Using debt-related events as explanatory factor of audit failures
Lee J. Yao*
Joseph A. Butt, S.J. College of Business
Loyola University New Orleans
Email: aljyao@gmail.com
Siew H. Chan
School of Accounting
Washington State University
Pullman, Washington, USA
Jia Wu
Charlton College of Business
University of Massachusetts at Dartmouth
Key words: audit independence, event study, debt-related events, going-concern; audit
failure
* All correspondence should be communicated to the first author.
INTRODUCTION
Background
The recent collapse of Enron, the world’s largest energy-trading company has put the
accounting profession under scrutiny. Enron highlights the possible failure of the
accounting profession. Arthur Andersen’s role in the Enron case has hurt the profession’s
credibility and the public’s trust in it. This debacle has triggered wide-ranging debates and
has subsequently raised many issues for the accounting profession, most important of all,
the issue of auditor independence.
Internationally, the issue of auditor independence has been featured prominently in the
reviews by the International Federation of Accountants and the European Commission, as
well as the U.S. Securities and Exchange Commission (SEC). The Asia Pacific Economic
Community (APEC) Task Force on Company Accounting and Financial Reporting have
also identified auditor independence as a pressing issue throughout APEC member
economies [Ministry of Finance, Singapore, 2001].
The auditor’s report plays a critical role in warning market participants of impending
going-concern problems. Indeed, the term audit failure typically refers to cases in which
auditors fail to issue going-concern opinions to clients that subsequently file for bankruptcy
[Blacconiere and DeFond, 1997]; [Weil, 2001].
Since independent auditing is an essential feature of efficient capital markets, regulators
have long been concerned about the potential threats to auditor independence. The
implications for such threats are far-reaching and could affect many players in the capital
markets.
Motivation
Auditors are charged with the responsibility of evaluating the likelihood of going-concern
of their clients. Although the evaluation is not intended to be a predictor of bankruptcy,
financial statement users often treat the evaluation as an early warning of impending
failure. Since regulators and users tend to treat an unmodified audit opinion as a “clean bill
of health”, they do not expect the business to fail in the near future [Casterella et al 2000].
Research has shown that more often than not, auditors end up letting users down when it
comes to predicting bankruptcy filings with audit opinions [Casterella et al 2000].
In the wake of Enron’s bankruptcy, auditors are blamed for not doing their jobs well.
Although auditors assert that they are not responsible for predicting future events, it is very
clear that their opinion decisions are evaluated, at least in part, based on events that occur
after the audit report date.
The interesting and logical next step is to find out why auditors fail in their roles. Does it
implicate the issue of auditor independence? At the time of auditing, was there contrary
information that the auditors chose to ignore or were there mitigating factors that indicated
that the firms would survive? With this knowledge in mind, auditors could prevent similar
incidents like Enron from happening in the future and help to restore the public’s
confidence in the accounting profession.
Objectives
The objective of this study is to examine the issue of audit failure by studying why some
bankrupt companies receive unmodified opinions while others do not. This study examines
the use of a contrary information, the occurrence of negative debt-related events, in
auditors’ decisions to issue going-concern opinions to firms, taking into consideration the
financial stress level of the firms.
Previous research by Mutchler et al [1997] has shown that contrary information and
mitigating factors will affect the going-concern modification decision made by auditors for
soon-to-be bankrupt companies. Contrary information questions the client’s continued
existence, and mitigating factors partially offset contrary information.
Organization of Report
The remaining of the paper is organized as follows. Part 2 reviews prior research done on
issues relevant to this paper. Studies on explanatory factors of audit failure are examined.
They are existence of contrary information and mitigating factors, and lack of auditor
independence. Part 3 provides discussions on the extension of prior research and the
development of hypotheses for this paper. It explains the rationale for testing those
hypotheses. The hypotheses are classified into five areas, each testing the different effects
on the variables involved. In addition, the process of sample selection and events studies is
elaborated. Part 4 presents the descriptive statistics and data analysis. In addition,
correlation and independent samples t-tests are performed to provide further analysis. Part 5
summarizes the findings of this research, states the limitations and provides some
suggestions for future studies.
LITERATURE REVIEW
Audit Failure
Many prior studies such as Altman and McGough [1974, 1982], Menon and Schwartz
[1986], Hopwood et al [1989] and McKeown et al [1991] had found that high proportion
(more than 50%) of bankrupt firms did not receive a going-concern qualification (GCQ) in
the year prior to their bankruptcies. It is questionable as to why such audit failure could
have occurred. Could it be due to a lack of auditor independence? Or was the existence of
contrary information at the time of auditing not strong enough to prompt GCQ or were
there mitigating factors that led the auditors to conclude that the firms would survive?
Existence of Contrary Information and Mitigating Factors as Explanatory Factor of
Audit Failure
Necessity to Consider Contrary Information and Mitigating Factors
Statement on Auditing Standards (SAS) No. 59 [AICPA, 1988] requires auditors to
evaluate the prospects that a client will be able to continue in existence for a reasonable
period of time as part of every engagement. In the evaluation, auditors are required to
consider the contrary information and mitigating factors. Contrary information is
information that questions the client’s continued existence [Mutchler et al 1997]. It
increases the probability of bankruptcy and includes information such as debt or covenant
defaults and substantial sale of assets to reduce debt [Sharma, 2001]. Mitigating factors are
information that reduce the probability of bankruptcy and include financial and nonfinancial news and events [Sharma, 2001].
A number of prior researches examined whether the occurrence of negative debt-related
events such as debt, covenant defaults, debt accommodations, had any association with the
types of audit opinion issued. In essence, these studies tested whether the existence of
contrary information would prompt auditors to issue GCQ. In addition, some studies tested
if mitigating factors could explain the non-issuance of GCQ.
Contrary Information: Default Status and Restructuring
In Chen and Church [1992], the default status of bankrupt firms in the year preceding
bankruptcy was examined. The variable default included payment and covenant defaults
together. The results showed that the relationship between default status and type of audit
opinion received was not independent. The study found that about 77% of the firms
receiving first-time GCQ were already in default or in the process of restructuring their
debts, the purpose being to avoid subsequent default [Chen and Church, 1992].
Contrary Information: Payment and Covenant Default
In Mutchler et al [1997], it was hypothesized that firms with payment or covenant default
were more likely to receive qualified opinion. Unlike Chen and Church [1992], the
payment and covenant defaults were studied as two separate variables. The result supported
the hypotheses.
Sharma [2001] hypothesized that debt or covenant defaults would increase the likelihood of
GCQ. Also it hypothesized that compared to companies that had never defaulted, those that
had cured their problems were more likely to receive GCQ. The evidence showed that debt
default and GCQ had a significant positive relationship. The hypothesis that firms with
cured debt had a greater likelihood of being qualified was also supported.
Contrary Information and Mitigating Factors: News Reported
In Mutchler et al [1997], the effects of news items reported as contrary information or
mitigating factors were studied. They collected news items reported in the Wall Street
Journal Index. The news found was classified as mild or extreme positive event or mild or
extreme negative event. The news were further classified as “before” if they occurred in the
time frame of two years prior bankruptcy to the last audit report date, and “after” if they
belonged to the time frame of between the last audit report date and the bankruptcy date.
The findings showed that only the “before” extreme negative events affected the opinion
issued. The mitigating factors were not significant.
Auditors’ Independence as Explanatory Factor of Audit Failure
The debate over auditor independence is decades old. The public and regulators are
concerned that with the fee dependency on the audit clients, auditors may compromise their
independence. One consequence of compromise of auditor independence is audit failure.
Many prior literatures undertook research in different ways to study whether auditor
independence was sacrificed when the client was a huge source of revenue.
According to research from Massachusetts Institute of Technology, Michigan State
University, and Stanford, auditors were more likely to condone earnings management when
audit clients paid large non-audit fees [Anonymous, 2002]. From the result, it may indicate
that the auditors had compromised their independence in exchange for the high fees. One
possible implication of condoning earnings management is it gives a higher risk of
corporate failure especially when the earnings management has been of a considerable
scale. Since the auditors are not likely to issue GCQ to this group of firms, the result will
thus be a higher probability of audit failure. One famous example of this would be Enron.
McKeown et al [1991] hypothesized that smaller companies were more likely to be
qualified, ceteris paribus. In the model for forming qualified opinion, the variable size was
already incorporated in the variable probability of bankruptcy, yet it was found to be a
significant variable in the model. Thus, the fact that the variable size was significant
indicated that size was a factor in the auditors’ opinion decisions above and beyond the fact
that there might be a relationship between bankruptcy and size [McKeown et al 1991]. This
provided evidence that with a larger client size, auditor independence was more likely to be
compromised.
Mutchler et al [1997] investigated whether the use of contrary information and mitigating
factors could explain the relationship between size and GCQ found in McKeown et al
[1991]. The result showed that the presence of contrary information and mitigating factors
did not explain the relationship. Once again, suggesting that auditors may compromise
independence in the presence of larger clients.
In another study by Rose-Green et al [2002], the auditor independence issue was
investigated by examining the associations between audit and non-audit fees paid to a
firm’s auditor. The research showed that audit firms collecting high audit fees from their
client firms might be willing to reduce those fees in exchange for non-audit services
contract. This implied that the provision of non-audit services influenced the auditors on
audit-related decisions. Although in this case, the effect was on pricing of audit fees, the
fees charged might have some impact on the audit effectiveness, since the resources
allocated for the audit might be affected.
Contrary to the findings of the above-mentioned literatures, the following researches found
no association between fee dependency and auditor independence. Reynolds and Francis
[2000] hypothesized that large clients created economic dependence, which was defined as
a client’s size relative to the size of the audit office, which might cause auditors to
compromise their independence and report more favorably to retain valuable clients.
However, no support for the hypothesis was found. Evidence did not show that economic
dependence caused the Big Five auditors to report more favorably for larger clients.
A study similar to the above, Craswell et al [2002] investigated whether fee dependency
affected the auditors’ exercise of independent judgment represented by the propensity to
issue qualified opinions. The result found no support for the claim that the level of fee
dependency would affect the auditors’ propensity to issue unqualified audit opinions.
DeFond et al [2002] examined for correlation between non-audit services fees and auditor
independence, whereby auditor independence was indicated by the auditor’s willingness to
issue a GCQ. In addition to non-audit services fees, the correlation between total fees and
auditor independence was also tested. Neither the non-audit services fee nor the total fees
was found to have significant association with the auditors’ propensity to issue GCQ.
DEVELOPMENT OF HYPOTHESES AND RESEARCH METHOD
This study examines the issue of audit failure, investigating the possible explanations as to
why auditors fail to issue GCQ to firms that displayed signs of financial distress (FD) prior
to their bankruptcies. This could entail issues relating to the lack of independence.
However, as numerous studies investigating audit fees as proxy of lack of independence
have been done, this issue will not be explored in this study. Instead, effects of negative
debt-related events and the debt magnitude of these events will be studied to further explore
if these factors could possibly provide explanations for the non-issuance of GCQ.
The first part of this chapter develops the hypotheses that test the objectives of this study.
The second part deals with the sample selection.
Effect of Financial Stress Level of Firms on Auditors’ Opinions
This study examines the effect of financial stress level of firms on auditors’ opinions. Firms
in FD should be issued GCQ as SAS No. 59 [AICPA, 1988] requires auditors to evaluate
the prospects of a client being able to continue in existence for a reasonable period of time
as part of every engagement. Raghunandan and Rama [1995] concluded that auditors were
more likely to modify the opinions of distressed firms after the issuance of SAS No. 59.
However, Carcello et al [1995] did not find a difference in auditors’ inclination to issue
GCQ after SAS No. 59.
On the other hand, Chen and Church [1992] found evidence of auditors issuing GCQ when
certain signs of FD were present. In view of the inconsistency in results previously
obtained, this study examines the following hypothesis:
H1:
Auditors tend to issue GCQ for bankrupt firms in FD prior to bankruptcy.
McKeown et al [1991] proposed an identical hypothesis. The only difference lies in the
proxy used for FD. In their study, the probability of bankruptcy was used as the proxy. In
the above hypothesis, two variables, FD and GCQ are tested for any positive correlation
between them. If auditors had issued GCQ for firms in FD and they subsequently went
bankrupt, it shows that the auditors had done a good job in evaluating the going-concern
probability of the firms.
Effect of Occurrence of Debt News on Auditors’ Opinions
Foster et al [1998]’s study on usefulness of debt defaults and GCQ in bankruptcy risk
assessment suggested that loan default/accommodation and loan covenant violation were
both significant explanatory variables of bankruptcy. In addition, these events captured the
information contained in auditors’ GCQ. Chen and Church [1992], Mutchler et al [1997]
and Sharma [2001] had concluded in their respective studies that the occurrence of debtrelated events in a firm would increase the likelihood of it receiving a GCQ.
The occurrence of negative debt news prior to the firm’s bankruptcy may provide some
insights to the firm’s going-concern problems. Further to prior studies in this area, debt
news is classified into seven categories in this study (refer to Table 3.5). This study
attempts to find out the impact of negative debt news on auditors’ decisions to issue GCQ,
thus leading to the following hypothesis:
H2:
The occurrence of negative debt-related events in the year prior to the
bankruptcy prompted auditors to issue GCQ.
The hypothesis is further broken down into each category of the negative debt-related
events as shown in Table 3.1. Each hypothesis is tested for any associative relationship
between the occurrence of a certain type of debt news and the issuance of GCQ.
TABLE 3.1: HYPOTHESES RELATING TO OCCURRENCE OF DEBT NEWS
AND AUDITORS’ OPINIONS
H3:
The occurrence of covenant violation news prompted the issuance of GCQ.
H4:
The occurrence of credit facility news prompted the issuance of GCQ.
H5:
The occurrence of debt news prompted the issuance of GCQ.
H6:
The occurrence of notes-related news prompted the issuance of GCQ.
H7:
The occurrence of default news prompted the issuance of GCQ.
H8:
The occurrence of restructuring news prompted the issuance of GCQ.
H9:
The occurrence of waiver of debt news prompted the issuance of GCQ.
Occurrence of Debt News and Financial Stress Level of Firms
Prior FD studies [Giroux and Wiggins, 1984]; [Lau, 1987]; [Ward, 1994, 1995]; [Ward and
Foster, 1996] researched on distress events other than bankruptcy experienced by stressed
firms and concluded debt loan default/accommodation as one of the most severe FD events.
This study builds on these prior literatures to examine for correlation between the
occurrence of negative debt-related events and financial stress level of firms. It is expected
that FD firms would experience a higher incidence of debt-related events compared to nonfinancial distress (NFD) firms. This leads to the following hypothesis:
H10: The occurrence of negative debt-related events is positively correlated with FD.
This hypothesis is further tested for correlations between FD and each of the seven
categories of debt news as shown in Table 3.2. This is to find out whether there is any
significant correlation between FD and occurrence of a certain type of debt news.
TABLE 3.2: HYPOTHESES RELATING TO OCCURRENCE OF DEBT NEWS
AND FINANCIAL STRESS LEVEL OF FIRMS
H11: The occurrence of covenant violation news is positively correlated with FD.
H12:
The occurrence of credit facility news is positively correlated with FD.
H13:
The occurrence of debt news is positively correlated with FD.
H14:
The occurrence of notes-related news is positively correlated with FD.
H15:
The occurrence of default news is positively correlated with FD.
H16:
The occurrence of restructuring news is positively correlated with FD.
H17:
The occurrence of waiver of debt news is positively correlated with FD.
Magnitude of Debt on Financial Stress Level of Firms
This section further examines the magnitude of debts in the debt-related events on the
financial stress level of the sample firms. This is an area that prior FD studies have not
explored.
Besides considering the debt amount, which is taken to be the aggregate of all the debt
amounts in the debt-related events taken into account within the time period, the magnitude
of debt ratios are also examined. These debt ratios include ratio of the debt amount to the
total sales, total assets, net profit and total liabilities in the year of the news occurrence.
These ratios are included in this study as they are commonly used as performance
indicators by both management and financial institutions when evaluating the liquidity and
viability of the company or clients. Table 3.3 shows the 5 hypotheses that are tested in this
section. The debt amounts and ratios of FD and NFD firms are tested for differences in
mean.
TABLE 3.3: Hypotheses Relating to Magnitude of Debt on Financial Stress Level of
Firms
H18:
The FD group and NFD group have no difference in the mean of debt amount.
H19:
The FD group and NFD group have no difference in the mean of debt/sales ratio.
H20:
The FD group and NFD group have no difference in the mean of debt/total asset ratio.
H21:
The FD group and NFD group have no difference in the mean of debt/net profit ratio.
H22:
The FD group and NFD group have no difference in the mean of debt/total liabilities
ratio.
Magnitude of Debt on Opinion Issued to Firms
Similar to the previous section, the study of the magnitude of debt on the opinions issued
by auditors is an area that has not been done by prior researchers. This study seeks to find
out whether auditors are affected by the magnitude of the debt amounts in the news events
in their issuance of audit opinions. In addition, this may explain why auditors did not issue
GCQ for the sample firms, which had occurrence of negative debt-related events. The low
magnitude of debt and/or debt ratios could be plausible explanations for the non-issuance of
GCQ for 70% of the sample firms.
Table 3.4 shows the hypotheses that are tested. The debt amounts and ratios of firms, which
were issued GCQ and those, which were issued non-going-concern qualifications (NGCQ)
are tested for differences in mean.
TABLE 3.4: Hypotheses Relating to Magnitude of Debt on Opinions Issued to Firms
H23:
The GCQ group and NGCQ group have no difference in the mean debt amount.
H24:
The GCQ group and NGCQ group have no difference in the mean of debt/sales ratio.
H25: The GCQ group and NGCQ group have no difference in the mean of debt/total
asset ratio.
H26:
The GCQ group and NGCQ group have no difference in the mean of debt/net profit ratio.
H27:
The GCQ group and NGCQ group have no difference in the mean of debt/total liabilities
ratio.
Types of Companies in Sample
The main source of data is the Global Researcher (GR) database.1 The GR contains the
SEC database detailing both financial and textual information on over 12,000 US public
companies. The SEC database uses templated data collected from SEC company filings,
annual report and information filed with the companies’ corresponding exchanges. To be
involved in the GR SEC database, a company must provide a direct good or service and file
with the SEC. Thus, the criteria2 that the companies used in the sample selection include:
1) provide a direct good or service
2) listed on a national securities exchange or trade securities over-the-counter
3) have at least 500 shareholders of one class of stock
4) have at least $5 millions in assets.
Sample Selection
Bankruptcy
The sample consists of publicly traded US firms that filed for Chapter 11 bankruptcy
during the period 1999-2001. The authors selected the initial sample by identifying
bankrupt (inactive) firms with Standard Industrial Classification (SIC) codes less than
6000, which are industrial firms. Firms with SIC codes greater than 6000 are excluded, as
1
2
Global Researcher is now known as OSIRIS.
Criteria 2 to 4 being conditions to fulfill in order to file with SEC.
they are financial firms with different financial statements reporting formats.
The authors first identified firms in the GR database that went bankrupt in the three years,
1999 to 2001. The firms were considered bankrupt in the year they filed for bankruptcy.
Hence, any bankrupt firms that were brought forward from the previous years were
eliminated from the list of bankrupt firms of a particular year.
Financial Distress
In Argenti [1976], three types of corporate failure were identified. The first type of
corporate failure included fledging companies that never moved out of FD. The second type
included companies that slowly moved into insolvency, having financial ratios that would
have shown signs of problems. The third type had companies that failed without any
warning signs. In the issuance of auditors’ opinions, Argenti [1976]’s results showed that
auditors face two situations, FD was important for one but not for the other. By breaking
the sample into FD and NFD, this would enhance within-group homogeneity and hence
explanatory power. Previous studies by Mutchler [1985] and Hopwood et al [1994]
recommended that financial statements of the inactive firms be examined to determine if
the firms were financially stressed. This recommendation is adopted in this study with
some modifications.
Gilbert et al [1990] defined distressed group as companies that had negative cumulative
earnings (income from continuing operations) over a consecutive three-year period. Chen
and Church [1992] defined problem companies as meeting any of the criteria: (1) negative
net worth, (2) negative cash flows, (3) negative operating income, (4) negative working
capital, (5) negative net income or (6) negative retained earnings. Mutchler et al [1997]
defined financially stressed as (1) negative working capital in the last financial statement
issued before bankruptcy, (2) loss from operations in any of the three years prior to
bankruptcy or (3) retained earnings deficit in three years prior bankruptcy. After
considering the definitions used in prior studies, FD is defined in this study as firms
exhibiting at least one of the following three criteria:
(1)
negative working capital in the year prior to bankruptcy3 ;
(2)
negative equity in the year prior to bankruptcy4 ;
(3)
operating loss for consecutive three years prior to the year of bankruptcy5
The bankrupt firms not meeting any of the above criteria were considered as NFD firms.
The initial sample of 1,284 bankrupt firms is separated into 475 FD and 809 NFD firms
(see Diagram 3.1).
Auditors’ Opinions
Following the identification of bankrupt and financially distressed firms from the GR
database, the authors examined the audit reports of the initial set of bankrupt firms for
GCQ.
Chen and Church [1992] used key words of (1) going-concern, (2) unable to continue in
existence and (3) unable to continue in operations, in search for going-concern firms.
Mutchler et al [1997] defined classification of going-concern modification as (1) disclaims
an opinion, (2) expresses doubt about ability to survive as going-concern and (3) expresses
doubt about ability to finance future operations.
Considering the definitions used in prior studies, GCQ in this study includes qualified audit
report and any form of modification, disclaimer or limitation that are suggested in the
report. Keywords used in the Boolean search function in GR were “qualified”, “emphasis
on”, “continuity dependent upon”, “substantial doubt” and “subject to”. Hence, qualified
firms in this study also include firms with modified unqualified audit report. The bankrupt
firms without any of these keywords in the audit reports were classified as non-qualified
firms. The initial sample of 1,284 bankrupt firms is separated into 171 qualified firms and
1,113 non-qualified firms (see Diagram 3.1).
3
Adopted in Chen and Church [1992] and Mutchler, Hopwood and McKeown [1997]
Adopted in Chen and Church [1992]
5
Adopted in Gilbert, Menon and Schwartz [1990]
4
DIAGRAM 3.1: BREAKDOWN OF FIRMS ENGAGED IN NEWS SEARCH
Bankrupt Firms: 1,284
Qualified Firms: 171
Financial
Distressed
Firms: 138
Non-Financial
Distressed
Firms: 33
Non-Qualified Firms: 1,113
Financial
Distressed
Firms: 337
Non-Financial
Distressed
Firms: 776
Events Studies
In Mutchler et al [1997], the effects of news items reported as contrary information or
mitigating factors were studied. In this study, a similar approach is adopted but the focus is
on a contrary information, negative debt-related news, and using it to explain the nonissuance of GCQ.
Debt-Related News Search
Next, the Factiva Online6 was used to search for negative debt-related events of these 1,284
bankrupt firms. The search was confined to news that occurred in the calendar year prior to
the firm’s bankruptcy. Any news that had negative debt-related events was included as
occurrences. The news search using Factiva Online presented 98 bankrupt firms with 161
incidents of negative debt-related news.
Classification of News Search Results
Table 3.5 below shows a classification of the news search results into 7 broad categories
and the types of news that are included in each category.
6
Factiva Online includes news publications from Reuters, Dow Jones Interactive, Wall Street Journal, Federal
Filing Newswires, Metal Bulletin and other industrial publications.
TABLE 3.5: TYPES OF NEWS IN THE SEVEN CATEGORIES
News Classification
Covenant Violation
Credit Facility
Debt
Default
Notes
Restructuring
Wavier
Types of News Included in Category
 Violation of debt covenants
 Negotiate extension of waiver of terms of its
bank-credit agreement
 New credit line
 Amendment of credit facility
 Use of credit line
 Obtaining new loan
 Extension of loan term
 Terms amendment
 Default on credit facility
 Loan default
 Inability to make payment
 Inability to meet debt obligations
 Bonds issue
 Plans to issue bonds
 Notes issue
 Sold promissory notes
 Selling of business unit to get funds
 Listed company going private for funds.
 Obtaining new financing source
 Negotiation of financing agreement
 Financing package
 Converting debt to equity (reorganization of
capital structure)
 Take over by other firms
 Wavier of default
 Wavier of debt
 Wavier of obligations
Many prior studies such as Mutchler et al [1997] and Sharma [2001] have used covenant
violation as a study factor. Hence, it is also considered as a variable in this study.
Default and restructuring are suggested by SAS No.59 [AICPA, 1988] to be potential
indicators of going-concern problems. Furthermore, default is a factor commonly used in
studies of related field, including Chen and Church [1992], Mutchler et al [1997], and
Sharma [2001].
Credit facility (short-term liability) and debt (long-term liability) form separate categories
in order to examine if the time period of financial commitment would make any difference
in the analysis. Notes issue is also of similar nature to debt, but nonetheless forms a
different category, as the former is a larger scale activity to raise funds compared to the
latter. Separating the two would enable more meaningful analysis to be made.
Waiver forms an individual category because it may involve a reclassification of debt as
short-term. Though it denotes positive essence, the continuation of the waiver could be
uncertain and that payment of debt could be demanded during the year if the covenant
violation is not remedied [Chen and Church, 1992]. Wilkins [1997] examined the
likelihood of firms receiving a GCQ when they were faced with accelerated repayment and
the corresponding liquidity difficulties resulting from debt reclassification. The study
concluded that although the decision to issue GCQ was not independent of the
reclassification decision, the existence of one did not necessarily imply the presence of the
other.
DATA ANALYSIS
Descriptive Statistics
Classification of News Events
From Table 4.1, news events relating to restructuring has the most frequent occurrence of
30%. On the other hand, news relating to waiver of debt and violation of debt covenants
make up only 2% and 4% of the total 161 news events respectively.
Table 4.1
CLASSIFICATION OF NEWS EVENTS
News Classification No. of News Incidents Percentage*
Covenant Violation
6
4%
Credit Facility
21
13%
Debt
21
13%
Default
31
19%
Notes
29
18%
Restructuring
49
30%
Waiver
4
2%
161
100%
* Includes rounding off error
Auditors’ Opinions of Sample Firms
Out of the 98 sample firms with negative debt-related news, 30% firms were issued GCQ
and the remaining 70% were non-qualified firms (see Diagram 4.1). Though GCQ firms
constitute only 30% of the sample firms, they make up 60% of the news occurrences (see
Table 4.2). GCQ firms display higher occurrence of restructuring news of 36%, whereas the
NGCQ group exhibit a higher occurrence of default news of 27% (see Table 4.2).
Diagram 4.1: GCQ and Financial Stress Level of Sample Firms
FD
NFD
Total
Percentage
GC
11
18
29
30%
NGC
40
29
69
70%
Total
51
47
98
100%
Percentage
52%
48%
100%
Table 4.2
AUDITORS’ OPINIONS OF SAMPLE FIRMS
News Classification
Covenant Violation
Credit Facility
Debt
Default
Notes
Restructuring
Wavier
% of total News
Occurrences
* Includes rounding off error
GC Firms
% of Total
Occurrences
No. of
In GC*
Occurrences
1
1%
11
11%
15
16%
14
14%
17
18%
35
36%
4
4%
97
100%
60%
NGC Firms
No. of
Occurrences
% of Total
Occurrences
In NGC*
5
10
6
14
12
14
0
64
8%
16%
9%
27%
19%
21%
0%
100%
30%
Financial Stress Level of Sample Firms
52% of the sample experienced FD prior to their bankruptcies, while the remaining 48%
did not (see Diagram 4.1). Unlike the going-concern case, no higher occurrence of news in
the FD group is observed, they each make up 50% of the total news occurrences (see Table
4.3). Default is the larger component (27%) of the FD group, while restructuring make up a
larger proportion (39%) of the NFD group (see Table 4.3).
Table 4.3
FINANCIAL STRESS LEVEL OF SAMPLE FIRMS
News Classification
FD Firms
NFD Firms
No. of
Occurrences
% of Total
Occurrences
In FD*
No. of
Occurrences
% of Total
Occurrences
In NFD*
5
13
9
22
13
18
1
81
6%
16%
11%
27%
16%
23%
1%
100%
1
8
12
9
16
31
3
80
1%
10%
15%
11%
20%
39%
4%
100%
Covenant Violation
Credit Facility
Debt
Default
Notes
Restructuring
Wavier
% of total News
Occurrences
50%
50%
* Includes rounding off error
Mean Debt Amounts and Ratios
It is observed that the FD group has a relatively higher mean for debt amounts and ratios
than the NFD group (see Table 4.4). This is logical as a firm tends to have higher debt
amounts and ratios when it is financially stressed. It is also observed that the GCQ group
has lower means for debt amounts and ratios as compared to the NGCQ group (see Table
4.5). Interestingly, this is an observation that deviates from expectation.
TABLE 4.4: SUMMARY OF THE MEAN DEBT AMOUNTSAND RATIOS FOR FD
AND NFD GROUPS
Mean
FD
NFD
Debt Amount
490839.1
218712.4
Debt / Sales
66758.73
152.2051
Debt / Total Assets
475.1997
41.9095
Debt / Net Profit
33510.37 1542.8813
Debt / Total Liabilities
547.0134
82.4115
(Extracted from Tables A1, A2, A3, A4, A5 in Appendix)
TABLE 4.5: SUMMARY OF THE MEAN DEBT AMOUNTSAND RATIOS FOR
GCQ AND NGCQ GROUPS
Mean
GCQ
NGCQ
Debt Amount
111628.0
446691.9
Debt / Sales
82.9090
44115.13
Debt / Total Assets
42.0087
324.8280
Debt / Net Profit
95.0209
23099.22
Debt / Total Liabilities
68.2778
392.4592
(Extracted from Tables A6, A7, A8, A9, and A10 in Appendix)
Relationship Between GCQ and FD Firms
Only 21.6% (see Table A11) of FD firms received GCQ. This is consistent with prior
studies [Altman and McGough 1974, 1982]; [Menon and Schwartz 1986]; [Hopwood et al
1989]; [McKeown et al 1991], which showed that less than 50% of FD firms received GCQ
for the last financial statements prior to their bankruptcies. 48% (see Table A11) of
bankrupt firms showed no signs of FD prior bankruptcy, which is a much higher percentage
compared to previous study by McKeown et al [1991]. Contrary to previous research
[Kida, 1980]; [Mutchler, 1985]; [McKeown et al 1991], which showed lower proportion of
NFD firms being qualified, a higher proportion (38.3%) of the NFD firms are issued GCQ
(see Table A11).
Correlation Analysis
The following analyses are carried out using the SPSS software.
Analysis of Effect of Financial Stress Level of Firm on Auditors’ Opinions
H1:
Auditors tend to issue GCQ for bankrupt firms in FD prior to bankruptcy.
FD and GCQ have a correlation coefficient of -0.183 (see Table A12). Although the
relationship is weak, the negative correlation suggests that firms in FD are not more likely
to be issued GCQ. Thus H1 is rejected.
This result is not in line with the general expectation that auditors will qualify firms that are
in FD. Many factors such as lack of auditor independence, mitigating factors and contrary
information could explain the non-issuance of GCQ. In this research, the magnitude of the
debts as reported in the news is taken to be as one of the mitigating factors.
Companies in the lower (25th percentile) and upper quartiles (75th percentile) of debt
amount are examined to find out if a higher percentage of GCQ firms exists in the upper
quartile as compared to the lower quartile. If so, it may imply that larger debt amounts
positively affect the issuance of GCQ. As seen from Table 4.6, firms in the upper quartile
are not more likely to be qualified as compared to the firms in the lower quartile. The same
comparison is made for debt to sales ratio, debt to total assets ratio, debt to net profit ratio
and debt to total liabilities ratio (see Table 4.6). Interestingly, except for debt to sales ratio,
the firms in the lower quartile are more likely to be qualified. This observation may imply
that the debt amounts and corresponding debt ratios are not suitable proxies to explain the
non-issuance of GCQ. Consequently, it may be concluded that debt amounts and
corresponding debt ratios are not material mitigating factors.
TABLE 4.6: COMPARSION OF GCQ FIRMS IN LOWER AND UPPER
QUARTILES
Debt
Amount
Debt /
Sales
Debt / Total
Assets
Debt / Net
Profit
Debt / Total
Liabilities
Lower Quartile
GCQ firms (%)
34.8
19.0
21.7
17.4
21.7
Upper Quartile
GCQ firms (%)
17.4
23.8
17.4
8.7
13.0
(Extracted from Tables A13, A14, A15, A16 and A17 in Appendix)
In view of the fact that debt amounts and corresponding debt ratios do not provide
satisfactory explanation to the non-issuance of GCQ, the occurrence of negative debtrelated news is studied for further explanation.
Analysis on Effect of Occurrence of Negative Debt-Related News on Auditors’ Opinions
H2:
The occurrence of negative debt-related events in the year prior to the
bankruptcy prompted auditors to issue GCQ.
The correlation coefficient between the occurrence of negative debt-related events and
GCQ is -0.209, which is significant at 0.05 level (see Table A18). The negative relationship
suggests that even with the existence of negative debt-related news, auditors’ propensity to
issue GCQ is low. Hence, H2 is rejected.
The rejection of H2 is not consistent with our argument that occurrences of negative news
prompt auditors to issue GCQ. This may be explained by the consideration of materiality
by auditors during the auditing process, as auditors only use information that would have
material impact on the firms [Mutchler et al 1997]. Another reason given by Mutchler et al
[1997] was that auditors might discount this information because it might reflect
management’s attempts to downplay the firms’ FD. However, it is not advisable to adopt
the first explanation fully as it is not likely that all the news occurrences are immaterial.
Nevertheless, the consideration of materiality may be the contributing factor to discounting
the negative news in some cases. The following hypotheses are tested to find out if any
associative relationship exists within a specific type of news events.
H3:
The occurrence of covenant violation news prompted the issue of GCQ
The correlation coefficient between the occurrence of covenant violation news and GCQ is
-0.150 (see Table A19). The negative relationship proposes that firms with covenant
violation news are not more likely to be issued GCQ. Thus H3 is rejected. Possible
justification for the relationship could be that the covenant violations are immaterial or the
debt amounts involved in those cases are of small magnitude.
Further analysis is done to find out if the second explanation is valid. Firms in the 25th
percentile of debt amount are considered to have small magnitude. From Table A20, it is
shown that 66.7% of firms with covenant violation news are in the 25th percentile. The
relatively small magnitude of debt amounts is likely to be one reason why auditors did not
issue GCQ despite the firms violating covenants. Nonetheless, it must be noted that the
number of firms with covenant violations in the whole sample is only six, out of which only
three had debt amounts mentioned in news which are considered in this analysis.
H4:
The occurrence of credit facility news prompted the issuance of GCQ
The occurrence of credit facility news and GCQ have a correlation coefficient of -0.061
(see Table A21). The result proposes that the occurrence of credit facility news is not likely
to prompt GCQ. One explanation could be that the auditors are rather optimistic and
believe that the credit facility extension could help the problem-facing firms turnaround.
The auditors may perceive this request for credit facility extension as action by
management to downplay the FD of the firms.
As credit facility is more targeted to ease short-term problems, the act of management to
seek credit facility as a solution to their problems may imply that the difficulties faced by
the firms are only temporary. Hence, this reduces the likelihood of firms being issued GCQ.
Furthermore, the auditors could be positively influenced by the bankers’ decisions to
approve further credit facility. The banks’ confidence in the firms could have a positive
impact on the auditors’ decisions.
H5:
The occurrence of debt news prompted the issuance of GCQ.
The occurrence of debt news and GCQ have a correlation coefficient of 0.043 (see Table
A22). This suggests that for firms that have more occurrences of debt news, they are more
likely to be qualified. Thus H5 is not rejected.
The difference in the time period involved could provide some explanations to the contrary
results of H4 and H5. Upon taking up a new debt, the firm puts itself into a long-term
commitment. Thus, the auditors may consider this contrary information as relatively more
material. Furthermore, the need to get more long-term debts instead of short-term credit
facilities may imply that the firm’s problem is not a temporary one that could be eased with
short-term inflow of cash. The auditor may then have more doubts about the firm’s goingconcern, hence, more willing to issue a GCQ.
H6:
The occurrence of notes-related news prompted the issuance of GCQ.
The occurrence of notes-related news and GCQ have a correlation coefficient of 0.005 (see
Table A23). This suggests that firms with occurrences of notes-related news are more likely
to be qualified. If the notes issues are successful, the firms will be incurring more liabilities,
the arguments for debt news above will then hold here. Conversely, if the issues are
unsuccessful, the firms will not be able to get the funds they need, the auditors may then
raise doubts about their going-concern and thus more willing to issue GCQ.
H7:
The occurrence of default news prompted the issuance of GCQ.
The occurrence of default news is correlated with GCQ with a coefficient to -0.134 (see
Table A24). This negative relationship suggests that for firms with default news, they are
not more likely to be issued GCQ. Thus, H6 is rejected.
This finding is contrary to the results of Chen and Church [1992], Mutchler et al [1997] and
Sharma [2001], for which all showed a positive relationship between default and GCQ.
However, these prior studies did not examine the debt magnitude. In order to explain our
result, further analysis as performed above for covenant violation news is repeated here. As
shown in Table A25, 66.7% of the firms with default news are in the first and second
quartiles. This could imply that the relatively low debt amounts involved in the default
news led the auditors to conclude that they were not material. This could perhaps provide
some insights to our finding that is contrary to prior studies.
H8:
The occurrence of restructuring news prompted the issuance of GCQ.
The occurrence of restructuring news and GCQ have a correlation coefficient of 0.130 (see
Table A26). This suggests that firms that undertake restructuring are more likely to receive
GCQ. This result supports previous findings of Chen and Church [1992]. Hence, H8 is not
rejected.
One reason could be restructuring is an extensive scale of financial activity, and it is
generally perceived that firms undergo restructuring only when they are in serious financial
difficulties. Thus, undertaking restructuring unnecessarily may weaken the public’s
confidence in the firms, and also impact auditors’ confidence in the firms’ going-concern
negatively, resulting in a higher probability of receiving GCQ.
H9:
The occurrence of waiver of debt news prompted the issuance of GCQ.
The occurrence of waiver of debt news and GCQ have a correlation coefficient of 0.092
(see Table A27). This suggests that firms with occurrences of waiver of debt news are more
likely to receive GCQ. Thus H9 is not rejected. The auditors may have perceived the firms
as being in serious financial problems since seeking waiver from creditors is likely to be a
last resort undertaken by firms, as it may affect the firms’ credibility and make future loans
difficult to obtain.
Analysis on Magnitude of Debt on Financial Stress Level of Firms
H10: The occurrence of negative debt-related events is positively correlated with FD.
The occurrence of negative debt-related events and FD have a correlation coefficient of
0.184 (refer to Table A28). The positive relationship suggests that the firms with such
negative news occurrences are more likely to be FD firms.
The occurrence of negative debt-related events is segregated into seven different categories.
It is to aid further analysis in studying how the different types of news will correlate with
the financial stress level (i.e. FD or NFD) of the firms.
H11: The occurrence of covenant violation news is positively correlated with FD.
The occurrence of covenant violation news and FD have a correlation coefficient of 0.130
(see Table A29). The result suggests that for firms with covenant violation news, they are
more likely to be FD firms. This is logical since for firms with covenant violation news, it
is highly possible that their financial status is not very sound, thus resulting in FD.
Therefore, H11 is not rejected.
H12: The occurrence of credit facility news is positively correlated with FD.
The occurrence of credit facility news and FD have a correlation coefficient of 0.116 (see
Table A30). This positive relationship between them can be explained in two ways. First, as
the firms are in FD and short of funds, they will need to get (more) credit facility, thus
resulting in a positive relationship between them. Second, it is the extension of credit
facility that leads to the FD. With the increased use of credit line, those firms will be
incurring more debts, mainly as current liabilities, hence resulting in a higher likelihood of
negative working capital. Therefore, H12 is not rejected.
H13: The occurrence of debt news is positively correlated with FD.
The occurrence of debt news and FD have a correlation coefficient of -0.096 (see Table
A31). The result suggests that for firms that have more occurrences of debt news, i.e. they
manage to get more new loans or extension or amendments of loan terms, they are less
likely to be in FD. Thus H13 is rejected.
The credit facility tested in the previous hypothesis may seem similar in nature to the debt
tested here, the only difference being credit facility is short-term while debt is a more longterm commitment. However, H13 shows result contrary to H12. The time period involved
may provide a valid explanation. A possible reasoning could be that the (long-term) debt
arrangement may be structured such that the funds will flow to the organization at an
appropriate time, to ensure a more proper matching of assets and liabilities, thereby
reducing the risks of negative equity. This is unlikely to be possible with the (short-term)
credit facility arrangement.
Another possible explanation for the negative relationship could be that firms in FD are less
likely to use debt as solutions to their FD problems. In granting loans, the firms’ ability to
repay is an important determinant of the loan approval. Thus, trying to get more loans or
amendments of terms when they are in FD are unlikely to be successful. Even if the loans
are successful, the terms are unlikely to be favorable.
H14: The occurrence of notes-related news is positively correlated with FD.
The occurrence of notes-related news and FD have a correlation coefficient of -0.021 (see
Table A32 of Appendix). This suggests that for firms with notes-related news, they are less
likely to be in FD. Thus H14 is rejected.
Notes are actually of a similar nature to debt as discussed earlier. They both lead to a longterm financial commitment. Thus the argument presented for debt would also hold here.
Furthermore, firms undertaking notes issues are less likely to be FD firms as it is unlikely
that the notes issued will fetch good terms or have good responses.
H15: The occurrence of default news is positively correlated with FD.
The occurrence of default news and FD have a coefficient of 0.125 (see Table A33). This
suggests that firms with default news are more likely to be FD firms. If the firms are not in
FD, they are unlikely to end up with default. Thus, H15 is not rejected.
H16: The occurrence of restructuring news is positively correlated with FD.
The occurrence of restructuring news and FD have a correlation coefficient of -0.221 (see
Table A34). This suggests that firms with occurrences of restructuring news are less likely
to be in FD. Therefore, H16 is rejected.
One explanation is that, the firms were not in FD but undertook restructuring to achieve
some other objectives, such as expansion of business. This explanation is supported as it is
observed that of the 49 restructuring news, 31 belong to the NFD group (see Table 4.3).
H17: The occurrence of waiver of debt news is positively correlated with FD.
The occurrence of waiver of debt news and FD have correlation coefficient of 0.087 (see
Table A35). This suggests that firms with occurrence of waiver of debt news are more
likely to be FD firms. Thus H17 is not rejected.
One possible explanation is if the firms were not in FD, they would not have defaulted their
obligations and resorted to seeking waivers. Seeking waivers unnecessarily may hurt the
firms’ credibility. Moreover, if the firms were not in FD, they would not ask for waivers, as
creditors would not be likely to grant it.
Independent Samples T-Test for Equality of Means
The following t-tests are carried out for firms with debt amounts reported in the news. This
sample constitutes 73% (72 out of 98 firms) of the sample that have negative debt-related
news. The 72 firms have a total of 102 news events, with 22 companies having more than
one news event, i.e. they have more than one debt amount. For such cases, the debt
amounts are added before using them for computation. This is justifiable since all the news
occurred in the same year, and auditors are likely to consider the overall impact of all news
events in their issuance of GCQ.
Analysis on Differences in the Means of Debt Amounts and Ratios of FD and NFD Groups
H18: The FD group and NFD group have no difference in the mean of debt amount.
H19: The FD group and NFD group have no difference in the mean of debt/sales
ratio.
H20: The FD group and NFD group have no difference in the mean of debt/total
asset ratio.
H21: The FD group and NFD group have no difference in the mean of debt/net
profit ratio.
H22: The FD group and NFD group have no difference in the mean of debt/total
liabilities ratio.
Independent samples t-tests for equality of means are performed to test the hypotheses as
shown above. The levels of significance for the 5 independent samples t-tests performed are
as summarized in Table 4.7. All the 5 tests have levels of significance of more than 0.05.
Thus H18, H19, H20, H21 and H22 are not rejected. The results suggest that the means of
debt amounts and ratios of the FD and NFD groups are not significantly different.
TABLE 4.7: SUMMARY OF LEVEL OF SIGNIFICANCE OFT-TESTS FOR FD
AND NFD
t-test signifance level
(2-tailed)
Debt Amount
0.283
Debt / Sales
0.313
Debt / Total Assets
0.209
Debt / Net Profit
0.426
Debt / Total Liabilities
0.256
(Extracted from Tables A36, A37, A38, A39 and A40 in Appendix)
Analysis on Differences in the Means of Debt Amounts and Ratios of GCQ and NGCQ
Groups
H23: The GCQ group and NGCQ group have no difference in the mean of debt
amount.
H24: The GCQ group and NGCQ group have no difference in the mean of debt/sales
ratio.
H25: The GCQ group and NGCQ group have no difference in the mean of debt/total
asset ratio.
H26: The GCQ group and NGCQ group have no difference in the mean of debt/net
profit ratio.
H27: The GCQ group and NGCQ group have no difference in the mean of debt/total
liabilities ratio.
Independent samples t-tests for equality of means are performed to test the hypotheses as
shown above. The levels of significance for the 5 independent samples t-tests performed are
as summarized in Table 4.8. All the 5 tests have levels of significance of more than 0.05.
Thus H23, H24, H25, H26 and H27 are not rejected. The results suggest that the means of
debt amounts and ratios of the GCQ and NGCQ groups are not significantly different.
TABLE 4.8: SUMMARY OF LEVEL OF SIGNIFICANCE OFT-TESTS FOR GCQ
AND NGCQ
t-test significance
level (2-tailed)
Debt Amount
0.214
Debt / Sales
0.496
Debt / Total Assets
0.386
Debt / Net Profit
0.545
Debt / Total Liabilities
0.403
(Extracted from Tables A41, A42, A43, A44 and A45 in Appendix)
CONCLUSION
This study investigates whether the occurrence of negative debt-related events has any
impact on auditors’ decisions to issue GCQ to firms, taking into consideration the financial
stress level of the firms. It aims to find out if occurrence of these events can help to explain
audit failure.
Summary of Results
An analysis of the sample shows that generally, the occurrence of negative debt-related
events does not prompt the issuance of GCQ. However, the occurrences of specific news,
namely debt, notes-related, restructuring and waiver news are positively associated with the
issuance of GCQ. Results also show that although more than half of the firms were in FD
prior to their bankruptcies, only 30% of them were issued GCQ. Having consistent findings
with many prior research, which showed low proportion of GCQ issued to firms in the year
prior to their bankruptcies, this may, once again imply the existence of audit failure. The
statistical analysis reveals that FD does not increase the likelihood of auditors issuing GCQ.
This result is contrary to the general expectation that auditors are likely to be prompted by
their clients’ financial stress level in their issuance of GCQ.
The results of this study suggest that occurrence of negative debt-related events may not be
a critical consideration for auditors in making going-concern decisions. The relatively small
magnitude of the debt amounts and ratios may provide some explanations for this
phenomenon, as auditors are mostly concerned with materiality.
Limitations
The occurrence of debt-related events may not necessarily be a good indicator of
impending firm failure. The incidence of debt-related news may signal some problems but
they may not be the main determinants of the collapse of the firm [Chen and Church, 1992].
Besides, the time period used in the news search was based on one calendar year prior to
the bankruptcy of the firms. This could be an inaccurate cutoff, as firms might not have
their financial years in coincidence with the calendar year. Hence, the time period that the
authors consider might not be the same as what the auditors of the firms had considered as
relevant in determining the likelihood of going-concern for the firms. In addition, some
relevant negative debt-related news might have been omitted because they were not found
in the Factiva Online or due to human error. Furthermore, the lack of non-bankrupt firms as
a control group may limit the analysis.
Future Research
Future research may consider, in addition to news publication, disclosures of debt-related
events through SEC filings. Auditor’s fees pertaining to non-audit services may be
examined to analyze the possibility that auditor independence may be impaired in the
occasion that the firm was in FD and had occurrence of negative debt-related events but
was not issued a GCQ. To gain a more accurate analysis of effects of these news events, it
may be more precise to consider the financial year of the sample firms instead of calendar
year in the news search. A study in Singapore context may also be considered.
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APPENDIX
TABLE A1: GROUP STATISTICS OF DEBT AMOUNT
FOR FD AND NFD GROUPS
Group Statistics
A_DEBT
FD
yes
no
N
Mean
490839.1
218712.4
32
40
Std. Error
Mean
272463.1
56206.98
Std. Deviation
1541284.103
355484.18007
TABLE A2: GROUP STATISTICS OF DEBT/SALES RATIO
FOR FD AND NFD GROUPS
Group Statistics
A_SALES
FD
yes
no
N
Mean
66758.73
152.2051
31
37
Std. Error
Mean
64869.07
65.14277
Std. Deviation
361175.68920
396.24799
TABLE A3: GROUP STATISTICS OF DEBT/TOTAL ASSET RATIO
FOR FD AND NFD GROUPS
Group Statistics
A_ASSETS
FD
yes
no
N
32
40
Mean
475.1997
41.9095
Std. Deviation
1909.90351
43.20501
Std. Error
Mean
337.62643
6.83131
TABLE A4: GROUP STATISTICS OF DEBT/NET PROFIT RATIO
FOR FD AND NFD GROUPS
Group Statistics
A_NP
FD
yes
no
N
32
40
Mean
33510.37
1542.8813
Std. Deviation
224050.17063
5744.46090
Std. Error
Mean
39606.85
908.27902
TABLE A5: GROUP STATISTICS OF DEBT/TOTAL LIABILITIES RATIO
FOR FD AND NFD GROUPS
Group Statistics
A_LIAB
FD
yes
no
N
32
40
Mean
547.0134
82.4115
Std. Error
Mean
401.36383
19.80718
Std. Deviation
2270.45670
125.27158
TABLE A6: GROUP STATISTICS OF DEBT AMOUNT
FOR GCQ AND NGCQ GROUPS
Group Statistics
A_DEBT
GCQ
yes
no
N
23
49
Mean
111628.0
446691.9
Std. Error
Mean
41547.46
181237.7
Std. Deviation
199254.62518
1268663.906
TABLE A7: GROUP STATISTICS OF DEBT/SALES RATIO
FOR GCQ AND NGCQ GROUPS
Group Statistics
A_SALES
GCQ
yes
no
N
21
47
Mean
82.9090
44115.13
Std. Error
Mean
27.79389
42798.35
Std. Deviation
127.36760
293410.68402
TABLE A8: GROUP STATISTICS OF DEBT/TOTAL ASSET RATIO
FOR GCQ AND NGCQ GROUPS
Group Statistics
A_ASSETS
GCQ
yes
no
N
23
49
Mean
42.0087
324.8280
Std. Deviation
48.32624
1549.10382
Std. Error
Mean
10.07672
221.30055
TABLE A9: GROUP STATISTICS OF DEBT/NET PROFIT RATIO
FOR GCQ AND NGCQ GROUPS
Group Statistics
A_NP
GCQ
yes
no
N
23
49
Mean
95.0209
23099.22
Std. Deviation
1966.09276
180695.35220
Std. Error
Mean
409.95868
25813.62
TABLE A10: GROUP STATISTICS OF DEBT/TOTAL LIABILITIES RATIO FOR
GCQ AND NGCQ GROUPS
Group Statistics
A_LIAB
GCQ
yes
no
N
23
49
Mean
68.2778
392.4592
Std. Deviation
141.37395
1838.07484
Std. Error
Mean
29.47851
262.58212
TABLE A11: CROSS TABULATION OF GCQ AND FD FIRMS
FD * GCQ Crossta bula tion
GCQ
yes
FD
yes
no
Total
Count
% within FD
% within GCQ
Count
% within FD
% within GCQ
Count
% within FD
% within GCQ
no
11
21.6%
37.9%
18
38.3%
62.1%
29
29.6%
100.0%
40
78.4%
58.0%
29
61.7%
42.0%
69
70.4%
100.0%
Total
51
100.0%
52.0%
47
100.0%
48.0%
98
100.0%
100.0%
TABLE A12: CORRELATION BETWEEN FD AND GCQ
Correl ations
FD
GCQ
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
FD
1.000
.
98
-.183
.071
98
GCQ
-.183
.071
98
1.000
.
98
TABLE A13: BREAKDOWN OF GCQ FIRMS IN
DEBT AMOUNT PERCENTILE
C_DEBT * GCQ Crosstabulation
GCQ
yes
C_DEBT
25th percentile
50th percentile
75th percentile
100th percentile
Total
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
no
8
34.8%
9
39.1%
2
8.7%
4
17.4%
23
100.0%
10
20.4%
9
18.4%
16
32.7%
14
28.6%
49
100.0%
Total
18
25.0%
18
25.0%
18
25.0%
18
25.0%
72
100.0%
TABLE A14: BREAKDOWN OF GCQ FIRMS IN DEBT/SALES RATIO
PERCENTILE
C_SALES * GCQ Crosstabulation
GCQ
yes
C_SALES
25th percentile
50th percentile
75th percentile
100th percentile
Total
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
4
19.0%
5
23.8%
7
33.3%
5
23.8%
21
100.0%
no
13
27.7%
12
25.5%
10
21.3%
12
25.5%
47
100.0%
Total
17
25.0%
17
25.0%
17
25.0%
17
25.0%
68
100.0%
TABLE A15: BREAKDOWN OF GCQ FIRMS IN
DEBT/TOTAL ASSETS RATIO PERCENTILE
C_ASSETS * GCQ Crosstabulation
GCQ
yes
C_ASSETS
25th percentile
50th percentile
75th percentile
100th percentile
Total
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
5
21.7%
6
26.1%
8
34.8%
4
17.4%
23
100.0%
no
13
26.5%
12
24.5%
10
20.4%
14
28.6%
49
100.0%
Total
18
25.0%
18
25.0%
18
25.0%
18
25.0%
72
100.0%
TABLE A16: BREAKDOWN OF GCQ FIRMS IN
DEBT/NET PROFIT RATIO PERCENTILE
C_NP * GCQ Crosstabulation
GCQ
yes
C_NP
25th percentile
50th percentile
75th percentile
100th percentile
Total
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
4
17.4%
10
43.5%
7
30.4%
2
8.7%
23
100.0%
no
14
28.6%
8
16.3%
11
22.4%
16
32.7%
49
100.0%
Total
18
25.0%
18
25.0%
18
25.0%
18
25.0%
72
100.0%
TABLE A17: BREAKDOWN OF GCQ FIRMS IN
DEBT/TOTAL LIABILITIES RATIO PERCENTILE
C_LIAB * GCQ Crosstabulation
GCQ
yes
C_LIAB
25th percentile
50th percentile
75th percentile
100th percentile
Total
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
Count
% within GCQ
5
21.7%
7
30.4%
8
34.8%
3
13.0%
23
100.0%
no
13
26.5%
11
22.4%
10
20.4%
15
30.6%
49
100.0%
Total
18
25.0%
18
25.0%
18
25.0%
18
25.0%
72
100.0%
TABLE A18: CORRELATION BETWEEN OCCURRENCES OF
NEGATIVE DEBT-RELATED EVENTS AND GCQ
Correlations
GCQ
GCQ
NEWTYPE
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
-.209*
.039
98
NEWTYPE
-.209*
.039
98
1
.
98
*. Correlation is s ignificant at the 0.05 level (2-tailed).
TABLE A19: CORRELATION BETWEEN OCCURRENCES OF
COVENANT VIOLATION NEWS AND GCQ
Correl ations
CON_V IO
GCQ
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
CON_V IO
1
.
98
-.150
.140
98
GCQ
-.150
.140
98
1
.
98
TABLE A20: PERCENTAGE OF COVENANT VIOLATION NEWS
IN EACH PERCENTILE OF DEBT AMOUNT
C_DEBT * CON_VIO Crosstabulation
CON_VIO
yes
C_DEBT
25th percentile
50th percentile
75th percentile
100th percentile
Total
Count
% within CON_VIO
Count
% within CON_VIO
Count
% within CON_VIO
Count
% within CON_VIO
Count
% within CON_VIO
2
66.7%
1
33.3%
3
100.0%
no
16
23.2%
17
24.6%
18
26.1%
18
26.1%
69
100.0%
Total
18
25.0%
18
25.0%
18
25.0%
18
25.0%
72
100.0%
TABLE A21: CORRELATION BETWEEN OCCURRENCES OF
CREDIT FACILITY NEWS AND GCQ
Correl ations
GCQ
GCQ
CR_FAC
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
-.061
.552
98
CR_FAC
-.061
.552
98
1
.
98
TABLE A22: CORRELATION BETWEEN OCCURRENCES OF
DEBT NEWS AND GCQ
Correl ations
GCQ
GCQ
DE BT
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
.043
.676
98
DE BT
.043
.676
98
1
.
98
TABLE A23: CORRELATION BETWEEN OCCURRENCES OF
NOTES-RELATED NEWS AND GCQ
Correl ations
GCQ
GCQ
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
NOTES
1
.
98
.005
.965
98
NOTES
.005
.965
98
1
.
98
TABLE A24: CORRELATION BETWEEN OCCURRENCES OF
DEFAULT NEWS AND GCQ
Correl ations
GCQ
GCQ
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
DE FAULT
1
.
98
-.134
.187
98
DE FAULT
-.134
.187
98
1
.
98
TABLE A25: PERCENTAGE OF DEFAULT NEWS
IN EACH PERCENTILE OF DEBT AMOUNT
C_DEBT * DEFAULT Crosstabulation
DEFAULT
yes
C_DEBT
25th percentile
50th percentile
75th percentile
100th percentile
Total
Count
% within DEFAULT
Count
% within DEFAULT
Count
% within DEFAULT
Count
% within DEFAULT
Count
% within DEFAULT
1
16.7%
3
50.0%
1
16.7%
1
16.7%
6
100.0%
no
17
25.8%
15
22.7%
17
25.8%
17
25.8%
66
100.0%
Total
18
25.0%
18
25.0%
18
25.0%
18
25.0%
72
100.0%
TABLE A26: CORRELATION BETWEEN OCCURRENCES OF
RESTRUCTURING NEWS AND GCQ
Correl ations
GCQ
GCQ
RESTRU
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
.130
.202
98
RESTRU
.130
.202
98
1
.
98
TABLE A27: CORRELATION BETWEEN OCCURRENCES OF
WAIVER NEWS AND GCQ
Correl ations
GCQ
GCQ
Pearson Correlation
Sig. (2-tailed)
N
W AIVER Pearson Correlation
Sig. (2-tailed)
N
1
.
98
.092
.366
98
W AIVER
.092
.366
98
1
.
98
TABLE A28: CORRELATION BETWEEN OCCURRENCES OF
NEGATIVE DEBT-RELATED EVENTS AND FD
Corre lations
FD
Pearson Correlation
Sig. (2-tailed)
N
NEWTYPE Pearson Correlation
Sig. (2-tailed)
N
FD
1.000
.
98
.184
.069
98
NEWTYPE
.184
.069
98
1.000
.
98
TABLE A29: CORRELATION BETWEEN OCCURRENCES OF
COVENANT VIOLATION NEWS AND FD
Correl ations
FD
FD
CON_V IO
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
.130
.203
98
CON_V IO
.130
.203
98
1
.
98
TABLE A30: CORRELATION BETWEEN OCCURRENCES OF
CREDIT FACILITY NEWS AND FD
Correl ations
FD
FD
CR_FAC
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
.116
.255
98
CR_FAC
.116
.255
98
1
.
98
TABLE A31: CORRELATION BETWEEN OCCURRENCES OF
DEBT NEWS AND FD
Correl ations
FD
FD
DE BT
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
-.096
.347
98
DE BT
-.096
.347
98
1
.
98
TABLE A32: CORRELATION BETWEEN OCCURRENCES OF
NOTES-RELATED NEWS AND FD
Correl ations
FD
FD
NOTES
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
-.021
.840
98
NOTES
-.021
.840
98
1
.
98
TABLE A33: CORRELATION BETWEEN OCCURRENCES OF
DEFAULT NEWS AND FD
Correl ations
FD
FD
DE FAULT
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
.125
.221
98
DE FAULT
.125
.221
98
1
.
98
TABLE A34: CORRELATION BETWEEN OCCURRENCES OF
RESTRUCTURING NEWS AND FD
Correlations
FD
FD
RESTRU
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
1
.
98
-.221*
.029
98
RESTRU
-.221*
.029
98
1
.
98
*. Correlation is significant at the 0.05 level (2-tailed).
TABLE A35: CORRELATION BETWEEN OCCURRENCES OF WAIVER NEWS AND
Correl ations
FD
Pearson Correlation
Sig. (2-tailed)
N
W AIVE R Pearson Correlation
Sig. (2-tailed)
N
FD
1.000
.
98
.087
.397
98
W AIVE R
.087
.397
98
1.000
.
98
TABLE A36: T-TEST RESULT OF DEBT AMOUNT FOR FD AND NFD GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_DEBT
Equal variances
as sumed
Equal variances
not ass umed
3.897
Sig.
.052
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
1.083
70
.283
272126.64
251271.03
-229018
773270.9
.978
33.646
.335
272126.64
278200.24
-293463
837716.6
TABLE A37: T-TEST RESULT OF DEBT/SALES RATIO FOR FD AND NFD GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_SALES
Equal variances
as sumed
Equal variances
not ass umed
5.106
Sig.
.027
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
1.123
66
.265
66606.522
59289.834
-51769.5
184982.5
1.027
30.000
.313
66606.522
64869.101
-65873.8
199086.9
TABLE A38: T-TEST RESULT OF DEBT/TOTAL ASSETS RATIO FOR FD AND NFD GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_ASSETS
Equal variances
as sumed
Equal variances
not ass umed
t-test for Equality of Means
Sig.
8.068
t
.006
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
1.437
70
.155
433.2902
301.53954
-168.111
1034.692
1.283
31.025
.209
433.2902
337.69553
-255.422
1122.002
TABLE A39: T-TEST RESULT OF DEBT/NET PROFIT RATIO FOR FD AND NFD GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_NP
Equal variances
as sumed
Equal variances
not ass umed
4.909
Sig.
.030
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
.904
70
.369
31967.492
35376.746
-38589.2
102524.2
.807
31.033
.426
31967.492
39617.262
-48829.0
112764.0
TABLE A40: T-TEST RESULT OF DEBT/TOTAL LIABILITIES RATIO FOR FD AND NFD GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_LIAB
Equal variances
as sumed
Equal variances
not ass umed
t-test for Equality of Means
Sig.
7.134
t
.009
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
1.294
70
.200
464.6019
359.03465
-251.470
1180.674
1.156
31.151
.256
464.6019
401.85227
-354.820
1284.024
TABLE A41: T-TEST RESULT OF DEBT AMOUNT FOR GCQ AND NGCQ GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_DEBT
Equal variances
as sumed
Equal variances
not ass umed
3.075
Sig.
.084
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
-1.255
70
.214
-335063.8
267032.27
-867643
197515.2
-1.802
52.859
.077
-335063.8
185938.96
-708033
37905.70
TABLE A42: T-TEST RESULT OF DEBT/SALES RATIO FOR GCQ AND NGCQ GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_SALES
Equal variances
as sumed
Equal variances
not ass umed
1.847
Sig.
.179
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
-.685
66
.496
-44032.22
64295.232
-172402
84337.35
-1.029
46.000
.309
-44032.22
42798.356
-130181
42116.40
TABLE A43: T-TEST RESULT OF DEBT/TOTAL ASSETS RATIO FOR GCQ AND NGCQ GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_ASSETS
Equal variances
as sumed
Equal variances
not ass umed
2.805
Sig.
.098
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
-.872
70
.386
-282.8193
324.30471
-929.625
363.98608
-1.277
48.199
.208
-282.8193
221.52984
-728.187
162.54889
TABLE A44: T-TEST RESULT OF DEBT/NET PROFIT RATIO FOR GCQ AND NGCQ GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_NP
Equal variances
as sumed
Equal variances
not ass umed
1.887
Sig.
.174
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
-.608
70
.545
-23004.20
37821.143
-98436.1
52427.69
-.891
48.024
.377
-23004.20
25816.877
-74911.8
28903.44
TABLE A45: T-TEST RESULT OF DEBT/TOTAL LIABILITIES RATIO FOR GCQ AND NGCQ GROUPS
Independent Samples Test
Levene's Test for
Equality of Variances
F
A_LIAB
Equal variances
as sum ed
Equal variances
not ass umed
2.439
Sig.
.123
t-test for Equality of Means
t
df
Sig. (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
-.842
70
.403
-324.1814
385.23617
-1092.51
444.14796
-1.227
49.200
.226
-324.1814
264.23163
-855.120
206.75725