPOs providing earnings forecasts at the time of going public, we expect that conservatism will be

realized via forecasts which prove, ex post, to be more conservative Even if ex post evidence of

conservative forecasts reflects some degree of upwards earnings management in the first post-listing result, this still reflects the deferral of

‘good news’ and/or more aggressive reporting to a later point than explicitly incorporating it in the forecast result Moreover, it is hard to imagine that

an auditor who attests to conservative forecasts would simply allow aggressive accounting in the subsequent result High quality auditors also will likely face higher costs where they are found to have endorsed over-optimistic forecasts, as compared to ‘excessive’ conservatism

On the other hand, systematically conservative estimates of future results would be expected to reduce the overall level of accuracy that would

arise from otherwise unbiased estimates, with the

result that higher quality auditors may not be

associated with forecasts which prove, ex post, to be

more accurate Ultimately, the extent to which audit

quality is associated with either conservatism or

accuracy is an empirical question Hence, we test

the following two hypotheses, both of which are

stated in the null form:

H1: There is no association between audit quality

and forecast accuracy

H2: There is no association between audit quality

and forecast bias

3 DATA

3.1 Sample

Our sample begins with all Australian industrial

IPOs between 1991 and 1998 Our data begins at

1991 to reflect the effect of changes to the

Corporations Law Mining IPOs are excluded, as

they typically do not forecast earnings, primarily

because this practice is actively discouraged for

exploration firms Trusts and pooled development

funds are also excluded, due to the differences in

operating structure and taxation treatment of

dividends and capital distributions The resulting

sample of IPOs comprises 220 firms, of which 184

provide earnings forecasts with a horizon of at least

60 days However, five of these firms were

eliminated because the company was delisted prior

to the end of the forecast period and/or the

forecast could not be matched with actual results

Table 1 provides a summary of the temporal

distribution and industry membership of the

sample firms Panel A shows that there is some

temporal clustering, consistent with the existence

of ‘hot’ and ‘cold’ issue markets Panel B indicates

that the sample is relatively evenly distributed

across the five broad industry groupings, with the

exception of Financial services, which has a lower

representation

In order to test our hypotheses, a proxy for

differential audit quality is required Consistent

with theory (DeAngelo, 1981) and an

over-whelming amount of empirical evidence (Hay et al.,

2006), we use the conventional Big 6/non-Big 6

distinction Our focus on the most common

method of identifying high quality auditors is also

motivated by our desire to highlight the underlying

tension between the effects of audit quality (as

conventionally measured) on forecast accuracy as

distinct from the effect of forecast bias (i.e., conservatism effects), rather than complicating the analysis with more equivocal proxies for differential audit quality Other possible indicators

of high quality auditors such as client industry specialization have mixed support For example,

although Craswell et al (1995) report evidence that

industry specialist auditors earn significant audit fee premiums, more recent evidence suggests that this premium was eroded as the audit market was consolidated from a Big 8 through to a Big 6 and, finally, a Big 4 (Ferguson & Stokes, 2002) This is consistent with a reduced number of large international audit firms making it more difficult for any one of those firms to be seen as an industry specialist, simply because the ‘random’ market share in each client industry increases as the number of competing audit firms declines

Table 1: Summary of temporal distribution and industry group membership details of 179 initial public offerings for the period January 1991–June 1998

Panel A: Temporal distribution of industrial ipos disclosing an earnings forecast

Year Number of firms Per cent

Panel B: Industry group distribution

Group Number of firms Per cent

Construction &

Development

Retail & Consumer/

Firms are classified as belonging to one of five industry groups which are formed based on Australian Stock Exchange Industry Classifications These groups are: Services, Construction Development, Retail Consumer/Household Goods, Financial, and Industrials Mining firms are excluded from the sample

3.2 Forecast errors

We hand collect data, and so carefully match the

forecast income number with the actual result In

many cases, forecasts are provided for several

income definitions When this occurs we match

forecast operating profit before tax (OPBT) with

actual We prefer this measure relative to after-tax

earnings because discussion in several prospectuses

suggests that firms often forecast tax using the

nominal corporate tax rate rather than the expected

rate applicable to the calculation of income tax

expense.12 Where firms do not forecast OPBT, an

alternative definition is used, either operating profit

after tax but before abnormal and extraordinary

items, operating profit after tax, or earnings before

interest and tax.13In all cases, forecast error is the

difference between forecast and actual, so that a

positive forecast error indicates optimism

Descriptive data for forecast accuracy (i.e.,

absolute error) and forecast bias (i.e., signed error)

are presented in Table 2 Earnings forecast errors

are scaled two ways First, we utilize issue size as a deflator This gives a feel for the possible ‘economic significance’ of these forecast errors, relative to the funds raised through the IPO However, earnings are for the firm as a whole, but the use of issue size

as a deflator reflects only the interest of the ‘new’ shareholders Hence, we also measure earnings forecast errors on a per share basis, where the deflator is the issue price per share Both of the forecast error measures we report provide a more intuitively ‘economic’ measure than simple error percentages with respect to actual or forecast earnings, and most closely corresponds with the measures of forecast error (or ‘earnings surprise’) used in other studies.14

From Panel A of Table 2, the absolute forecast error expressed relative to share price at the time

of the offering has a mean (median) error of 4.93% (1.48%) Turning to the extent of possible bias, the data are consistent with forecast errors being, on average, optimistic However, the median forecast error is negative which

Table 2: Descriptive statistics of forecast accuracy (Panel A) and bias (Panel B) for 179 IPO firms

Forecast accuracy is measured as the absolute value of (Forecast earnings less Actual earnings), while bias is measured as (Forecast earnings less Actual earnings) Reported forecast measures (accuracy and bias) are scaled

by two alternate deflators (i) issue size and (ii) on a per share basis with the deflation by the issue price per share This results in two measures of forecast accuracy: error as a percentage of issue size and per share error deflated

by issue price All figures are expressed as percentages

Mean Std Dev Min Median Max.

Abs (F-A) per share/Issue price per share 4.93 8.37 0 1.48 61.48

(F-A) per share/Issue price per share 2.00 9.51 -34.22 -0.14 61.48

Mean Std Dev Min Median Max.

Abs (F-A) per share/Issue price per share 7.76 12.20 0 2.29 61.48

(F-A) per share/Issue price per share 5.34 13.46 -15.41 0.12 61.48

Mean Std Dev Min Median Max.

Abs (F-A) per share/Issue price per share 3.71*** 5.65 0.02 1.08* 34.22

(F-A) per share/Issue price per share 0.55*** 6.74 -34.22 -0.22 23.09

*/**/*** = statistically significantly different from non-Big 6 auditees at 10%, 5%, 1% levels

indicatesthat there are actually more forecasts

ex post pessimistic than optimistic (100/179).

Expressed on a per share basis, the mean (median)

signed forecast error measured as a percentage

of the issue price is 2.00% (-0.14%).15 Panel B of

Table 2 contains descriptive statistics for accuracy

and bias of non-Big 6 auditees while data for Big 6

auditees is contained in Panel C Both measures of

absolute forecast error (i.e., forecast accuracy) have

means and medians that are significantly lower for

Big 6 auditees However, for signed forecast errors

(i.e., forecast bias), only the mean is significantly

lower for Big 6 auditees This is consistent with

the distribution of forecast errors for non-Big 6

auditees being more skewed, with a relatively

larger proportion of forecasts that prove, ex post, to

have large optimistic errors However, given the

numerous systematic differences between Big 6

and non-Big 6 auditees documented in Table 3,

which may also be associated with the sign and size

of forecast errors, we caution against relying on

these univariate comparisons

3.3 Control variables

In order to identify the effect of differential audit

quality on earnings forecast accuracy and bias,

we regress measures of forecast error on our

proxy for audit quality (i.e., a Big 6 dummy

variable), a measure of underwriter quality and

three composite control variables Because we are

interested in the incremental effect of differential

audit quality rather than the determinants of

forecast error per se, we use principal component

analysis (Harman, 1976) to construct three

composite control variables (‘factors’), which

are intended to capture firm specific risk

(FIRMRISK), forecast characteristics (FORECAST)

and managerial incentives (INCENTIVES),

respectively.16

The objective is simply to establish a limited

number of composite control variables where

each composite variable comprises a number of

measures that intuitively capture similar attributes

We do not use orthogonalization procedures to

specifically minimize factor correlation.17 Rather,

we pre-select the components of each factor, and

use principal component analysis to create the three

factors purely to simplify the presentation of our

analysis and to reduce the focus on individual

determinants of forecast error and bias Of course,

where the components of a factor are highly

correlated, there are some efficiency gains from simply maximizing the extent of the explained dispersion across this set of variables before attempting to explain the variation in forecast error

or bias.18Principal component analysis allows us to isolate linear combinations of the potential control variables that are likely to capture similar aspects

of the firm, its forecasting environment or the incentives to make more accurate and/or less biased forecasts Hence, we construct an artificial variable (i.e, factor) that is an optimally weighted linear combination of the original variables Each factor is the normalized linear combination of the assigned set of control variables with maximum variance Importantly, all of our results with respect

to the relation between audit quality and forecast accuracy or bias are robust to simply estimating a model with all of the individual control variables rather than the three factors as independent variables

Our selection of possible control variables (and the three resulting factors) is guided by prior evidence on the determinants of IPO earnings forecast accuracy and/or bias (e.g., Clarkson, 2000), as well as prior studies showing a relation between proxies for firm-specific risk and complexity that are ‘priced’ by auditors (Craswell

et al., 1995) Due to uncertainty about the future

and the inherent complexity of the firm’s operations, managers typically forecast earnings with some error Possible proxies for firm specific risk and complexity include the age of the firm, firm size, leverage, the number of subsidiaries of the IPO firm, whether or not the firm has foreign operations, proportion of issue price not backed by net tangible assets (i.e., a measure of ‘growth options’ for the firm),19whether or not the firm had

a loss in the previous three years and the number

of risk factors highlighted in the IPO prospectus

We include each of these measures in our first estimated composite proxy, which we label FIRMRISK.20Many of these variables are also used

to control for aspects of audit risk (i.e., number of subsidiaries) in audit pricing models, which also demonstrate evidence of differential audit quality

(Craswell et al., 1995).

In addition to the firm specific characteristics included in our composite FIRMRISK measure described above, forecast specific characteristics may also be associated with the size and/or sign of forecast errors The length of time between the date

of making the forecast and the end of the period to which it relates will affect the degree of confidence

with which predictions can be made about the

future Accordingly, the forecast horizon, measured

as the number of months between the prospectus

date and the end of the forecast period, is included

in our second composite proxy We also control for

the level of detail with which the forecast is made

A more detailed forecast likely reflects greater

confidence in the accuracy of the forecast Forecast

detail is captured using a self constructed index,

which awards a score from 1 to 9 based on how

many of the following are disclosed in the forecast:

earnings, revenues, expenses, capital expenditures,

financing details, cash flows, dividends,

assumptions used in forecasting and sensitivity

analysis.21 Finally, a dummy variable is used to

indicate whether the firm provided forecasts for

more than one financial year Firms providing

forecasts for multiple years are expected to be more

confident about future outcomes, and as such are

likely to have lower forecast errors These three

measures are combined in our second composite

proxy, which we label FORECAST

It is also possible that IPO earnings forecasts

reflect some degree of moral hazard on the part of

those providing them Lack of publicly available

information may provide managers with

opportunities to exploit investors, since the costs

of relying on an inaccurate earnings forecast are

generally borne by new investors In contrast, if

managers intend to return to the capital market

they will have incentives to provide more accurate

forecasts to maintain investor confidence

Accordingly, four variables are used to proxy

for competing managerial incentives: the level of

retained ownership, the proportion of

newly-raised funds paid to vendor shareholders, and

dummy variables for whether the firm conducted

a seasoned equity offering (SEO) in the two

years following the IPO and whether or not the

offer is a packaged or unit offer The distinction

between IPOs where the offering is a package of

current (i.e, shares) and deferred (e.g., options)

equity purchase reflects evidence that among

Australian IPOs, unit IPOs represent a signalling

strategy intended to address concerns about the

quality of the firm’s business model that would

otherwise result in increased underpricing (Lee

et al., 2003a) We combine these four measures into

our third composite proxy, which we label

INCENTIVES

Apart from our focus on the effect of differential

audit quality, another external party expected to

serve a monitoring function in relation to the

prospectus is the underwriter Although not directly responsible for the forecast provided in the prospectus, underwriters typically have access to superior information about the strategy and future prospects of the firm which is relevant to valuation

of the IPO Similar to Big 6 auditors, high quality underwriters likely have their reputation at stake in the event that a forecast is found to be extremely inaccurate/biased This leads to an expectation that high quality underwriters will encourage IPO firms

to provide more accurate earnings forecasts A dummy variable is used to indicate if the IPO firm used a high quality underwriter or not.22

Finally, we include industry dummies in our regressions to reflect possible industry-specific variation in forecast attributes This is especially relevant to IPOs, where it is also possible that IPOs cluster by type according to market conditions We use the broad industry groupings summarized in Table 1

Our model used to identify the effect of audit quality on forecast accuracy and bias is therefore as follows:

b FORECAST b INCENTIV

+

where:

IA_BIG 6 equals 1 if the auditor is a BIG 6 auditor, otherwise 0;

FIRMRISK is a composite factor capturing firm-specific attributes that are likely to be associated with the riskiness of the forecasting task; FORECAST is a composite factor capturing attributes of the forecast which are likely to be associated with increased variation and/or bias; INCENTIVES is a composite factor capturing variables which are likely to be associated with managers’ incentives to make accurate and/or biased forecasts;

INDUSTRY is a numeric variable distinguishing sample firms on industry groupings as outlined in Table 1;

and e is an error term

Descriptive data on the variables used to construct our composite proxies, the underwriter quality proxy and the auditor quality variable is reported

in Table 3 Panel A reports mean, standard deviation, minimum, median and maximum values for the continuous variables for the full sample and the Big 6/non-Big 6 sub-samples Data relating to

Table