audit committee quality, auditor independence, and internal control weaknesses
DESCRIPTION
Yan Zhang, Jian Zhou, and Nan ZhouTRANSCRIPT
Audit Committee Quality, Auditor Independence, and
Internal Control Weaknesses
Yan Zhang, Jian Zhou, and Nan Zhou*
* All authors are from SUNY – Binghamton. We thank two anonymous reviewers for detailed and insightful suggestions that have significantly improved the paper. We also thank workshop participants at the 2006 American Accounting Association Auditing Midyear Meeting and the 2006 American Accounting Association Annual Meeting for comments, and Raj Addepalli, Shanshan Chen, Yujing Pan, Gaurav Rastogi, Eric Romanoff, Grace Witte, and Meng Zhao for research assistance. Please address all correspondence to Jian Zhou, School of Management, SUNY – Binghamton, Binghamton, NY 13902-6000; email: [email protected]; phone: (607) 777 6067.
Audit Committee Quality, Auditor Independence, and Internal Control Weaknesses
Abstract
In this paper we investigate the relation between audit committee quality, auditor independence, and the disclosure of internal control weaknesses after the enactment of the Sarbanes-Oxley Act. We begin with a sample of firms with internal control weaknesses and, based on industry, size, and performance, match these firms to a sample of control firms without internal control weaknesses. Our conditional logit analyses indicate that a relation exists between audit committee quality, auditor independence, and internal control weaknesses. Firms are more likely to be identified with an internal control weakness, if their audit committees have less financial expertise or, more specifically, have both less accounting financial expertise and non-accounting financial expertise. They are also more likely to be identified with an internal control weakness, if their auditors are more independent. In addition, firms with recent auditor changes are more likely to have internal control weaknesses.
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Audit Committee Quality, Auditor Independence, and Internal Control Weaknesses
1. Introduction
The Sarbanes-Oxley Act (hereafter SOX) of 2002 went into effect on July 30,
2002 to address the increasing concern of investors about the integrity of firms’ financial
reporting, due to scandals involving once well-respected companies, such as Enron and
WorldCom and auditors, such as Arthur Andersen. One important aspect of SOX is that
it has two sections specifically focusing on internal control issues related to financial
reporting. Under Section 302, management is required to disclose all material
weaknesses in internal control, when they certify the periodic, annual, and quarterly
statutory financial reports. Under Section 404, a firm is required to assess the
effectiveness of its internal control structure and procedures for financial reporting and
disclose such information in its annual reports. Furthermore, the firm’s auditor is required
to provide an opinion on the assessment made by the management in the same report.
Because such mandatory disclosure under SOX provides us with more information on
internal controls, we are interested in investigating the determinants of internal control
weaknesses in the post-SOX era.
We begin with a sample of firms with internal control weaknesses, and, based on
industry, size, and performance, match these firms to a sample of control firms without
internal control weaknesses. Our conditional logit analyses indicate that a relation exists
between audit committee quality, auditor independence, and internal control weaknesses.
Firms are more likely to be identified with an internal control weakness, if their audit
committees have less financial expertise or, more specifically, have less accounting
financial expertise and non-accounting financial expertise. They are also more likely to
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be identified with an internal control weakness, if their auditors are more independent. In
addition, firms with recent auditor changes are more likely to have internal control
weaknesses.
Our paper is related to several recent papers on the determinants of internal
control weaknesses. Krishnan (2005) examines the period prior to the enactment of
SOX, when internal control problems are only disclosed in 8-Ks filed by firms when
changing auditors. With information collected from 8-K filings, she finds that
independent audit committees and audit committees with more financial expertise are
significantly less likely to be associated with the incidence of internal control problems.
Ge and McVay (2005) and Doyle et al. (2006a) find that material weaknesses in internal
control are more likely for firms that are smaller, less profitable, more complex, growing
rapidly, or undergoing restructuring. Ashbaugh-Skaife et al. (2006) find that firms with
more complex operations, recent changes in organization structure, auditor resignation in
the previous year, more accounting risk exposure, and less investment in internal control
systems are more likely to disclose internal control deficiencies.
We document that financial expertise in audit committees continues to be an
important determinant of internal control weaknesses after the enactment of SOX. Our
findings thus complement those in Krishnan (2005), who studies the pre-SOX period.
Focusing on the post-SOX period enables us to take advantage of the wealth of
information on internal control unleashed by SOX and to construct a sample of firms with
internal control problems from both mandated disclosures in the firms’ 10-Q and 10-K
filings under SOX and information disclosed in 8-K filings when firms change auditors.
Consisting of only those firms that change auditors in the pre-SOX period, the sample
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firms in Krishnan (2005) tend to be smaller in size and are traded on smaller stock
exchanges. We avoid this sample selection bias by focusing on the post-SOX period,
given that all firms are required to disclose material internal control weaknesses under
SOX. In addition, we document that auditor independence is an important determinant of
internal control weaknesses. This adds to the literature that supports the hypothesis that
auditor independence matters, such as Frankel et al. (2002) and Krishnamurthy et al.
(2006). Different from other researchers who also focus on the post-SOX period, such as
Ge and McVay (2005), Doyle et al. (2006a) and Ashbaugh-Skaife et al. (2006), we show
that audit committee quality, characterized as having more financial expertise or, more
specifically, having more accounting financial expertise and non-accounting financial
expertise, is an important determinant of internal control weaknesses. In addition, we
find that auditor independence, calculated as the ratio of audit fee to total fee, is also a
determinant of internal control weaknesses.
The rest of the paper is organized as follows. Section 2 introduces the
background and proposes our hypotheses. Section 3 describes the sample selection
procedures. Section 4 discusses the empirical findings, and Section 5 presents our
conclusions.
2. Background and hypotheses
2.1. Background
SOX emphasizes internal control, which is defined as “a process, effected by an
entity's board of directors, management and other personnel, designed to provide
reasonable assurance regarding the achievement of objectives”, according to the COSO
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framework.1 SOX Section 302 (hereafter SOX 302), which went into effect on August
29, 2002, requires management to disclose significant internal control deficiencies, when
they certify annual or quarterly financial statements. Specifically, the signing officers,
being responsible for internal controls, have evaluated the internal controls within the
previous ninety days and reported in their findings: (1) a list of all deficiencies in the
internal controls and information on any fraud that involves employees who are involved
with internal control activities; (2) any significant changes in internal controls or related
factors that could have a negative impact on the internal controls.
Section 404 took this reporting a step further. It not only requires management to
provide an assessment of internal controls, but also requires auditors to provide an
opinion on management’s assessment. Specifically, issuers are required to disclose
information concerning the scope and adequacy of the internal control structure and
procedures for financial reporting in their annual reports. This statement shall also assess
the effectiveness of such internal controls and procedures. The registered auditing firm
shall, in the same report, attest to and report on the effectiveness of the internal control
structure and procedures for financial reporting. According to the rulings of the
Securities Exchange Commission (SEC), a company that is an “accelerated filer”2 must
comply with SOX Section 404 (hereafter SOX 404) for its first fiscal year ending on or
after November 15, 2004. A non-accelerated filer must begin to comply with these
requirements for its first fiscal year ending on or after July 15, 2007. A foreign private
1 COSO stands for the Committee of Sponsoring Organizations of the Treadway Commission, who undertook an extensive study of internal control to establish a common definition that would serve the needs of companies, independent public accountants, legislators, and regulatory agencies and to provide a broad framework of criteria, against which companies could evaluate the effectiveness of their internal control systems. COSO published its Internal Control -- Integrated Framework in 1992. 2 An “accelerated filer” is defined in Exchange Act Rule 12b-2. Generally, it refers to a U.S. company that has equity market capitalization over $75 million and has filed an annual report with the SEC.
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issuer that files its annual report on Form 20-F or Form 40-F must begin to comply with
the corresponding requirements in these forms for its first fiscal year ending on or after
July 15, 2006.3
According to Compliance Week, most of the internal control weakness disclosures
under SOX 302 and SOX 404 are related to financial systems and procedures. This
group typically involves financial closing processes, account reconciliation, or inventory
processes. For example, United Stationers disclosed problems with “the design and
effectiveness of internal controls relating to receivables from suppliers”. Personnel issues
rank as the second largest category of weakness disclosures. This category is related to
the poor segregation of duties, inadequate staffing, or other related training or supervision
problems. For example, Sanmina-SCI cited a “lack of sufficient personnel with
appropriate qualifications and training in certain key accounting roles.” Other common
types of weaknesses include revenue recognition, documentation, and IT system and
controls (e.g. security and access controls, backup and recovery issues). In addition,
issues related to international operations and mergers and acquisitions are sources of
weakness disclosure, although they represent a relatively small percentage of all
disclosures. For example, Masco cited internal control problems attributable to
“historical growth through acquisition and decentralized organizational structure,” and
GulfMark Offshore identified internal control deficiencies related to the complexity of
their multi-national operations.
Based on their severity, these internal control problems are classified into three
types: material weakness, significant deficiency, and control deficiency. Auditing
3 The SOX compliance information is from www.sec.gov, and the SOX summaries are from www.soxlaw.com.
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Standard (hereafter AS) No. 2 defines a material weakness as “a significant deficiency, or
combination of significant deficiencies, that results in more than a remote likelihood that
a material misstatement of the annual or interim financial statements will not be
prevented or detected.” Under AS No.2, a significant deficiency is “a control deficiency,
or a combination of control deficiencies, that adversely affects the company’s ability to
initiate, authorize, record, process, or report external financial data reliably in accordance
with genernally accepted accounting principles such that there is more than a remote
likelihood that a misstatement of the company’s annual or interim financial statements
that is more than inconsequential will not be prevented or detected.” A control deficiency
occurs “when the design or operation of a control does not allow management or
employees, in the normal course of performing their assigned functions, to prevent or
detect misstatement on a timely basis.” Since only material weaknesses are required to
be publicly disclosed under SOX 302 and SOX 404, we follow Doyle, Ge, and McVay
(2006a; 2006b), and focus on firms that disclosed material weaknesses in our study.4 For
the sake of brevity, we will refer to material internal control weaknesses as internal
control weaknesses hereafter.
2.2. Audit committee quality and internal control
Since an entity’s internal control is under the purview of its audit committee
(Krishnan, 2005), we investigate the relation between audit committee quality and
internal control weaknesses. The audit committee not only plays an important
monitoring role to assure the quality of financial reporting and corporate accountability
4 This is also driven by the fact that Compliance Week lists only firms with material weaknesses starting March 2005.
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(Carcello and Neal, 2000), but also serves as an important governance mechanism,
because the potential litigation risk and reputation impairment faced by audit committee
members ensure that these audit committee members discharge their responsibilities
effectively. We thus expect that firms with high-quality audit committees are less likely
to have internal control weaknesses than firms with low-quality audit committees.
On measuring audit committee quality, we focus on the financial expertise in
these committees. The Blue Ribbon Committee on Improving the Effectiveness of
Corporate Audit Committees (BRC)’s (1999) recommendation that each audit committee
should have at least one financial expert highlights the importance of the financial
literacy and expertise of audit committee members.5 Section 407 of the SOX
incorporates the above suggestion and requires firms to disclose in periodic reports,
whether a financial expert serves on a firm’s audit committee and, if not, why not. Such
financial expertise of audit committee members has been shown to be important for
dealing with the complexities of financial reporting (Kalbers and Fogarty, 1993) and for
reducing the occurrence of financial restatements (Abbott et al., 2004). In addition,
DeZoort and Salterio (2001) find that audit committee members with financial reporting
and auditing knowledge are more likely to understand auditor judgments and support the
auditor in auditor-management disputes than members without such knowledge.
Moreover, financially knowledgeable members are more likely to address and detect
material misstatements. Audit committee members with financial expertise can also
5 The Report of the BRC’s recommendation related to Audit Committee Competence states that “the audit committee should consist of at least three members, each of whom is "independent" (defined in the Report as having "no relationship to the corporation that may interfere with the exercise of their independence from management and the corporation") and "financially literate" (defined as "the ability to read and understand fundamental financial statements"). At least one member of the audit committee should have accounting or financial management expertise (defined as past employment or professional certification in accounting or finance, or comparable experience including service as a corporate officer with financial oversight responsibility)”.
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perform their oversight roles in the financial reporting process more effectively, such as
detecting material misstatements (Scarbrough et al., 1998; Raghunandan et al., 2001).
Indeed, Abbott et al. (2004) find a significantly negative association between an audit
committee having at least one member with financial expertise and the incidence of
financial restatement. Krishnan (2005) presents evidence that audit committees with
financial expertise are less likely to be associated with the incidence of internal control
problems. Therefore, we have the following directional prediction.
Hypothesis 1: Firms with greater audit committee financial expertise are less likely to
have internal control weaknesses.
DeFond et al. (2005) document significantly positive cumulative abnormal returns
around the appointment of accounting financial experts to the audit committee,
suggesting that audit committees with accounting financial expertise improve corporate
governance. Therefore, we further separate audit committee financial expertise into
accounting financial expertise and non-accounting financial expertise and test the relation
between these two variables and internal control weaknesses.
In measuring the financial expertise of an audit committee member, we follow the
definition adopted in SOX Section 407, and, more specifically, modify the definition
used in DeFond et al. (2005). An audit committee member is a financial expert if he or
she can be classified into the following two categories: (a) an accounting financial expert
who has experience as a public accountant, auditor, principal or chief financial officer,
controller, or principal or chief accounting officer; or (b) a non-accounting financial
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expert who has experience as the chief executive officer, president, or chairman of the
board in a for-profit corporation, or who has experience as the managing director, partner
or principal in venture financing, investment banking, or money management. With this
definition, we measure audit committee financial expertise (ACFE) as the percentage of
audit committee members who are financial experts. We further separate audit
committee financial expertise into accounting financial expertise (ACCT_ACFE),
measured as the percentage of audit committee members who are accounting financial
experts, and non-accounting financial expertise (NONACCT_ACFE), the percentage of
audit committee members who are non-accounting financial experts.
2.3. Auditor independence and internal control
Auditor independence can be related to the disclosure of a firm’s internal control
problems. When there is a strong economic bond between an auditor and a client firm,
the auditor has an incentive to ignore potential problems and issue a clean opinion on the
client firm’s internal controls. While some studies (DeFond et al., 2002; Ashbaugh et al.,
2003; Chung and Kallapur, 2003; Reynolds et al., 2002; Francis and Ke, 2003) find no
relation between non-audit fees and auditor independence and argue that an auditor’s
concern with maintaining its reputation for providing high quality audits could restrain it
from undertaking activities that jeopardize independence, since the revenue from each
client will be a small percentage of the auditor’s total revenue, other studies suggest that
the provision of non-audit services compromises auditor independence. For example,
Frankel et al. (2002) find that non-audit services are associated with increased discretionary
accruals and the achievement of certain earnings benchmarks and Krishnamurthy et al.
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(2006) document that the abnormal returns for Andersen’s clients around Andersen’s
indictment are significantly more negative, when the market perceived the auditor’s
independence to be compromised. Given these mixed empirical findings, we measure
auditor independence (RATIO) as the ratio of the audit fee to the total fee, and propose
the non-directional null hypothesis, as follows.
Hypothesis 2: Auditor independence is not associated with the disclosure of internal
control weaknesses.
2.4. Control variables
2.4.1. Audit committee
In addition to audit committee financial expertise, other attributes of an audit
committee have been found to be important factors in effective monitoring. Specifically,
we control for audit committee independence, since Krishnan (2005) finds that there is a
positive relation between audit committee independence and the quality of internal
control prior to the enactment of SOX.6 While SOX requires that audit committees be
composed of all independent directors for firms traded on an organized stock exchange
(e.g., NYSE, AMEX) or a recognized dealer quotation system (e.g., NASDAQ),
exemptions may be given by the SEC, if it determines that it is appropriate under certain
circumstances. We thus still control for audit committee independence (ACIND), defined
as the percentage of independent directors on the audit committee. Under SOX, an audit
committee member is independent, if he or she is not affiliated with the firm and does not
6 Previous research has also found an association between audit committee independence and the quality of accounting information (e.g., Klein, 2002b; Abbott et. al., 2004).
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accept any consulting fees.
We next control for the natural logarithm of audit committee size (ACSZ),
measured as the number of audit committee members, because research suggests that a
large audit committee tends to enhance the audit committee’s status and power within an
organization (Kalbers and Fogarty, 1993), to receive more resources (Pincus et al., 1989),
and to lower the cost of debt financing (Anderson et al., 2004). We thus expect that a
large audit committee is more likely than a small one to improve the quality of internal
controls, because increased resources and enhanced status will make the audit committee
more effective in fulfilling its monitoring role.
We also control for the natural logarithm of audit committee meetings
(ACMEET), measured as the number of audit committee meetings held each year,
because research shows that effective audit committees meet regularly (Menon and
Williams, 1994; Xie et al., 2003).7 Consistent with this hypothesis, McMullen and
Raghunandan (1996) find that the audit committees of firms with SEC enforcement
actions or earnings restatements are less likely to have frequent meetings than those
without and Lennox (2002) finds that there is a significant increase in the number of audit
committee meetings during an auditor dismissal year. However, it is also possible that an
audit committee meets more frequently to discuss internal control issues, when there are
significant problems associated with a firm’s internal controls. Therefore, we make no
prediction on the relation between the number of audit committee meetings and the
quality of internal controls.
7 Hymowitz and Lublin (2003) report that “many audit committees are spending far more time than they used to reviewing financial statements and overseeing auditors, meeting 10 or 11 times a year, up from three or four times.”
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2.4.2. Board of directors
The quality of an entity’s internal controls is a function of the quality of its
control environment that includes the board of directors and the audit committee
(Krishnan, 2005). First, we focus on board independence (BDIND), measured as the
percentage of outside directors on the board,8 because research suggests that board
independence is negatively related to the likelihood of financial fraud and SEC
enforcement actions (Beasley, 1996; Dechow et al., 1996). We also control for the
natural logarithm of board size (BDSZ), measured as the number of directors on the
board. While some researchers find that a large board has more expertise than a small
one (Dalton et al., 1999), that it tends to be more effective in monitoring accruals (Xie et
al., 2003), and that it leads to a lower cost of debt (Anderson et al., 2004). Others suggest
that a small board is more effective in mitigating the agency costs associated with a large
board (Yermack, 1996; Eisenberg et al., 1998; Hermalin and Weisbach, 1998, 2003).
Given the mixed empirical evidence on board size, we expect that the relation between
board size and the likelihood of internal control weaknesses is indeterminate. Finally, we
control for the natural logarithm of board meetings (BDMEET), as measured by the
number of board meetings held each year. While Conger et al. (1998) suggest that board
meeting frequency is important to improve board effectiveness, Vafeas (1999) finds that
it is inversely related to firm value, because of the increased board activities following
share price declines. Since board independence, size, and meeting frequency all
influence a board’s effectiveness, they, in turn, are related to the quality of internal
controls.
8 Outside directors are those who are not affiliated with the firm, other than serving on its board. We first exclude those directors who are the firm’s officers and major shareholders, and then further exclude those who have consulting relationships or other related-party transactions with the firm.
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2.4.3. Auditor Types
We use a dummy variable (BIG4) to measure auditor type,9 because a firm’s
decision to hire a Big 4 auditor is likely to be associated with internal controls for several
reasons. Doyle et al. (2006a) find that smaller and less profitable firms are more likely to
have internal control problems than larger or more profitable ones. On the one hand,
such firms with internal control problems are less likely to hire a Big 4 auditor, because
they are constrained by financial resources and cannot afford it. On the other hand, they
might also be avoided by the Big 4 auditors, because they are perceived as being risky
and may expose the Big 4 to potential litigations. Given that a firm shunned by a Big 4
auditor may signal that it has potential internal control problems, we introduce the
dummy variable BIG4 to control for auditor quality.
2.4.4. Auditor Changes
Ashbaugh-Skaife et al. (2006) find that firms with recent auditor changes are
likely to have internal control problems. On the one hand, auditors may drop risky
clients as part of their risk management strategies, since firms with material internal
control weaknesses may represent high audit failure risk. On the other hand, firms may
dismiss auditors for lack of performance, when the firms discover material internal
control weaknesses. Therefore, we use a control variable AUDCHG, which is equal to
one, if there is an auditor change in 2003 or 2004, and zero otherwise.
2.4.5. Other variables
9 The dummy variable (BIG4) takes a value of one, if a firm is a Big 4 client and zero otherwise.
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We also control for firm characteristics that may be associated with internal control
problems. Since Doyle et al. (2006a) show that small and high growth firms are likely to
have internal control weaknesses, in our model, we control for size, measured as the
natural logarithm of total assets (TA), and growth, measured as industry-median-adjusted
sales growth (ADJSALEGR). It may take some time for a firm that recently engaged in
mergers and acquisition to integrate different internal control systems; consequently, such
a firm is more likely to have internal control problems. We thus introduce a dummy
variable (ACQUISITION), which takes the value of one, if a firm engages in acquisitions
during 2003, 2004 and from January to July of 2005, and zero otherwise. Since a firm
experiencing restructuring is also likely to have internal control problems, because of the
loss of experienced and valuable employees and because of the dramatic changes
associated with such an event, we follow Ashbaugh-Skaife et al. (2006) and use a dummy
variable (RESTRUCTURE), coded as one, if a firm has been involved in restructuring,
and zero otherwise.10 Because firms with greater complexity and scope of operations are
more likely to have internal control problems than those without, we also include the
natural logarithm of the number of business segments (BUS) and an indicator variable for
foreign currency translation (FOREIGN) in our model (see Ashbaugh-Skaife et al., 2006;
Ge and McVay, 2005).
3. Sample and control firms selection
3.1. Selection of sample firms
10 A firm is engaged in a restructuring, if it has non-zero values of COMPUSTAT data #376, #377, #378, or #379.
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Table 1 provides the details for the sample selection. Our initial sample is from
Compliance Week, an electronic newsletter that searchs through 8-Ks, 10-Qs, and 10-Ks
for all public companies to identify any firms with internal control problems. While
Compliance Week discloses firms with internal control problems on a monthly basis
starting from November 2003, we examine the period from November 15, 2004 to July
31, 2005, so as to make it feasible to hand-collect most of the governance information
required in our study.11 For our sample period, there are 372 firms identified by
Compliance Week as having various types of internal control problems under SOX 302 or
SOX 404, 12 including material weakness, significant deficiency, reportable conditions,
and control deficiency. 13 We exclude ten firms without Cusip numbers, nine firms not in
COMPUSTAT, 13 foreign firms or subsidiaries, 57 firms with missing values for
EBITDA profit margin,14 54 non-material weakness firms,15 and 21 firms without proxy
information. This leaves us with a final sample of 208 firms with material internal
control weaknesses. We retrieve all financial information from 2004 COMPUSTAT,
obtain the acquisition information from Securities Data Company, acquire the business
segment information from COMPUSTAT Segment files, and hand-collect all audit and
non-audit fee, audit committee, and board information from the firms’ proxy statements
for the year of their material weakness disclosure in Compliance Week.
11 We start from November 15, 2004, given that there is increasing attention to internal control issues, since SOX 404 became effective for accelerated filers. 12 We exclude 31 duplicate appearances during the sample period. 13“Reportable conditions” is an old term, which was defined by AICPA as “a significant deficiency in the design or operation of the internal control structure that could adversely affect the company’s ability to record, process, summarize, and report financial data consistent with the assertions of management in the financial statements.” Compliance Week lists some of the early firms under this term. 14 We include this filter because our match firms are selected based on sales and EBITDA profit margin (EBITDA/sales). If a firm has a missing value for sales, it will also have a missing value for EBITDA profit margin. 15 These firms are identified as having significant deficiencies, control deficiencies, or reportable conditions. Starting from March 2005, Compliance Week lists only firms with material weaknesses.
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3.2. Control firms’ selection
To study the determinants of internal control weaknesses, we use the matched-
pairs design. Although using matched samples when the number of treatment firms is not
proportional to sample population may lead to biased parameters and probability
estimates (Palepu, 1986), we adopt this approach to make it feasible for us to hand-collect
audit committee and board information from the proxy statements. The 208 control firms
without internal control weaknesses are matched to the 208 sample firms with internal
control weaknesses, one-to-one, based on certain key characteristics. Specifically, we
follow Purnanandam and Swaminathan (2004), who use selected publicly traded firms in
the same industry as comparable firms.16 Since their procedure balances between
matching based on industry or sales, which can be too approximate, and matching based
on a list of accounting variables, which can be so numerous that it becomes impossible to
find match firms, we adapt their procedure to create our sample of match firms. The
procedure is described as follows:
(1) We select all firms in 2004 COMPUSTAT. From these firms, we eliminate
subsidiaries and require firms to be incorporated in the U.S. We further require
them to have information on CRSP, and be identified as common stocks of
domestic U.S. firms (CRSP share code = 10 or 11).
(2) We use COMPUSTAT SIC codes to group the remaining firms into 48
industries using the industry classification in Fama and French (1997).
(3) The remaining firms in each industry are sorted into three portfolios by sales,
and then each sales portfolio is sorted into three portfolios by EBITDA profit
margin (EBITDA/sales), where EBITDA stands for earnings before interest,
16 Guo, Lev, and Zhou (2005) adapt this procedure to study the relative valuation of biotech IPOs.
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taxes, depreciation, and amortization. As a result, we have 9 (3x3) portfolios of
comparable firms in each industry. If there are not enough firms in an industry
(fewer than 70 firms), we limit ourselves to a 2x2 classification, which leads to 4
portfolios of comparable firms in that industry.
(4) We obtain sales and EBITDA margin for our sample firms from the 2004
COMPUSTAT and also classify them into different industries, according to the
Fama-French industry classification. Each sample firm is matched with a
portfolio of comparable firms based on industry, sales and EBITDA margin. In
that portfolio, one firm with the closest total sales is selected as the match firm. If
the match firm does not file a proxy or have sufficient information in proxy or has
internal control weaknesses, we replace it with a non-weakness firm from the
same portfolio that has the next closest total sales.17
Following the same procedure as for the sample firms, we obtain all the
information from COMPUSTAT and proxy statements for our control firms. Table 2
provides summary statistics for our sample firms and control firms. While the mean
(median) sales for sample firms is $2701.43 million ($375.02 million), the mean
(median) sales for match firms is $1745.72 million ($365.11 million). While the mean
(median) EBITDA profit margin for sample firms is –0.14 (0.11), the mean (median)
EBITDA profit margin for match firms is –0.45 (0.11). The large difference in the mean
comparison of sales is driven by General Electric (GE), which has substantially larger
sales than its closest match firm has. Without GE and its match firm, the mean (median)
sales for the sample and control will be 1983.57 million (372.50 million) and 1742.15 17 We check the Compliance Week list and 10-Ks to ensure that a match firm does not have internal control weaknesses. A match firm is replaced, if it appears on the Compliance Week list from November 2003 to July 2005 or is flagged with internal control weaknesses in its 10-K filed prior to July 2005.
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million (364.18 million), respectively.18 If we exclude GE and its match firm, sample
and control firms share similar characteristics in terms of sales and EBITDA profit
margin, since our selection procedure for match firms is based on these two variables.
4. Empirical results
4.1. Univariate analyses
Table 2 provides mean and median comparisons of the sample and control firms
for our variables of interest. Because our sample firms are matched with control firms on
a one-to-one basis, we use the paired t-test to test the difference in means and the
Wilcoxon signed rank test to test the difference in medians.19 There are several
noticeable differences between these two groups of firms. On average, 75 percent of the
audit committee members of the sample firms are financial experts, while 83 percent of
the audit committee members of the control firms are financial experts. This difference,
significant at the one-percent level, implies that firms with more audit committee
financial expertise are less likely to have internal control problems, providing initial
support for Hypothesis 1. We further separate audit committee financial experts into
accounting financial experts and non-accounting financial experts. On average,
accounting financial experts account for 22 percent of the sample firms’ and 23 percent
of the control firms’ audit committee members, while non-accounting financial experts
account for 53 percent of the sample firms’ and 59 percent of the control firms’ audit
committee members. The difference in non-accounting financial expertise between the
two groups is significant at the five-percent level.
18 We find that our main results in Table 4 remain unchanged, when we exclude GE and its match firm in our conditional logit regressions. 19 The Wilcoxon signed rank test is the nonparametric analog of the paired t-test.
19
We use the ratio of audit fee to total fee to measure auditor independence, where a
low ratio indicates that the firm’s auditor provides more non-audit services and thus lacks
independence. The average audit fee ratios are 78 percent for the sample firms and 75
percent for the control firms. This significant difference indicates that independent
auditors are more likely to uncover internal control problems, providing initial support
for Hypothesis 2. In addition, the sample firms have more audit committee and board
meetings, on average, probably in response to the sample firms’ internal control
problems. Firms that have changed auditors or engaged in restructuring activities
recently are also more likely to experience internal control weaknesses.
Table 3 presents the correlation coefficients for the dependent and independent
variables after we pool the sample and control firms together. We create a dummy for
internal control weaknesses (ICW), which takes the value of one if a firm belongs to the
sample firm group, and zero if it belongs to the control firm group. This dependent
variable of interest is significantly negatively correlated with audit committee financial
expertise, indicating that firms with greater audit committee financial expertise are less
likely to have internal control weaknesses. Moreover, it is significantly positively
correlated with the audit fee ratio, indicating that firms with more independent auditors
are more likely to uncover internal control weaknesses. These results again provide
preliminary support for Hypotheses 1 and 2. In addition, the internal control weakness
dummy variable is positively correlated with the natural logarithms of audit committee
meeting frequency and board meeting frequency. Thus, the audit committee and board of
a firm with internal control weaknesses appear to hold additional meetings, dealing with
the firm’s internal control problems. Further, the internal control weakness dummy is
20
positively correlated to the variables for audit change and restructuring, suggesting that
firms with recent auditor changes or restructuring activities are more likely to have
internal control weaknesses.
4.2. Multivariate analyses
4.2.1. Conditional logit regression models
We use the conditional logit regression models to test our hypotheses that audit
committee financial expertise and auditor independence are related to internal control
weaknesses. Specifically, we express the internal control weakness variable as a function of
audit committee quality, auditor independence, and a set of control variables.
The conditional logistic regression is useful in investigating the relation between
an outcome (whether the firm is a sample firm with internal control weaknesses or a
control firm without such weaknesses) and a set of prognostic factors in a matched-pairs
study. We match control firms to sample firms to minimize inherent variations in those
factors. Because the traditional logistic regression cannot take into account the
correlation structure of a matched design, we analyze our matched sample-control study
using the conditional logistic regression that takes into account the non-random nature of
the data. For each matched set consisting of one sample firm and one control firm, the
conditional likelihood is as follows:
1
01
')))(exp(1( −−−+∏ ii
i
xxβ
where 1ix and 0ix are vectors of the prognostic factors for the sample and control firm,
respectively, of each ith matched set (Breslow, 1982; Hosmer and Lemeshow, 2000).
21
4.2.2. Conditional logit regression results
Tables 4 and 5 present the regression results using conditional logit analyses. All
variable definitions are provided in the Appendix. Table 4 presents four models with
different measures of audit committee quality. Models 1 and 2 use audit committee financial
expertise (ACFE) to measure audit committee quality. Klein (2002a) finds that the main
determinant of audit committee independence is board independence, and thus audit
committee characteristics and board characteristics are highly correlated. In order to avoid
multicollinearity, we introduce only audit committee characteristics (ACIND, LOG(ACSZ),
and LOG(ACMEET)), along with audit fee ratio (RATIO), in Model 1.20 We further control
for auditor type (BIG4), auditor change (AUDCHG), size (LOG(TA)), growth
(ADJSALEGR), acquisition (ACQUISTION), restructuring (RESTRUCTURE), segments
(LOG(BUS)), and foreign currency translation (FOREIGN). 21 The coefficient on ACFE is
significant at the one-percent level, and the coefficient on RATIO is significant at the five-
percent level. This supports Hypothesis 1 and rejects the null of Hypothesis 2. Our evidence
suggests that firms are more likely to be identified with an internal control weakness, if their
audit committees have less financial expertise or their auditors are more independent.
However, our result on auditor independence should be interpreted with caution, as there is
an alternative explanation for this positive coefficient on RATIO. Clients that purchase fewer
non-audit services may have fewer discretionary resources. This lack of discretionary
resources may lead to a lack of investment in internal controls, resulting in internal control
20 Following Klein (2002a), we take the natural logarithms of ACSZ, ACMEET, BDSZ, and BDMEET. Our results remain unchanged, if we use the raw variables. 21 In an early version of Doyle et al. (2006a), restructuring is measured as special items (#17) divided by lagged total assets (#6). We replace RESTRUCTURE with this measure in Models 1 and 2 of Table 4 and find that our results remain unchanged. We also measure size as log of total assets (#6) and find that our results in Table 4 remain unaltered.
22
weaknesses. In addition, the coefficient on AUDCHG is significant at the one-percent level
and the coefficient on RESTRUCTURE is significant at the ten-percent level. Consistent
with Doyle et al. (2006a) and Ashbaugh-Skaife et al. (2006), our findings imply that firms
with recent auditor changes or restructuring activities are more likely to have internal control
weaknesses. Finally, it is worth noting that a few of the insignificant results, noticeably the
one on size, might be due to the matched sample design used in this study.
In Model 2, we add board characteristics (BDIND, LOG(BDSZ), and
LOG(BDMEET)) to Model 1, and find that our results on ACFE, RATIO, AUDCHG and
RESTRUCTURE remain unchanged. Moreover, firms with a large board are less likely to
have internal control weaknesses. Klein (2002a) finds that board size is positively associated
with audit committee independence, implying that firms with a large board are more likely to
have effective audit committees and thus are more likely to demand high quality auditing
services. Thus, our finding on board size is consistent with that in Klein (2002a). Finally,
board meeting frequency is found to be positively related to internal control weaknesses.
Therefore, firms with internal control weaknesses are more likely to hold additional
meetings, dealing with their internal control problems. We do not find the relation between
audit committee independence and internal control weaknesses in Models 1 and 2, as does
Krishnan (2005), because SOX requires audit committees to be composed of all independent
board members.
Models 3 and 4 replicate Models 1 and 2 by replacing ACFE with two separate
measures: accounting financial expertise (ACCT_ ACFE) and non-accounting financial
expertise (NONACCT_ACFE). The coefficients on ACC_ ACFE and NONACCT_ ACFE
are all significant at the one-percent level, suggesting that both accounting and non-
23
accounting financial experts are helpful in improving internal controls. Other results are
similar to those reported for Models 1 and 2. Thus, our findings are robust to different ways
of measuring audit committee financial expertise.
Some board variables, namely board size and board meeting frequency, are found
to be related to internal control weaknesses in Table 4. This suggests that firms with
strong corporate governance may be less likely to have internal control problems. As a
natural extension to Table 4, we control for corporate governance in Table 5.
Specifically, we use the overall measure of corporate governance developed in DeFond et
al. (2005, pp. 168-170). They capture the strength of the governance environment using a
summary measure that combines the following six governance characteristics into a
single dichotomous variable: board size, board independence, audit committee size, audit
committee independence, shareholders’ rights as captured by the G index used in
Gompers, Ishii, and Metrick (2003), and institutional ownership. Because the G index
information is only available for 52 pairs of our sample and control firms,22 we adapt the
procedure in DeFond et al. (2005) and create our governance variable (GOVERN) based
on the following dichotomous measures of the five governance characteristics for each
firm.
1) Board size — We code firms 1 (for strong governance), if the firm’s board
size is less than the sample median and 0, otherwise.
22 When we run regressions based on these 52 pairs for Models in Table 5, we have one-tailed significance at the ten-percent level for the coefficient on audit committee financial expertise in Model 1 and the coefficient on non-accounting financial expertise in Model 2, respectively.
24
2) Board independence — We code firms 1 (for strong governance), if 60%
or more of the directors are independent and 0, otherwise.
3) Audit committee size — We code firms 1, if the proportion of the firm’s
audit committee size to its full board size is greater than the sample
median and 0, otherwise.
4) Audit committee independence — We code firms 1, if the committee is
composed only of independent members and 0, if the committee includes
at least one affiliated member.
5) Institutional ownership — We code firms 1, if the firm’s percentage of
institutional ownership is greater than the sample median and 0,
otherwise.23
We first summarize the five dichotomous measures for each firm and then create a
dichotomous variable based on the median of the summed values. This governance
measure is equal to one, indicating strong governance, if it is equal to or greater than the
median summed values and zero, otherwise. Note that the number of observations for
Table 5 is 206 pairs or 412 firms, because the institutional ownership information is
missing for two pairs.
Table 5 presents the empirical results after controlling for the above summarized
measure of corporate governance (GOVERN). Note that we no longer include ACIND,
ACSZ, BDIND, and BDSZ in our models, because these variables are incorporated into
GOVERN. The findings in Table 5 are very similar to those in Table 4. To measure
23 We retrieve the institutional ownership information from Compact D and supplement thirteen firms that have missing ownership data with information collected from Yahoo! Finance. Our results in Table 5 are unchanged, when these thirteen firms are excluded from our analyses.
25
audit committee quality, we use ACFE in Model 1, and ACCT_ACFE and
NONACCT_ACFE in Model 2. The coefficients on these variables are all significant at
the one-percent level, whereas the coefficient on GOVERN is not significant. After we
control the influence of corporate governance, the relation between audit committee
quality and internal control weaknesses still holds. In addition, the coefficients on
RATIO and AUDCHG are significant at the five-percent level or better. Thus, auditor
independence and auditor change continue to be positively associated with the disclosure
of internal control weaknesses.
4.2.3. Robustness checks
We perform the following additional tests to verify that our results in Tables 4 and 5
are robust.
(1) We use the natural logarithm of sales or market value of equity instead of the
natural logarithm of total assets.24
(2) We use the acquisition value defined in Doyle et al. (2006a), instead of the
acquisition dummy.
(3) We use raw ACSZ, ACMEET, BDSZ, and ACMEET, instead of the natural
logarithms of these variables.
In all these cases, our results are robust to these alternative specifications, adding
credence to our findings.
5. Conclusion
24 Because of missing information, there are only 206 pairs or 412 firms, when we use the market value of equity.
26
In this paper, we examine the relation between audit committee quality, auditor
independence, and disclosure of internal control weakness after the enactment of the
Sarbanes-Oxley Act. We begin with a sample of firms with internal control weaknesses
and, based on industry, size, and performance, match these firms to a sample of control
firms without internal control weaknesses. The results from our conditional logit
analyses suggest that a relation exists between audit committee quality, auditor
independence, and internal control weaknesses. Firms are more likely to be identified
with an internal control weakness, if their audit committees have less financial expertise
or, more specifically, have less accounting financial expertise and non-accounting
financial expertise, as well. They are also more likely to be identified with an internal
control weakness, if their auditors are more independent. In addition, firms with recent
auditor changes are more likely to have internal control weaknesses.
27
Appendix
Variable Definitions
ICW: 1, if a firm is identified with a material internal control weakness; 0, otherwise
ACFE: Percentage of audit committee members who are financial experts ACCT_ACFE: Percentage of audit committee members who are accounting
financial experts NONACCT_ACFE: Percentage of audit committee members who are non-accounting
financial experts RATIO: Ratio of audit fee to total fee ACIND: Percentage of outside directors on the audit committee ACSZ: Audit committee size ACMEET: Number of audit committee meetings BDIND: Percentage of outside directors on the board BDSZ: Size of the board of directors BDMEET: Number of board meetings BIG4: 1, if the auditor is a member of the Big 4; 0, otherwise AUDCHG: 1, if there is an auditor change in 2003 or 2004; 0, otherwise TOTAL ASSETS: Total assets (#6) ADJSALEGR: Two-digit industry median adjusted sales growth, measured as the
percentage change in sales from the previous year minus the two-digit industry median sales growth
ACQUISITION: 1, if a firm engages in acquisitions during 2003, 2004 and from January to July of 2005; 0, otherwise
RESTRUCTURE: 1, if a firm engages in a restructuring (non-zero values of #376, #377, #378, or #379); 0, otherwise
BUS: Number of business segments reported in 10-K FOREIGN: 1, if there is a foreign currency translation (#150); 0, otherwise SALES: Total sales (#12), in millions EBITDA/SALES: Ratio of EBITDA (#13) to sales (#12) GOVERN: Please see definition in the text.
Note:
COMPUSTAT item numbers are in parentheses.
28
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32
Table 1. Sample Selection Procedure The sample consists of firms identified by Compliance Week as having material internal control weaknesses from November 15, 2004 to July 31, 2005. We exclude firms without Cusip numbers or not in COMPUSTAT, foreign firms or subsidiaries, firms with missing values for operating margin, non-material weakness firms, and firms without proxy information. Data in parentheses indicate the number of firms removed from the full set of 372 firms to obtain the final sample of 208 companies.
Sample Characteristics Number of Firms
Total firms identified by Compliance Week as having internal control problems from November 15, 2004 to July 31, 2005 (excluding 31 duplicate appearances)
372
Excluding firms without Cusip Numbers
(10)
Excluding firms not in COMPUSTAT
(9)
Excluding foreign firms or subsidiaries
(13)
Excluding firms with missing values for EBITDA profit margin (COMPUSTAT #13/COMPUSTAT #12)
(57)
Excluding non-material weakness firms
(54)
Excluding firms with missing proxy information
(21)
Final Sample
208
33
Table 2. Mean and Median Comparison for Sample and Control Firms
Variable Sample firms
Mean Median
Control firms Mean Median
Mean Difference (p-value)
Median Difference (p-value)
ACFE 0.75 0.75
0.83 1.00
-0.08 (0.00)
-0.25 (0.01)
ACCT_ACFE 0.22 0.25
0.23 0.25
-0.01 (0.41)
0.00 (0.27)
NONACCT_ACFE 0.53 0.67
0.59 0.67
-0.06 (0.02)
0.00 (0.06)
RATIO 0.78 0.83
0.75 0.78
0.03 (0.09)
0.05 (0.05)
ACIND 0.92 1.00
0.93 1.00
-0.01 (0.55)
0.00 (0.82)
ACSZ 3.46 3.00
3.52 3.00
-0.06 (0.41)
0.00 (0.93)
ACMEET 9.31 8.00
7.89 8.00
1.42 (0.00)
0.00 (0.05)
BDIND 0.68 0.70
0.70 0.71
-0.02 (0.23)
-0.01 (0.31)
BDSZ 8.14 8.00
8.33 8.00
-0.19 (0.43)
-0.00 (0.52)
BDMEET 8.49 7.00
7.43 7.00
1.06 (0.01)
0.00 (0.05)
BIG4 0.81 1.00
0.79 1.00
0.02 (0.54)
0.00 (0.54)
AUDCHG 0.16 0.00
0.10 0.00
0.06 (0.06)
0.00 (0.06)
TOTAL ASSETS 11130.58 495.31
4893.83 574.86
6236.75 (0.26)
-79.55 (0.80)
ADJSALEGR 0.13 0.00
0.20 0.01
-0.07 (0.51)
-0.01 (0.42)
ACQUISITION 0.04 0.00
0.03 0.00
0.01 (0.43)
0.00 (0.43)
RESTRUCTURE 0.31 0.00
0.24 0.00
0.07 (0.10)
0.00 (0.10)
BUS 2.17 1.00
2.09 1.00
0.12 (0.64)
0.00 (0.62)
FOREIGN 0.30 0.00
0.29 0.00
0.01 (0.83)
0.00 (0.83)
SALE* 2701.43 375.02
1745.72 365.11
955.71 (0.35)
9.91 (0.95)
EBITDA/SALE -0.14 0.11
-0.45 0.11
0.31 (0.52)
0.00 (0.41)
N 208 208
The 208 control firms that have no internal control problems are matched to the 208 sample firms that do have internal control problems, one-on-one, based on industry, size, and performance. Financial variables are retrieved from COMPUSTAT; the acquisition variable is obtained from Securities Data Company; the business segment variable is acquired from COMPUSTAT segment files; and audit committee-, board-, and fee variables are hand-collected from the proxy statements. Because sample firms are matched to control firms on a one-to-one basis, we use the paired t-test to test the differences in mean and the Wilcoxon signed
34
rank test to test the differences in median. All variable definitions are in the Appendix. Two-tailed p-values are reported in parentheses.
* The large difference in the mean comparison of sales is driven by General Electric, which has substantially larger sales than does its closest match firm. Without GE and its match firm, the mean (median) sales in millions for the sample and control will be 1983.57 (372.50) and 1742.15 (364.18), respectively. We find that our main results in Table 4 remain unchanged, when we exclude GE and its match firm in our conditional logit regressions.
35
Table 3. Pearson (Upper Right) / Spearman (Lower Left) Correlation Coefficients
ICW ACFE ACCT_ ACFE
NONACCT_ ACFE RATIO ACIND
LOG (ACSZ)
LOG(AC MEET)
BD IND
LOG (BDSZ)
LOG(BD MEET) BIG4
AUD CHG LOG(TA)
ADJ SALEGR
ACQUI SITION
RESTRU CTURE
LOG (BUS)
FOR EIGN
ICW -0.16*** -0.04 -0.11** 0.08* -0.03 -0.03 0.11** -0.06 -0.04 0.13*** 0.03 0.09* 0.04 -0.03 0.04 0.08* 0.03 0.01
ACFE -0.14*** 0.25*** 0.64*** -0.05 0.06 -0.01 -0.07 0.13*** -0.01 -0.05 0.13*** -0.04 0.00 0.07 0.02 0.07 0.02 0.06
ACCT_ ACFE -0.05 0.27*** -0.54*** 0.06 0.01 -0.12*** 0.02 0.05 -0.03 -0.01 0.04 0.06 -0.02 -0.02 -0.01 0.02 0.01 -0.02
NONACCT_ ACFE -0.09* 0.67*** -0.52*** -0.09* 0.04 0.09* -0.08 0.07 0.02 -0.04 0.08* -0.08* 0.02 0.08 0.03 0.04 0.01 0.07
RATIO 0.09** -0.10** 0.06 -0.11** 0.01 0.03 0.09** -0.04 -0.02 0.02 0.07 -0.09* -0.10** 0.05 0.02 0.00 -0.03 -0.01
ACIND 0.01 0.06 0.01 0.06 0.02 -0.01 -0.10** 0.48*** -0.01 -0.07 0.03 -0.04 -0.03 0.07 0.06 -0.05 -0.06 0.04
LOG(ACSZ) 0.00 -0.05 -0.19*** 0.06 0.02 -0.01 0.12*** 0.26*** 0.41*** 0.07 -0.01 -0.07 0.35*** -0.14*** -0.07 0.04 0.15*** -0.06
LOG(AC MEET) 0.10** -0.05 0.06 -0.10** 0.12** -0.08* 0.19*** 0.06 0.25*** 0.41*** 0.22*** -0.01 0.35*** -0.01 0.03 0.14** 0.05 0.11**
BDIND -0.05 0.11** 0.03 0.07 -0.07 0.43*** 0.27*** 0.10** 0.16*** 0.02 0.15*** -0.07 0.23*** -0.08* -0.06 0.11** 0.06 0.08*
LOG(BDSZ) -0.03 -0.01 -0.06 0.02 -0.04 -0.03 0.38*** 0.26*** 0.21*** 0.15*** 0.04 -0.11** 0.60*** -0.03 -0.06 0.02 0.15** -0.03
LOG(BD MEET) 0.10** -0.01 -0.01 -0.01 0.02 -0.03 0.10** 0.34*** 0.04 0.14*** 0.01 0.02 0.19*** 0.07 -0.02 0.05 -0.03 -0.02
BIG4 0.03 0.12*** 0.03 0.06 0.06 0.04 -0.00 0.21*** 0.15*** 0.06 0.01 -0.30*** 0.17*** -0.12*** -0.06 0.21*** 0.23*** 0.18***
AUDCHG 0.09* -0.04 0.06 -0.08 -0.07 -0.01 -0.02 -0.01 -0.07 -0.12** 0.01 -0.30*** -0.12** 0.01 0.12*** -0.01 -0.06 -0.04
LG(TA) 0.01 0.02 -0.02 0.02 -0.14*** -0.03 0.30*** 0.36*** 0.27*** 0.58*** 0.18*** 0.15*** -0.11** -0.08 -0.06 0.08* 0.21*** 0.02
ADJ SALEGR -0.04 0.03 0.06 -0.03 -0.08 0.09* -0.12*** -0.01 -0.08* -0.10** -0.07 -0.04 0.04 -0.01 0.20 -0.09* -0.09* -0.00
ACQUI SITION 0.04 0.01 -0.01 0.04 0.02 0.07 -0.06 0.02 -0.08 -0.06 -0.01 -0.06 0.12 -0.07 0.03 -0.004 -0.03 -0.04
RESTRU CTURE 0.08* 0.06 0.01 0.03 -0.02 -0.02 0.04 0.16*** 0.13*** 0.03 0.05 0.21*** -0.01 0.11** -0.17*** -0.004 0.17*** 0.30***
LOG(BUS) 0.02 0.03 0.00 0.01 -0.03 -0.07 0.16*** 0.06 0.06 0.15*** -0.02 0.23*** -0.06 0.16*** -0.11** -0.03 0.17*** 0.04
FOREIGN 0.01 0.07 -0.01 0.06 -0.04 0.05 -0.07 0.09* 0.07 -0.03 -0.01 0.18*** -0.04 0.01 -0.04 -0.04 0.30*** 0.05
All variable definitions are in the Appendix. *, **, and *** denote the two-tailed significance at the ten-, five-, and one-percent levels, respectively.
36
Table 4. Conditional Logit Analysis of Determinants of Internal Control Weaknesses
Variable Predicted Sign Model 1 Model 2 Model 3 Model 4
ACFE - -1.84 (-3.46)***
-1.81 (-3.32)***
ACCT_ACFE -
-2.19 (-2.94)***
-2.21 (-2.90)***
NONACCT_ACFE -
-1.78 (-3.31)***
-1.75 (-3.17)***
RATIO ? 1.30 (2.18)**
1.28 (2.07)**
1.31 (2.19)**
1.29 (2.09)**
ACIND - 0.32 (0.42)
0.53 (0.56)
0.33 (0.43)
0.52 (0.55)
LOG(ACSZ) ? -0.71 (-1.23)
-0.35 (-0.56)
-0.79 (-1.33)
-0.43 (-0.67)
LOG(ACMEET) ? 0.31 (1.24)
0.20 (0.75)
0.31 (1.24)
0.21 (0.78)
BDIND -
-0.52 (-0.58)
-0.49 (-0.55)
LOG(BDSZ) ?
-0.95 (-1.81)*
-0.98 (-1.84)*
LOG(BDMEET) ?
0.56 (1.88)*
0.56 (1.89)*
BIG4 - 0.21 (0.52)
0.26 (0.64)
0.21 (0.53)
0.26 (0.64)
AUDCHG + 0.85 (2.44)***
0.88 (2.45)***
0.89 (2.51)***
0.92 (2.54)***
LOG(TA) - 0.24 (1.37)
0.26 (1.43)
0.23 (1.33)
0.25 (1.39)
ADJSALEGR + -0.11 (-0.96)
-0.12 (-1.06)
-0.11 (-1.03)
-0.13 (-1.15)
ACQUISITION + 0.31 (0.47)
0.27 (0.42)
0.23 (0.34)
0.19 (0.29)
RESTRUCTURE + 0.47 (1.47)*
0.54 (1.63)*
0.48 (1.50)*
0.55 (1.66)**
LOG(BUS) + 0.17 (0.83)
0.15 (0.75)
0.18 (0.91)
0.17 (0.83)
FOREIGN + -0.001 (-0.01)
0.04 (0.14)
0.01 (0.02)
0.05 (0.18)
N 416 416 416 416
This table presents the conditional logit analysis for matched-pair regressions. The 208 control firms that have no internal control problems are matched to the 208 sample firms that do have internal control problems, one-on-one, based on industry, size, and performance. The dependent variable ICW takes a value of 1, if a firm has internal control weaknesses and 0, otherwise. All variable definitions are in the Appendix. *, **, and *** denote significance at the ten-, five-, and one-percent levels, respectively, on a one-tailed test for coefficients with sign prediction and a two-tailed test without sign predictions.
37
Table 5. Conditional Logit Analysis of Determinants of Internal Control Weaknesses:
Controlling for Overall Measure of Corporate Governance
Variable Predicted Sign Model 1 Model 2
ACFE - -1.85 (-3.46)***
ACCT_ACFE -
-2.03 (-2.76)***
NONACCT_ACFE -
-1.81 (-3.35)***
RATIO ? 1.19 (1.96)**
1.19 (1.97)**
GOVERN - 0.22 (0.93)
0.22 (0.95)
LOG(ACMEET) ? 0.17 (0.64)
0.17 (0.64)
LOG(BDMEET) ? 0.47 (1.58)
0.47 (1.58)
BIG4 - 0.33 (0.84)
0.34 (0.86)
AUDCHG + 0.87 (2.45)***
0.89 (2.47)***
LOG(TA) - 0.23 (1.24)
0.22 (1.20)
ADJSALEGR + -0.10 (-0.81)
-0.10 (-0.84)
ACQUISITION + 0.33 (0.51)
0.29 (0.44)
RESTRUCTURE + 0.40 (1.21)
0.40 (1.22)
LOG(BUS) + 0.16 (0.82)
0.17 (0.85)
FOREIGN + 0.09 (0.34)
0.10 (0.36)
N 412 412
This table presents the conditional logit analysis for matched-pair regressions. The 206 control firms that have no internal control problems are matched to the 206 sample firms that do have internal control problems, one-on-one, based on industry, size, and performance. The dependent variable ICW takes a value of 1, if a firm has internal control weaknesses and 0, otherwise. We lost two pairs of observations, since we cannot find the institutional ownership data which are necessary to calculate the overall governance measure. All variable definitions are in the Appendix. *, **, and *** denote significance at the ten-, five-, and one-percent levels, respectively, on a one-tailed test for coefficients with sign prediction and a two-tailed test without sign predictions.