peasnell et al - 2005 - board monitoring and earnings management - do outside directors influence abnorm

Board Monitoring and Earnings
Management: Do Outside Directors
Influence Abnormal Accruals?
K.V. PEASNELL, P.F. POPE AND S. YOUNG*
Abstract: This paper examines whether the incidence of earnings manage-
ment by UK firms depends on board monitoring. We focus on two aspects of
board monitoring: the role of outside board members and the audit commit-
tee. Results indicate that the likelihood of managers making income-increasing
abnormal accruals to avoid reporting losses and earnings reductions is
negatively related to the proportion of outsiders on the board. We also find
that the chance of abnormal accruals being large enough to turn a loss into a
profit or to ensure that profit does not decline is significantly lower for firms
with a high proportion of outside board members. In contrast, we find little
evidence that outside directors influence income-decreasing abnormal
accruals when pre-managed earnings are high. We find no evidence that the
presence of an audit committee directly affects the extent of income-increasing
manipulations to meet or exceed these thresholds. Neither do audit commit-
tees appear to have a direct effect on the degree of downward manipulation,
when pre-managed earnings exceed thresholds by a large margin. Our find-
ings suggest that boards contribute towards the integrity of financial state-
ments, as predicted by agency theory.
Keywords: corporate governance, boards of directors, abnormal accruals,
earnings management
* The authors are from Lancaster University. They gratefully acknowledge the helpful
comments of the anonymous referee and those of Steve Lim, Gilad Livne, Scott
Richardson, Lakshmanan Shivakumar, Judy Tsui, and seminar participants at Bristol,
U.C. Dublin, Dundee, Glasgow, Lancaster, London Business School, University of
Science and Technology, Hong Kong, Feng Chia University, Taiwan, Stockholm, the
Scottish Institute for Research in Investment and Finance, the 2000 Annual Meeting of
the European Finance Association and the 2001 Annual Conference of the British
Accounting Association. Financial support was provided by the Research Board of the

Institute of Chartered Accountants in England and Wales, The Leverhulme Trust, and
the Economic and Social Research Council (contract No. H53627500497). (Paper
received June 2004, revised and accepted November 2004)
Address for correspondence: Ken Peasnell, Management School, Lancaster University,
Lancaster LA1 4YX, UK.
e-mail:
Journal of Business Finance & Accounting, 32(7) & (8), S eptember/October 2005, 0306-686X
#
Blackwell Publishing Ltd. 2005, 9600 Garsington Road, Oxford OX4 2DQ, UK
and 350 Main Street, Malden, MA 02148, USA.
1311
1. INTRODUCTION
Boards of directors are widely believed to play an important
role in corporate governance, particularly in monitoring top
management (Fama and Jensen, 1983). The governance debate
emphasises the distinctive contribution that outside directors
can make in helping to ensure that managers act in the interests
of outside stockholders (Fama, 1980; and Fama and Jensen,
1983). Prior US research indicates that outside directors influ-
ence a wide range of board decisions, including CEO removal
(Weisbach, 1988), negotiation of tender offer bids (Byrd and
Hickman, 1992) and resistance to greenmail payments (Kosnik,
1987). In this paper, we test whether the influence of outside
directors extends to the financial reporting process. In particu-
lar, we examine whether the incidence of earnings management
depends on board monitoring.
Studies that examine the relation between board monitoring
and financial reporting have mostly focused on blatant viola-
tions of Generally Accepted Accounting Principles (GAAP). For
example, Beasley (1996) reports that the incidence of financial

statement fraud in the US is lower for firms where the propor-
tion of outside directors is relatively high. Dechow et al. (1996)
report similar findings for firms subject to SEC accounting
enforcement actions. These studies provide evidence of a link
between gross violations of accounting standards and board
structure. However, whether this link extends to more subtle
accruals-based earnings management permissible within GAAP
remains an unresolved issue that this paper seeks to address.
Opportunities for earnings management arise because of
flexibility permitted by GAAP. The purpose of this paper is to
investigate whether boards actively monitor and take actions
that reduce the incidence of earnings management when the
incentives for manipulations are high. Our tests focus on situa-
tions where performance is either poor (in which case the
incentive will be to manage earnings upwards), or exceptionally
good (in which case the incentive will be to manage earnings
downwards).
We use abnormal working capital accruals to proxy for earn-
ings management. Our focus is on two dimensions of board
monitoring in the UK: the proportion of outside directors and
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the presence of an audit committee. The UK provides an inter-
esting experimental setting for investigating these issues since
there is greater variation in outside director representation on
boards in the UK than in the US (Peasnell et al., 1999) and audit
committees are not mandatory. Our results show that when pre-
managed earnings are negative or below last year’s reported
earnings, abnormal working capital accruals are less positive if

the proportion of outsiders on the board is relatively high.
Furthermore, we find that the chance of abnormal accruals
being sufficiently large as to result in reported earnings exceed-
ing the thresholds is significantly lower for firms with a high
proportion of outside board members. Our findings are consis-
tent with the prediction that outside directors contribute
towards the integrity of financial statements. However, boards
appear only to intervene in the case of income-increasing earn-
ings management: we find little evidence that outside directors
are associated with income-decreasing accruals when the incen-
tives to manipulate earnings downwards might be deemed to be
strong. Finally, we find that the mere presence or absence of an
audit committee has no measurable impact on earnings man-
agement. While audit committees are voluntary in the UK, 84%
of the companies in our sample had set up such a committee,
which might account for this null result.
The next section reviews the literature on the monitoring role
of boards of directors and develops our hypotheses. Section 3
presents the methods used to identify earnings management
and explains the research design. The data and sample are
described in Section 4. Section 5 presents the empirical results.
Our conclusions appear in Section 6.
2. HYPOTHESIS DEVELOPMENT
(i) Governance and Earnings Management
Schipper (1989) defines earnings management as purposeful
intervention in the external financial reporting process, with a
view to obtaining private gain for shareholders or managers.
Shareholders will gain when earnings management is used to
signal managers’ private information (Healy and Palepu, 1995),
to avoid costly debt re-contracting or to reduce political costs

BOARD MONITORING AND EARNINGS MANAGEMENT 1313
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(Watts and Zimmerman, 1986). Managers can also use earnings
management to extract rents from shareholders. Such gains
could take the form of increased compensation (Healy, 1985;
and Holthausen et al., 1995) or reduced likelihood of dismissal
when performance is low (Weisbach, 1988). We focus on the
role of corporate governance in constraining earnings
management.
Two measures of board monitoring that have been widely used
in the literature are the proportion of board members classified as
outside directors (e.g., Vicknair et al., 1993) and whether the board
has an audit committee (e.g., Pincus et al., 1989; C ollier, 1993; and
Collier and Gregory, 1999 ). The gov ernance literature emphasises
the role of outside directors in resolving agen cy problems between
managers and shareholders through the creation of appropriate
employment contracts and the subsequent monitoring of manage-
rial behaviour. Fama (1980) and Fama and Jensen (1983) argue
that outside directors have incentives to be effective monitors in
order to m aintain the value of t heir reputational capital. Prior US
research generally supports the predic tion that bo ard effectiveness
in protectin g shareho lders’ wealth is a positive function of the
proportion of outsiders o n t he board (Weisbach, 1988 ;
Rosenstein and Wyatt, 1990; Byrd and Hickman, 1992; Brickley
et al., 1994; and McWilliams and Sen, 1997).
1
The effectiveness of the board’s monitoring activities might
also depend on how the board is structured and organized.
Boards often delegate work on important tasks to standing

committees reporting directly to the main board (Klein, 1998).
The board committee responsible for financial reporting is the
audit committee, if one exists. The audit committee has specific
responsibility for the production of financial statements, and
usually for communicating with the external auditor. Audit
committees are not mandatory in the UK, although listed firms
1 The board’s effectiveness at monitoring the financial reporting process will depend on
the ability of outside directors to understand earnings management methods. Although
the level of accounting expertise, and hence monitoring effectiveness, will vary across
boards, there are at least two reasons for having confidence in outside directors’ general
ability in this regard. First, outside directors often have a financial background. For
example, Peasnell et al. (1999) report that over a quarter of all UK board members are
professionally qualified accountants. Second, outside directors frequently hold senior
management positions in other large corporations. As such, they are likely to be familiar
with financial reporting from a senior management perspective.
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are encouraged to form them (Collier, 1993; and Collier and
Gregory, 1999).
2
However, the creation of an audit committee
does not absolve the full board from its financial reporting
responsibilities. The full board will often have other reasons to
consider financial reporting issues, because accounting numbers
figure prominently in such matters as determining management
compensation, reviews of operating results and making invest-
ment decisions. The incremental monitoring contribution of
an audit committee is an empirical issue on which this study
aims to shed light.

The preceding discussion takes the perspective that earnings
management is undesirable because it is costly to shareholders.
However, signalling-based motivations for earnings management
need to be considered as well. Earnings management will benefit
shareholders if managers use accounting discretion to signal
private information about future performance. Subramanyam
(1996) shows that, in the US, discretionary accruals predict
future profitability and dividend changes, suggesting that man-
agers do use their discretion to improve the informativeness of
earnings. In such circumstances, shareholders will not expect
boards to constrain earnings management. We therefore start
our empirical analysis by considering whether signalling can
explain discretionary accruals behaviour, before investigating
the monitoring roles of the board and the audit committee.
(ii) Earnings Management Relative to Thresholds
Recent evidence suggests that the incidence of earnings manage-
ment is particularly pronounced when earnings fall below certain
thresholds. Three thresholds have been considered in the litera-
ture: avoiding reporting a loss; reporting a growth in profits; and
meeting the analysts’ consensus forecast. Burgstahler and Dichev
(1997) and Degeorge et al. (1999) find that there is a higher-than-
expected frequency of firms in the US with slightly positive
2 Collier (1993) provides evidence on the factors affecting the formation of audit
committees in the UK prior to the governance recommendations set out in the
Cadbury Report (1992). Since the London Stock Exchange’s decision to adopt the
Cadbury recommendations on board composition and audit committee formation, the
number of firms with such committees has increased dramatically. However, unlike in
the US, firms still have the option not to form an audit committee. As we show later in
the paper, a minority of firms exercise their option not to form an audit committee.
BOARD MONITORING AND EARNINGS MANAGEMENT

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reported earnings (and earnings changes) and a lower-than-
expected frequency of firms with slightly negative reported earn-
ings (and earnings changes). The same pattern has been observed
in the UK (Gore et al., 2002). Such discontinuities in the distribu-
tions are consistent with managers trying to beat the benchmarks
in question.
3
A key issue is how managers decide which bench-
mark to try to beat when the benchmarks conflict. Degeorge et al.
(1999) report that there appears to be a hierarchy to the bench-
marks, with firms behaving as if reporting a profit is of most
importance, followed by reporting growth in earnings, with meet-
ing analysts’ forecasts mattering only if the other two thresholds
have been met. We focus on avoiding losses and declines in profit
benchmarks since as well as being more important, we are able to
include in our analysis the many firms for which consensus fore-
casts are not available, and thereby to achieve more powerful tests.
There are a number of possible reasons for such threshold-
targeting earnings management b ehaviour. One possibility is
that capital market participants’ implicit contracts with manage-
ment are defined in terms of these simple thresholds. For
example, there is considerable anecdotal evidence of share-
holders increasing their monitoring activities when a loss or a
decline in earnings is reported, with significant knock-on costs
for man agemen t in the f or m of reduced compensatio n and an
increased probability of d ismissal. Consistent with this view, US
research reveals that firms subject to shareholder activism tend

to be characteri sed by poor earnings performance (Karpoff,
1998). Another r eason might be the fear that failing to meet a
threshold will result in a large decline in stock price.
4
Whatever,
the reason, Dechow et al. (2000) report that a ttempts by US
firms to avoid reporting losses and earnings declines appear to
be driven by managers’ desires to opportunisti cal ly delay
reporting poor performance. Thus, if board monitoring is
associated with earnings management, we expect that our
3 Other factors might play a role as well. For example, Beaver et al. (2003) show that, in
the US, the asymmetric treatment of income taxes and special items for profit and loss
firms can account for about two-thirds of the discontinuity in the distribution of
earnings.
4 For example, Skinner and Sloan (2002) have found that growth stocks in the US tend
to exhibit an asymmetrically large negative price response to negative earnings
surprises.
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ability to detect such a relation will be greatest close to threshold
points. Consequently, we condition our empirical tests on the
proximity of pre-managed earnings to zero earnings and zero
change in earnings. We predict that board monitoring will
constrain income-increasing earnings management when pre-
managed earnings undershoot these thresholds.
The preceding discussion focuses on the link between board
monitoring and the incidence of income-increasing earnings
management. Earnings management, however, is not restricted
solely to income-increasing behaviour. Prior research indicates

that, under certain conditions, managers engage in income-
decreasing earnings management. For example, Degeorge et al.
(1999) find that managers appear systematically to manipulate
reported earnings downwards when pre-managed earnings
exceed threshold earnings by a substantial amount.
5
Similarly,
Healy (1985), Gaver et al. (1995) and Holthausen et al. (1995)
report evidence of income-decreasing accounting choices by US
firms when managers’ accounting-based bonuses are at their
maximum. There are several plausible explanations for these
income-decreasing accounting choices. One possibility is that
managers prefer to shift abnormal positive earnings forward
in time in order to make the thresholds easier to cross and
targets easier to meet in the future. Another possibility is that
managers are reluctant to report large gains because of fears
that it will result in increased earnings-based performance tar-
gets for them in the future. If downward manipulation imposes
significant costs on external parties, boards should be as con-
cerned with income-decreasing manipulations as they are with
income-increasing ones. Therefore, we also test whether board
monitoring is negatively associated with income-decreasing
earnings management when pre-managed earnings exceed
these thresholds by a large margin.
5 The big bath hypothesis predicts income-decreasing earnings management when pre-
managed earnings fall well below the threshold. We have examined the issue of big bath
accrual choices for our sample. Untabulated results provide no indication that our
below-target firms were engaged in big bath accounting. One reason might be that the
incidence of big baths is dependent on other factors, such as whether or not there has
been a change in management. This is an issue that falls outside the scope of our study

and is therefore an aspect of earnings management that we do not investigate any
further in this paper.
BOARD MONITORING AND EARNINGS MANAGEMENT
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Our empirical tests explicitly examine both upward a nd
downward manipulations. However, we anticipate that boards
will have asymmetric loss functions with respect to earnings
management because the penalties a ssoci ated with overst ating
earnings (e.g., loss of reputation) are likely to exceed the costs
of unde rstat ing earnings. This lead s us to co njec tur e that the
incentives for b oards to monitor income-increasing earnings
management are greater than those to monitor income-
decreasing earnings management. Whether this is the case
remainsanempiricalissueonwhichweaimtoshedlightin
this paper.
(iii) The Intervening Effect of Managerial Share Ownership
The need for board monitoring depends on the extent to which
managers’ interests diverge from t hose of shareholders and other
investors. We expect share ownership by managers to lead to a
closer alignment of interests. US research has found that manage-
rial own ership is a ssociated with l ower levels of earnings man age-
ment (Dhaliwal et al., 1982; and Warfield et al., 1995). Also, there is
evidence in both the US and the UK of a negative association
between m anagerial share o wnership a nd both the proportion o f
outside board members (Weisbach, 1988; and Peasnell et al., 2003)
and the presence of an audit committee (Pincus et al., 1989 ; and
Collier, 1993). This prior research suggests that the demand for
board monitoring declines with managerial ownership and that

managerial ownership interacts wi th board monitoring of earnings
management. More precisely, we hypothe size that the constraining
association betwee n earnings manag ement and (i) the prop ortion
of outsid e directors and (ii) the existence of an audit committee will
be more pronounced when th e lev el of manage rial share o wner-
ship is low.
3. METHODOLOGY
(i) Measuring Earnings Management
Manipulation of operating accruals is likely to be a favored
instrument for opportunistic earnings management because
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they generally have no direct cash flow consequences
6
and are
relatively difficult to detect. A more costly method to manipulate
earnings is by changing the way the firm does business. The
firm could, for example, boost reported profit by cutting back
on advertising and research and development (Bushee, 1998).
There are many more possibilities: selling assets it would other-
wise keep (Bartov, 1993; and Poitras et al., 2002); cutting back
on staff development and essential equipment maintenance;
channel stuffing; the list is almost endless. All such actions are
costly, in the sense that they have negative effects on the firm’s
future cash flows. Such manipulations reduce the value of the
firm and as such are more costly than mere accounting manip-
ulations. We therefore expect that the manipulation of accruals
will be the instrument chosen first, before management resorts
to more costly ones involving real changes in investment and

operating activities. We focus only on the accounting
manipulations.
We use abnormal accruals as our proxy for earnings manage-
ment.
7
Several methods have been proposed in the literature
for separating operating accruals into abnormal (or dis-
cretionary) and normal (or non-discretionary) components.
(See Dechow et al., 1995, for a review of these models.) The
most frequently used methods are the Jones (1991) model and
the modified-Jones model (Dechow et al. 1995). Both methods
involve estimating parameters for normal accrual activity by
regressing a measure of accounting accruals on proxies for
normal business activity. These estimated normal accrual para-
meters are then combined with event-period data to generate
estimated unexpected accrual activity.
We estimate abnormal accruals using the modified-Jones (m-
J) model. Dechow et al. (1995) present evidence that the m-J
model is more powerful at detecting sales-based manipulations
6 Accruals can have tax effects, but these are likely to be of second-order importance in
the UK, given that financial reporting and tax accounting are governed by different
measurement rules.
7 Accruals-based measures are theoretically appealing because they aggregate into a
single measure the net effect of numerous recognition and measurement decisions,
thereby capturing the portfolio nature of income determination (Watts and
Zimmerman, 1990). Moreover, to the extent that boards treat earnings from operations
and cash from operations as key indicators, a simple comparison of the two numbers will
provide them with direct insight into the aggregate effect of operating accruals.
BOARD MONITORING AND EARNINGS MANAGEMENT
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than the original Jones (1991) model.
8
We estimate the m-J
model on a cross-sectional basis in order to maximize our sam-
ple size and to avoid the survivorship bias problem inherent in
the use of a firm-specific time-series approach (Becker et al.,
1998; and DeFond and Subramanyam, 1998). In contrast to
prior studies that model total operating accruals, we focus spe-
cifically on the working capital component. Prior studies have
generally defined total operating accruals as working capital
accruals plus a key long-term accrual, depreciation. We ignore
the long-term component of total accruals, for several reasons.
As Beneish (1998) points out, depreciation offers limited poten-
tial as a tool for systematic earnings management since changes
in depreciation policy cannot be made very frequently without
attracting adverse attention from the auditor or investors.
However, this is not the case with some other long-term
accruals, such as defined benefit pension obligations and certain
environmental liabilities where the amounts are very sensitive to
key assumptions. Nevertheless, we follow prior practice and
exclude these non-depreciation long-term accruals from our
analysis because of their very complexity. No prior study has
included long-term accruals other than depreciation. Lacking a
model of what drives those other long-term accruals, it is diffi-
cult to distinguish between normal and abnormal long-term
accruals. The power of our tests will be adversely affected by
this omission.
The m-J model parameters are estimated with the following

cross-sectional OLS regression:
WC
it
TA
i;tÀ1
¼ !
0
1
TA
i;tÀ1

þ !
1
ÁREV
it
TA
i;tÀ1

þ 
i
; ð1Þ
8 A number of different models have been developed to measure abnormal accruals. An
example is the margin model developed in Peasnell et al. (2000) that formally links sales,
accruals related to transactions with customers and suppliers, and operating profit.
Simulations by Peasnell et al. (2000) indicate that the Jones and modified-Jones models
are likely to be better at detecting revenue and bad debt manipulations than the margin
model, whereas the margin model is better at detecting non-bad debt expense manip-
ulations. Since we have no priors as to what form earnings management might take, to
aid comparability with related prior research, we have focused on the more familiar
modified-Jones model. We have also replicated many of our key tests using the margin

model, with essentially the same results.
1320 PEASNELL, POPE AND YOUNG
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where WC
it
is working capital accruals for firm i in year t,
defined as the change in non-cash current assets minus the
change in current liabilities, ÁREV
it
is the change in revenue
for firm i in year t, !
0
and !
1
are regression coefficients, and 
i
is
the (assumed i.i.d.) regression residual. Model estimates are
obtained for each industry and year combination. For estima-
tion purposes, we scale the variables by beginning-of-period
total assets, TA
i,tÀ1
, and suppress the intercept.
9
Industry-year
portfolios with less than ten observations are excluded from the
analysis.
Following Dechow et al. (1995), abnormal accruals (AA) is
defined as follows:

AA
i

WC
it
TA
i;tÀ1
À ^$
0
1
TA
i;tÀ1

þ ^$
1
ÁREV
it
À ÁREC
it
TA
i;tÀ1

; ð2Þ
where
^
!
0
and
^
!

1
are the OLS regression estimates of !
0
and !
1
respectively, obtained from equation (1), and ÁREC
it
is the
change in receivables during the year in question. Adjusting
ÁREV
it
by ÁREC
it
is designed to help capture credit sales
manipulations by treating
^
!
1
ÁREC
it
as a component of abnor-
mal accruals (Dechow et al., 1995).
Our empirical tests seek to isolate the incentives for earnings
management by comparing pre-managed earnings (PME
t
) with
benchmark or ‘target’ earnings levels. As explained in sub-sec-
tion 2(ii) above, we employ two benchmarks for current period
earnings: (i) zero and (ii) earnings reported in the previous year
(EARN

tÀ1
). We predict that managers will seek to manipulate
earnings upwards when either PME
t
< 0 or PME
t
< EARN
tÀ1
.
We also predict that managers will seek to manipulate earnings
downwards when PME
t
exceeds the zero and EARN
tÀ1
thresh-
olds by a large margin, so as to increase the likelihood of meet-
ing the respective threshold in future periods. We then examine
whether the level of board monitoring influences the amount of
upward (downward) earnings management when pre-managed
earnings undershoot (significantly exceed) target earnings.
9 We have also replicated all the tests reported in the paper using a version of (1) that
replaces the first term on the right-hand side with a constant. The results are substan-
tially the same.
BOARD MONITORING AND EARNINGS MANAGEMENT
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We use cash flow from operations (CFO
t
) as the instrument for

PME
t
. As we explain in the Appendix, the problem with using the
‘obvious’ measure of PME, namely EARN
t
À AA
t
,isthatitis
subject to a backing-out problem, where error in estimating AA
will lead automatically to equal error in the estimation of PME.
This in turn could possibly induce spurious correlation between
AA and PME. We have repeated all analyses using EARN
t
À AA
t
with substantially similar – indeed somewhat stronger – results to
those reported below. However, because of the possibility of spur-
ious correlation, we err on the side of caution and report only the
results that use CFO as the proxy for PME.
(ii) The Model
We test the impact of board monitoring on the extent of earn-
ings management by estimating the following pooled OLS
regression separately for each earnings threshold (zero and
EARN
tÀ1
, respectively):
AA
it
¼ 
0

þ 
1
BELOW
it
þ
2
HIGH
it
þ 
3
OUT
it
þ 
1
OUT
it
Á BELOW
it
þ 
2
OUT
it
Á HIGH
it
þ 
4
AC
it
þ 
3

AC
it
Á BELOW
it
þ 
4
AC
it
Á HIGH
it
þ
X
K
k¼1

k
Controls
kit
þ "
it
:
ð3Þ
In equation (3), AA is abnormal accruals scaled by total assets and
estimated using equation (2). We assume that what might be
material earnings management in a small company will not be so
in a large one. In other words, the underlying model is in deflated
form. BELOW is an indicator variable taking the value of one
if our proxy for pre-managed earnings is below threshold
earnings – PME
t

< 0 and PMT
t
< PMT
tÀ1
respectively – and
zero otherwise. Holding board monitoring effects constant, we
predict that 
1
will be positive due to income-increasing earnings
management behaviour.
HIGH is an indicator variable taking the value of one if
our proxy for pre-managed earnings (CFO) exceeds zero or
EARN
tÀ1
, as the case may be, by a specified margin and zero
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otherwise. For the regressions where PME is benchmarked
against zero, we define HIGH as one if PME for firm i in period
t exceeds the 75
th
percentile of the distribution of positive pre-
managed earnings and zero otherwise. For the regressions
where PME
t
is benchmarked against last year’s reported earn-
ings, HIGH is set equal to one if PME
t
minus EARN

tÀ1
for firm i
in period t exceeds the 75
th
percentile of that variable’s distribu-
tion of positive pre-managed earnings changes, and zero other-
wise. In the absence of board monitoring, we are expecting
firms to engage in income-decreasing earnings management;
we therefore predict that 
2
will be negative.
OUT is the proportion of outside board members and AC is
an indicator variable taking the value of one if the firm has an
audit committee and zero otherwise. If outside directors and
audit committees fulfill a monitoring role and seek to reduce
earnings management, we predict that 
1
and 
3
will be nega-
tive and that 
2
and 
4
will be positive.
Equation (3) also includes proxies for other factors that might
affect the level of earnings management. These include other
elements of the governance system such as board size, the pre-
sence of a dual Chairman and CEO, ownership structure and
auditor type, other earnings management stimuli such as lever-

age and financial performance. CFO (scaled by total assets) is
included as a control for errors in the measurement of abnor-
mal accruals. We predict CFO will be negatively associated with
AA. As we explain in the Appendix, we also use CFO to proxy
for PME; hence any hypothesis about the sign of the CFO
coefficient is therefore a joint one involving both governance
and measurement error factors. Our monitoring theory pre-
dicts a zero association between AA and PME when the latter
is outside the critical zones identified by the BELOW and HIGH
indicator variables. Measurement error considerations and our
monitoring theory therefore both predict that the coefficient on
CFO will be non-positive.
4. DATA AND SAMPLE
Our empirical tests are conducted using data for UK listed firms
with fiscal year ends between June 30, 1993 and May 31, 1996.
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The m-J model is estimated for each industry (Datastream
level-6) and year combination, using all firms on the Datastream
Active and Research files with available accruals data.
10
The num-
ber of firms used to estimate the models in 1993, 1994 and 1995
were 620, 651 and 657, respectively. The maximum number of
observations for any given industry-year combination is 56
(general engineering, 1995) while the mean (median) estimation
portfolio size is 21 (18) observations.
Board data were hand-collected using the following sampling
procedure. For each year we selected the largest 1000 listed

firms based on market capitalization at December 31, as
reported in the London Share Price Database. We then excluded
all financial firms (SIC codes 60–69) because they have funda-
mentally different accruals processes that are not captured by
the m-J model. We also excluded all regulated utilities (SIC
codes 40–44, 46, 48–49) because of differences in their incen-
tives and opportunities to manage earnings. The Price
Waterhouse Corporate Register is used as the source of board
composition data, and firms’ annual reports are used to identify
the presence or absence of an audit committee.
11
The Corporate
Register is also the main source of managerial share ownership
data, supplemented where necessary by annual reports. The
Corporate Register reports the number of shares held by each
executive board member, classified into beneficial and non-ben-
eficial categories, together with the total number of the firm’s
shares outstanding at the fiscal year-end. Since it is often impos-
sible to determine the voting and control rights of non-benefi-
cial shareholdings, we restrict our definition of ownership to
beneficial shareholdings only. For the same reason, we also
exclude all family and family-related holdings, together with
shares held in employee pension and share option plans. Data
on external share ownership were collected from the Stock
Exchange Official Yearbook. Data on auditor identity were
10 The sample of firm-years used to test the association between earnings management
and board effectiveness is a subset of the firm-year observations used to estimate the m-J
model.
11 The Corporate Register is published quarterly by Hemmington Scott Ltd. and includes
data for all firms listed on the London Stock Exchange. Hemmington Scott constructs

their board composition database using information from the London Stock Exchange
and Reuters.
1324 PEASNELL, POPE AND YOUNG
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collected from the Corporate Register. All remaining data, includ-
ing that used to calculate abnormal accruals, were obtained
from Datastream.
The final sample consists of 1,271 firm-years with the com-
plete data needed to estimate equation (3). The sample com-
prises 559 firms drawn from 34 Datastream level-6 industrial
groups.
12
The distribution of firms across sample years is as
follows: 125 firms are included in only one year, 156 firms are
included in two years, and 278 firms have data for each of the
three sample years. Annual sample sizes are 406, 453 and 412
for 1993, 1994 and 1995, respectively. When pre-managed
earnings are benchmarked against zero, 134 firm-year observa-
tions (10.7%) are classified as below target, while 260 (20.5%)
are classified as well-above target. Alternatively, when pre-man-
aged earnings are benchmarked against EARN
tÀ1
, 269 firm-
year observations (21.6%) are classified as below target, while
177 (13.9%) are classified as well-above target. The difference in
the below-target sample sizes reflects the fact that fewer firms
report losses than earnings declines.
Descriptive statistics for the explanatory variables are
reported in Table 1. The average board in our sample contains

eight directors, of which approximately 43% are outsiders.
Audit committees are present in 85% of firm-year observations.
The fact that so many firms in our sample have audit commit-
tees suggests that the inclusion of an indicator variable in our
regressions may not be sufficient to capture the effectiveness of
this particular governance mechanism.
Regarding the additional control variables, the roles of chair-
man and chief executive are combined in 24% of cases. The
typical sample firm has median managerial (institutional) own-
ership of 2% (19%). These levels are comparable to those
reported in previous studies of the UK (e.g., Short and
Keasey, 1999). Over half of the sample (53%) has at least one
external blockholder whose stake exceeds 10%.
12 Firms are distributed fairly evenly across the industrial groups. The largest industry
is Engineering with 115 firm-year observations, representing 9% of the final sample. No
other industrial group contains more than 6% of the sample.
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5. RESULTS
(i) A Signalling Explanation
As explained in sub-section 2(ii), before considering whether
board monitoring influences the extent of earnings manage-
ment, we must first establish that such earnings management
is not in shareholders’ interests. If managers are using their
accounting discretion to signal private information about future
Table 1
Descriptive Statis tics for Explanatory Variables
a

Variable Mean St. Dev. Min. Q1 Median Q3 Max.
OUT 0.427 0.144 0.000 0.333 0.429 0.500 0.857
BRDSIZE 8.010 2.653 3.000 6.000 8.000 9.000 24.000
BRDOWN 0.086 0.144 0.000 0.002 0.016 0.113 0.750
INSTOWN 0.216 0.166 0.000 0.079 0.190 0.330 0.968
LEV 0.523 0.185 0.071 0.404 0.515 0.629 2.193
CFO 0.116 0.185 À2.991 0.064 0.108 0.157 2.476
AC ¼ 1 0.836
DUAL ¼ 1 0.245
BLOCK ¼ 1 0.533
AUD ¼ 1 0.854
REL ¼ 1 0.530
Notes:
a
The sample comprises 1271 firm-year observations for UK listed firms over the period
1993–1996.
OUT is the number of outside board members over the total number of board members.
BRDSIZE is the total number of board members.
BRDOWN is the number of shares beneficially owned by inside directors over total
number of shares outstanding.
INSTOWN is the number of shares owned by institutional investors over total number
of shares outstanding.
LEV is total debt over total assets.
CFO is operating cash flow over beginning-of-year total assets.
AC is an indicator variable taking the value of one if the firm has an audit committee and
zero otherwise.
BLOCK is an indicator variable taking the value of one if the firm has an external
stockholder owning !10% of the outstanding shares and zero otherwise.
DUAL is an indicator variable taking the value of one if the roles of Chairman and CEO
are combined and zero otherwise.

AUD is an indicator variable taking the value of one if the firm has a Big 5 auditor and
zero otherwise.
REL is an indicator variable taking the value of one if earnings before abnormal
accruals, scaled by beginning-of-period total assets, are less than industry median scaled
reported earnings and zero otherwise.
All values are measured at fiscal year-end, unless otherwise indicated.
1326 PEASNELL, POPE AND YOUNG
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earnings performance, then it is unclear why boards should
seek to prevent such behaviour. We therefore present evidence
on the extent to which abnormal accrual activity is attributable
to signalling. If a signalling rationale explains abnormal accrual
activity, then we would expect to observe a positive association
between current period abnormal accruals and future earnings
changes.
We test this prediction using a logistic regression, where the
dependent variable takes the value of one if our proxy for one-
period-ahead pre-managed earnings is higher than reported
earnings in the current period and zero otherwise:
log
probðPME
tþ1
> EARN
t
Þ
probðPME
tþ1
EARN
t

Þ

¼ 
0
þ 
1
CFO
t
þ 
2
NA
t
þ 
3
AA
t
: ð4Þ
In addition to abnormal accruals, the set of explanatory
variables also includes measures of current period operating
cash flow and normal accruals. Separate regressions are esti-
mated for the below- and above-threshold sub-samples. The
results for equation (4) appear in Table 2. Regardless of
whether pre-managed earnings are benchmarked against zero
(Panel A) or EARN
tÀ1
(Panel B), the estimated coefficients
on AA are significantly negative when PME is above the thres-
hold and indistinguishable from zero when PME is below the
threshold. These findings do not support a signalling explan-
ation. We therefore conclude that it is appropriate to proceed as

though abnormal accruals are potentially costly to market
participants.
(ii) Board Monitoring
Equation (3) provides our basic model for capturing the impact
of board monitoring on abnormal accrual activity. We consider
two versions of the model, M1 and M2. M1 includes only our
test variables OUT and AC, together with the indicator variables
BELOW and HIGH and their interactions with the test vari-
ables. M2 is the full model, inclusive of the vector of control
variables.
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The control variables are as follows. DUAL is an indicator of
CEO power, set equal to one if the roles of chairman and chief
executive are combined, and zero otherwise. BRDSIZE is the
number of directors and serves as a measure of board effective-
ness. BRDOWN is the proportion of shares owned by inside
directors and proxies for the congruence of interests of share-
holders and management. We use two indicators of the mon-
itoring activities of important shareholders: INSTOWN is the
Table 2
Logistic Regression Models Relating Future Pre-mana ged Earnings
Changes to Measures of Current Period Accruals and Cash Flows
a
log
probðPME
tþ1
> EARN
t

Þ
probðPME
tþ1
EARN
t
Þ

¼ 
0
þ 
1
CFO
t
þ 
2
NA
t
þ 
3
AA
t
Intercept CFO NA AA À2 Log Like N
Panel A: Earnings Threshold ‡ 0
PME below threshold
Coefficient estimate 0.194 À1.459 0.722 1.045 172.19 130
p-value
b
(0.51) (0.23) (0.90) (0.67)
PME above threshold
Coefficient estimate 0.506 2.799 À4.054 À3.743 1274.91 1084

p-value
b
(0.01) (0.01) (0.12) (0.01)
Panel B: Earnings Threshold ‡ EARN
t{1
PME below threshold
Coefficient estimate 0.265 À0.127 À2.202 0.819 358.31 263
p-value
b
(0.15) (0.86) (0.60) (0.68)
PME above threshold
Coefficient estimate 0.741 1.521 À4.184 À3.701 1093.63 951
p-value
b
(0.01) (0.04) (0.12) (0.02)
Notes:
a
The dependent variable takes the value of one if one-period-ahead pre-managed
earnings (proxied by cash flow from operations) exceeds current period reported earn-
ings and zero otherwise.
b
All probability values are for two-tailed tests.
AA is current period abnormal accruals scaled by beginning-of-period total assets,
estimated using the m-J model.
NA is current period normal accruals scaled by beginning-of-period total assets, meas-
ured as the difference between total working capital accruals and AA.
CFO is current period operating cash flow scaled by beginning-of-period total assets.
1328 PEASNELL, POPE AND YOUNG
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proportion of share owned by institutional investors; BLOCK is
set equal to one if an external shareholder owns more than 10%
of the shares, and zero otherwise. AUD is an indicator of auditor
quality and is set equal to one if the firm has a Big 5 auditor, and
zero otherwise. LEV is the ratio of total debt to total assets and is
included to pick up debt contracting motivations for earnings
management (DeFond and Jiambalvo, 1994). REL is the firm’s
earnings relative to that of the industry and is included to control
for income smoothing (DeFond and Park, 1997). LEV and REL
are controls for other possible reasons why firms might manage
earnings. CFO is a control both for errors in the measurement of
abnormal accruals and for earnings management activity outside
the anticipated critical regions.
The results are reported in Table 3. Columns (i) and (ii)
present results for pre-managed earnings benchmarked against
zero while columns (iii) and (iv) provides findings for pre-man-
aged earnings benchmarked against EARN
tÀ1
. We focus first on
the results where pre-managed earnings are benchmarked
against zero. The positive and significant coefficient estimates
on BELOW in models M1 and M2 are consistent with the
hypothesis that managers make positive abnormal accruals
when pre-managed earnings are negative. Similarly, the nega-
tive and significant coefficients on HIGH in M1 and M2 provide
evidence that managers seek to manipulate earnings down-
wards when pre-managed earnings are high. The results also
provide evidence that outside directors monitor earnings man-
agement activity in certain circumstances. In both models, the
estimated coefficient on the interaction term OUT

ÁBELOW is
negative and significant at the 0.01 level. This suggests less
income-increasing earnings management behaviour to meet or
exceed the threshold for firms whose boards comprise a higher
proportion of outsiders. A comparison of models M1 and M2
reveals that this finding is insensitive to the inclusion of control
variables designed to measure other aspects of firms’ govern-
ance structures. In contrast, the estimated coefficients on the
OUT
ÁHIGH interaction terms are not significant at conven-
tional levels, suggesting that outside directors do not constrain
income-decreasing manipulations.
In addition to examining the impact of board composition on
earnings management, models M1 and M2 also throw light on
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Table 3
OLS Regressions of Abnormal Accruals on Below-threshold and High Pre-
managed Earnings, Allowing for the Intervening Effects of Board Monitoring
a
AA
it
¼
0
þ 
1
BELOW
it
þ 

2
HIGH
it
þ 
3
OUT
it
þ 
1
OUT
it
Á BELOW
it
þ 
2
OUT
it
Á HIGH
it
þ 
4
AC
it
þ 
3
AC
it
Á BELOW
it
þ 

4
AC
it
Á HIGH
it
þ 
1
DUAL
it
þ 
2
BRDSIZE
it
þ 
3
BRDOWN
it
þ 
4
INSTOWN
it
þ 
5
BLOCK
it
þ 
6
AUD
it
þ 

7
SIZE
it
þ 
8
LEV
it
þ 
9
REL
it
þ 
10
CFO
it
þ
X
1995
k¼1994

k
YEAR
kit
þ "
it
Earnings
Threshold ! 0
Earnings Threshold
! EARN
tÀ1

(i) (ii) (iii) (iv)
M1 M2 M1 M2
Variable
Expected
Sign
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Intercept ? 0.015 0.035 0.007 0.031
(0.04) (0.01) (0.26) (0.01)
BELOW þ 0.108 0.058 0.092 0.057
(0.01) (0.01) (0.01) (0.01)
HIGH
b
ÀÀ0.039 À0.028 À0.061 À0.046
(0.01) (0.01) (0.01) (0.01)
OUT ÀÀ0.039 À0.021 À0.021 À0.009
(0.01) (0.07) (0.07) (0.25)
OUT
ÁBELOW ÀÀ0.117 À0.121 À0.080 À0.081
(0.01) (0.01) (0.01) (0.01)

OUT
ÁHIGH þ 0.016 0.010 0.011 0.012
(0.13) (0.21) (0.16) (0.12)
AC À 0.009 0.011 0.001 0.006
(0.12) (0.05) (0.84) (0.27)
AC
ÁBELOW À 0.040 0.032 0.042 0.032
(0.14) (0.19) (0.13) (0.21)
AC
ÁHIGH þÀ0.022 À0.018 À0.004 À0.009
(0.04) (0.06) (0.74) (0.40)
DUAL 0.002 0.001
(0.61) (0.77)
BRDSIZE À0.012 À0.012
(0.02) (0.01)
BRDOWN 0.015 0.018
(0.20) (0.09)
INSTOWN À0.005 À0.005
(0.67) (0.61)
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Table 3 (Continued)
Earnings
Threshold ! 0
Earnings Threshold
! EARN
tÀ1
(i) (ii) (iii) (iv)
M1 M2 M1 M2

Variable
Expected
Sign
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Coefficient
(p-value)
b
BLOCK 0.000 0.001
(0.94) (0.84)
AUD À0.003 À0.004
(0.48) (0.35)
LEV À0.003 0.004
(0.68) (0.63)
REL 0.046 0.030
(0.01) (0.01)
CFO À0.085 À0.076
(0.01) (0.01)
Adj-R
2
0.232 0.382 0.344 0.423
F 47.50 41.10 81.73 48.50
Notes:

a
The sample comprises 1271 firm-year observations for UK-listed firms over the period 1993–1996.
b
Probability values are for one-tailed tests when we have explicit predictions and two-tailed
otherwise.
The dependent variable AA is abnormal accruals scaled by beginning-of-period total assets, esti-
mated using the m-J model.
BELOW is an indicator variable taking the value of one if pre-managed earnings (proxied by
operating cash flow) is less than zero (EARN
tÀ1
) and zero otherwise.
HIGH is an indicator variable taking the value of one if pre-managed earnings (proxied by operat-
ing cash flow) are well above zero (EARN
tÀ1
) and zero otherwise.
OUT is the number of outside board members divided by the total number of board members.
AC is an indicator variable taking the value of one if an audit committee exists and zero otherwise.
DUAL is an indicator variable taking the value of one if the roles of Chairman and CEO are
combined and zero otherwise.
BRDSIZE is the total number of board members.
BRDOWN is the number of shares beneficially owned by inside directors over total number of
shares outstanding.
INSTOWN is the number of shares owned by institutional investors over total number of shares
outstanding.
BLOCK is an indicator variable taking the value of one if the firm has an external stockholder
owning !10% of the outstanding shares and zero otherwise.
AUD is an indicator variable taking the value of one if the firm has a Big 5 auditor and zero
otherwise.
LEV is total debt over total assets.
REL is an indicator variable taking the value of one if earnings before abnormal accruals, scaled by

beginning-of-period total assets, is less than industry median scaled reported earnings and zero
otherwise.
CFO is operating cash flow over beginning-of-year total assets.
YEAR
k
is a vector of indicator variables for fiscal years 1994 and 1995. The coefficient estimates are
not reported for parsimony.
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whether the presence of an audit committee influences abnor-
mal accrual activity. If audit committees play an incremental
role in constraining income-increasing earnings management
then we would expect the estimated coefficient on the
AC
ÁBELOW interaction term to be negative and significant.
Similarly, if audit committees help to limit income-decreasing
earnings management, then the estimated coefficient on
AC
ÁHIGH should be positive and significant. The results pre-
sented in columns (i) and (ii) of Table 3 provide no support for
the audit committee hypothesis: the estimated coefficients dis-
play the wrong signs and are statistically insignificant for
AC
ÁBELOW. However, since only 16% of firms did not have
an audit committee, this null result may be due to a lack of
statistical power in our experimental design.
The results presented in columns (iii) and (iv), where pre-
managed earnings are benchmarked against last period’s
reported earnings, are similar to those discussed above. In

particular, the estimated coefficients on BELOW (HIGH) are
positive (negative) and significant, indicating that managers
seek to manipulate earnings upwards (downwards) when pre-
managed earnings are below (well above) last year’s reported
earnings. The coefficients on the OUT
ÁBELOW interaction
terms are negative and significant, indicating that firms whose
boards contain a higher proportion of outsiders are less likely to
be associated with income-increasing earnings management to
meet or exceed the target. In contrast, the OUT
ÁHIGH coeffi-
cients are statistically indistinguishable from zero. Finally, as
with the results in columns (i) and (ii), there is no evidence
that the mere existence of an audit committee influences either
the level of upward manipulation to meet the threshold or
downward manipulation to rein in earnings.
The above results are insensitive to the inclusion or exclusion
of control variables. Indeed, only BRDSIZE, REL and CFO are
significantly different from zero. The negative coefficient on
BRDSIZE and REL suggest that earnings management is less
likely the larger the size of the board and when pre-managed
earnings are less than the median for its industry. These results
are contrary to prior expectations, as is the lack of significance
of the AUD coefficients. As expected, the coefficient on CFO is
negative.
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(iii) Management Share Ownership
The incentive-alignment effects of managerial ownership

suggest that the demand for monitoring by the board of direc-
tors will be strongest in firms when the separation of ownership
and control is most acute, all other factors held constant. We test
this prediction by extending model (3) to include the three-way
interaction terms OWN
ÁOUTÁBELOW and OWNÁACÁBELOW.
We focus on those cases when pre-managed earnings under-
shoot the threshold because our previous results indicate that
board monitoring is more pronounced in such cases. OWN is an
indicator variable taking the value of one if managerial owner-
ship (BRDOWN) is less than 5% and zero otherwise. We predict
that the estimated coefficients on these three-way interaction
terms will be negative and significant. The reasoning behind
these predictions is that this is the situation where the incentive
to manipulate earnings is highest and external constraints at a
minimum, and hence the need for board monitoring is greatest.
We also include OWN in place of the control variable
BRDOWN used in the previous model,
13
together with the
two-way interaction term OWN
ÁBELOW, to test whether low
ownership has any direct effect on earnings management.
The results reported in Table 4 provide little support for these
conjectures. When pre-managed earnings are benchmarked
against zero, the estimated coefficients on the
OWN
ÁOUTÁBELOW term are negative and significant, as
expected. However, the coefficient is only significant at the 0.10
level, and then only in the case of model M1 where control

variables are omitted. When the benchmark is the previous
year’s reported earnings, the OWN
ÁOUTÁBELOW coefficients
are insignificant for both models. For both benchmarks, the two-
way interaction variable OUT
ÁBELOW remains negative and
(weakly) significant, suggesting that boards continue to have a
constraining influence on earnings management even when
shareholder and manager interests are better aligned. The poor
explanatory power of the audit committee variable is unchanged
by the inclusion of the two- and three-way interactions with OWN.
13 Note that OWN equals one when managerial share ownership is less than 5%
whereas BRDOWN is the proportion of shares owned by management. We therefore
expect the coefficients for OWN and BRDOWN to be opposite in sign.
BOARD MONITORING AND EARNINGS MANAGEMENT
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Table 4
OLS Regressions of Abnormal Accruals on Below- threshold and High
Pre-managed Earnings, Allowing for the Intervening Effects of Board
Monitoring and Managerial Stock Ownership
a
AA
it
¼ 
0
þ 
1
BELOW

it
þ 
2
HIGH
it
þ 
3
OUT
it
þ 
1
OUT
it
Á BELOW
it
þ 
2
OUT
it
Á HIGH
it
þ 
4
AC
it
þ 
3
AC
it
Á BELOW

it
þ 
4
AC
it
Á HIGH
it
þ 
5
OWN
it
þ 
5
OWN
it
Á BELOW
it
þ 
1
OUT
it
Á BELOW
it
Á OWN
it
þ 
2
AC
it
Á BELOW

it
Á OWN
it
þ Controls þ "
it
Earnings
Threshold ! 0
Earnings
Threshold
! EARN
tÀ1
(i) (ii) (iii) (iv)
M1 M2 M1 M2
Variable
Expected
Sign
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Intercept ? 0.017 0.038 0.009 0.035
(0.02) (0.01) (0.18) (0.01)

BELOW þ 0.090 0.049 0.084 0.050
(0.01) (0.03) (0.01) (0.01)
HIGH
b
ÀÀ0.041 À0.029 À0.064 À0.047
(0.01) (0.01) (0.01) (0.01)
OUT ÀÀ0.030 À0.017 À0.012 À0.006
(0.03) (0.12) (0.21) (0.34)
OUT
ÁBELOW ÀÀ0.076 À0.088 À0.058 À0.059
(0.12) (0.06) (0.09) (0.08)
OUT
ÁHIGH þ 0.007 À0.001 0.009 0.009
(0.37) (0.48) (0.27) (0.27)
AC À 0.010 0.011 0.002 0.006
(0.09) (0.06) (0.70) (0.27)
AC
ÁBELOW À 0.037 0.030 0.043 0.032
(0.16) (0.22) (0.12) (0.22)
AC
ÁHIGH þÀ0.021 À0.017 À0.003 À0.008
(0.05) (0.08) (0.80) (0.45)
OWN þÀ0.009 À0.007 À0.009 À0.007
(0.01) (0.05) (0.01) (0.05)
OWN
ÁBELOW þ 0.046 0.027 0.015 0.014
(0.11) (0.21) (0.28) (0.28)
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(iv) Beating the Benchmark
We conjecture that managers are most likely to engage in
income-increasing earnings management when pre-managed
earnings fall short of key threshold levels, and that it is the job
of the outside directors to prevent them from doing so. This
raises the question of whether the likelihood of actually beating
the threshold is lower for firms with a high proportion of out-
side board members. Accordingly, we estimated logistic regres-
sions for firms with pre-managed earnings below the thresholds
Table 4 (Continued)
Earnings
Threshold ! 0
Earnings
Threshold
! EARN
tÀ1
(i) (ii) (iii) (iv)
M1 M2 M1 M2
Variable
Expected
Sign
Coefficient
(p-value)
b
Coefficient
(p-value)
b
Coefficient
(p-value)
b

Coefficient
(p-value)
b
OWNÁOUTÁBELOW ÀÀ0.097 À0.078 À0.038 À0.040
(0.10) (0.13) (0.23) (0.20)
OWN
ÁACÁBELOW À 0.014 0.019 0.002 0.005
(0.60) (0.42) (0.90) (0.77)
Control variables Not
included
Included Not
included
Included
Adj-R
2
0.235 0.383 0.364 0.422
F 32.48 35.72 55.29 41.96
Notes:
a
The dependent variable AA is abnormal accruals scaled by beginning-of-period total
assets, estimated using the m-J model.
b
Probability values refer to one-tailed tests when we have explicit predictions and two-
tailed otherwise.
BELOW is an indicator variable taking the value of one if pre-managed earnings
(operating cash flow) is less than zero (EARN
tÀ1
) and zero otherwise.
HIGH is an indicator variable taking the value of one if pre-managed earnings
(operating cash flow) is well above zero (EARN

tÀ1
) and zero otherwise.
OUT is the number o f outside b oar d me mbers d ivided by the total number of board
member s.
AC is an indicator variable taking the value of one if an audit committee exists and zero
otherwise.
OWN is an indicator variable taking the value of one if managerial ownership
(BRDOWN) is less than 5% and zero otherwise.
Control variables are as specified (but excluding BRDOWN) and defined in Table 3.
BOARD MONITORING AND EARNINGS MANAGEMENT
1335
#
Blackwell Publishing Ltd 2005