Management Going Concern Reporting: Impact on Investors and Auditors
Jagan Krishnan [email protected]
Jayanthi Krishnan [email protected]
Eunju (Ivy) Lee [email protected]
Temple University Department of Accounting
Fox School of Business 1801 Liacouras Walk
Philadelphia, PA 19122
Revised: September 2018
Preliminary version We appreciate the comments of workshop participants at Temple University.
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Management Going Concern Reporting: Impact on Investors and Auditors
ABSTRACT The Financial Accounting Standards Board (FASB)’s Accounting Standards Update (ASU) 2014-15 required, effective for fiscal years ending after December 15, 2016, managements to evaluate whether there is substantial doubt about the firm’s ability to continue as a going concern, and provide disclosures in financial statement footnotes. Prior to this, information about a firm’s going concern status came from its auditor, which issues a going concern modified (AGC) or “clean” audit opinion on the financial statements. We examine two research questions. First, is the new information provided by management valued by investors? We find that the earnings response coefficients for firms with clean audit opinions (including those that disclose going concern issues), but not for firms with AGCs, increased in the first year of the standard. Second, we examine whether there was a change in auditors’ reporting strategy. We find, after controlling for changes in client characteristics, that auditors became more conservative in the issuance of AGCs in the first year of the standard. Keywords: ASU 2014-15, FASB, Going Concern, Audit Opinion
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I. INTRODUCTION
Information about a company’s future survivability is important for investors and the
financial markets. Unless liquidation is imminent, US GAAP requires that corporate financial
statements be prepared under the “going concern presumption” that the company will continue to
operate.1 However, even if liquidation is not imminent, a firm can face going concern
uncertainties that would be of interest to investors. Until recently, the firm’s managers played a
relatively passive role in disclosing such uncertainties. Auditing standards require the firm’s
independent auditor to evaluate whether there is substantial doubt about its client’s going
concern ability and, in the event of an affirmative assessment, issue a going concern modified
audit opinion (henceforth AGC) (AS 2415, PCAOB 2017). When such an opinion is issued, the
SEC requires the firm to disclose the associated financial difficulties. In 2014, the Financial
Accounting Standards Board (FASB) issued Accounting Standards Update (ASU) 2014-15,
introducing an important change to firms’ going concern reporting. Management must now
evaluate whether there is substantial doubt about the firm’s ability to continue as a going
concern, and provide disclosures in financial statement footnotes.
We examine the impact of this standard in the first year of adoption.2 The FASB expects
the standard to improve financial reporting quality by “reducing diversity in the timing and
content of existing footnote disclosures for all entities” (emphasis added). Our first research
question, motivated by the FASB’s expectation, is the following: do investors perceive earnings
1 ASU 2014-15 does not define the concept of “going concern presumption.” In its 2013 Exposure draft for the standard, the Board defined it as the presumption that an entity “will continue to operate such that it will be able to realize its assets and meet its obligations in the ordinary course of business” (FASB 2013). 2 ASU 2014-15 applies to public and private entities. We focus on public entities only.
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of companies to be more credible in the first year of adoption of ASU 2014-15 (which included
both auditor and management evaluations) compared with the previous year (which included
only auditor evaluations)? We then examine a second question: did the new standard change the
auditor’s behavior in issuing an AGC? Although the FASB’s main focus in implementing this
standard is on the benefits to users of financial statements, the auditor will need to assess these
new client disclosures about going concern, while also making its own AGC decision (PCAOB
2014, Staff Audit Practice Alert No. 13). We posit therefore that auditor behavior can also be
affected by the standard. Further motivation for this research question is provided by
commenters on the exposure draft that preceded the new standard, many of whom analyzed the
potential effect on auditors. Also, the PCAOB is now reviewing and considering revisions to the
auditing standards for the going concern opinion, in light of the new FASB accounting standard.
The going concern evaluation requires considerable judgement (Carcello, Hermanson,
and Huss 1995; DeFond, Raghunandan, and Subramanyam 2002; Knechel and Vanstraelen
2007; DeFond and Zhang 2014). The FASB articulates two sources of benefits to investors from
ASU 2014-15. First, management can provide additional information about the entity’s going
concern status than that provided by auditors, particularly when the auditor does not issue a
going concern opinion in the presence of mitigating factors. To the extent that this is new
information which investors can use, it can influence investor perceptions about the companies
reporting such information. The second benefit can arise for all companies as noted in the FASB
quote above. ASU 2014-15 defines management’s responsibility to evaluate its going concern
status and provides guidance about the evaluation and disclosures. Management has private
information about the company operations, its strategy, its negotiation with lenders, and other
critical matters, which are relevant to such evaluation. The FASB expects that, because of the
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judgment needed in the GC assessment, firms may need to “implement and document underlying
processes and controls” (FASB 2014, 31). Thus, regardless of the final outcome of the going
concern judgments by the auditor, the working of the standard can engender positive investor
perceptions of change in firms’ financial reporting quality for all firms.
Under ASU 2014-15, management performs an active role in the evaluation and public
disclosure of going concern issues, compared with its previous passive role of responding behind
the scenes to its auditor’s inquiries about such issues.3 Two factors are relevant here. First, such
active involvement likely means that management is more rigorous than before in its assessment.
Since management has superior private information about the firm, this can potentially provide
both investors and auditors with greater confidence than before in their own assessments. For
investors, while the auditor’s opinion on the firm’s going concern is informative, another layer of
information provided by management can enhance the information environment.
Second, while ASU 2014-15 incorporates many of the disclosure considerations in the
auditing standard, it introduces some important differences. These include, as we discuss in more
detail later, a formal definition of “substantial doubt,” a longer forward-looking window than
that used by auditors, and the requirement that, unlike auditors, management must disclose
relevant information even when the initial substantial doubt is expected to be alleviated by
mitigating factors. Investors, who previously knew only the auditor’s binary going concern
assessment, are now provided more details about the company’s going concern status. An
example of such additional details is provided in a recent much-publicized Form 10-K filing by
3 In addition, SEC rules require disclosures by management when the auditor issues a going concern opinion. More relevant to our analyses, some managers with no auditor going concern modified opinions also disclosed going-concern-related issues prior to the new standard, in the Management, Discussion, and Analysis (MD&A) (Mayew, Sethuraman, and Venkatachalam 2015) and Risk Factors sections of their 10-Ks, but these disclosures were voluntary in nature.
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Sears for the fiscal year ended January 28, 2017. Sears disclosed that conditions suggesting
substantial doubt about going concern were mitigated by management plans. This disclosure was
accompanied by a clean audit report from Sears’ auditors, Deloitte (Steele 2017).
We hand-collect data on management disclosures for firm-years before and after the
effective date of the standard. Not surprisingly, there is considerable overlap between auditors’
and managements’ going concern assessments when the auditor issues a going concern opinion.
However, there is variation in managements’ disclosures about going concern for “clean” firms
that have not received going concern opinions from their auditors. In most cases, clean firms
have no disclosures relating to going concern (suggesting the absence of any adverse issues), or
state explicitly that they have no going concern issues. We expect that this provides a dual
assurance about clean firms, the auditor’s clean opinion being confirmed by management. This is
different from the pre-standard period when disclosures were voluntary and therefore, their
absence did not necessarily indicate the absence of going concern problems. Some firms disclose
(under ASU 2014-15) issues relating to going concern even in the absence of an auditor’s going
concern report. These provide information about management plans and factors that mitigate
initial substantial doubt judgments.
We compare investors’ responsiveness to earnings – measured by the response of stock
returns to earnings surprises (the earnings response coefficient, ERC) - in the pre-standard year
(henceforth the “PRE period”) and the post-standard year (the “POST period”). We document
the following findings. First, there is no change in the ERCs for firms with going concern audit
opinions. This is consistent with the conjecture that, due to the SEC disclosure requirements for
AGC firms, the ASU 2014-15 disclosures do not provide new information. Second, ERCs for
firms with clean audit reports (i.e., no AGC) and with management confirmation of the absence
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of going concern issues, increase in the POST period. We conjecture that this is due to the “dual
assurance” being offered in the POST period, as opposed to the single (auditor) assurance that
was offered in the PRE period. Third, we also find, interestingly, an increase in ERC for the
clean (audit opinion) firms whose management discloses going concern-related issues in the 10-
K. This suggests that investors find the information to be useful in interpreting earnings even
though the information indicates that there was an initial assessment about substantial doubt. One
potential explanation is the usefulness of information about management’s plans. ASU 2014-15
requires management to disclose plans that alleviate the initial substantial doubt about going
concern. The FASB asserts that information about management’s plans could give financial
statement users the opportunity to “evaluate the likely success of those plans in mitigating the
conditions or events that raised substantial doubt” (FASB 2014, BC36). The increase in ERC we
note above seems to support this conjecture.
In our second research question, we examine whether auditors change their going
concern reporting strategy after the adoption of ASU 2014-15. Following Francis and Krishnan
(2002) and Geiger, Raghunandan, and Rama (2005), we decompose the change in probability of
issuing a going concern opinion from the PRE to POST periods into two components: the change
attributable to auditors’ reporting strategy and change attributable to client risk characteristics.4
We find an average increase of 1.22% in the probability of auditors’ issuance of a going concern
report. However, we are interested in whether auditors’ reporting strategy changed from the PRE
to POST periods. Decomposition of the overall change in probability into its two components
4 This methodology (i.e., the decomposition of a change in probability into components) is drawn from studies in labor economics (e.g., Farber 1990).
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reveals that there is a 0.16% increase on average due to change in auditors’ reporting strategy,
after controlling for changes in client characteristics. This suggests that auditors became more
conservative in issuing a going concern report.5 Moreover, the number is economically
significant, given a going concern rate of 5.5% in the PRE period. Interestingly, this increased
conservatism is more marked for firms with no management assertions about going concern
issues. We offer two explanations for this increased conservatism: (a) auditors face more scrutiny
from regulators and more attention from financial statement users in the first year of adoption of
the standard, and (b) auditors have less pressure to avoid issuing a going concern opinion to keep
the client when management is also responsible for going concern disclosures.
Overall, we conclude that ASU 2014-15 increased the informativeness of reported
earnings but also induced greater conservatism in auditors. The standard appears to have been
effective in the first year of adoption at least in terms of providing useful information to the
market. However, the change in auditor’s reporting strategy seems to be an unexpected
consequence of the new policy. At this point, it is unclear whether the increased conservatism of
auditors suggests more accurate going concern assessments or overly conservative decisions.
Our study makes the following contributions. First, we provide detailed descriptive
analyses of managements’ disclosure pursuant to the new standard. Second, we provide some
preliminary assessments of the impact of the standard. We contribute specifically to the debate
on the potential usefulness of mandating management going concern assessments by
documenting increase in earnings informativeness, and to the more general subject of the
5 This is based on the full sample of all firms. We also conduct a similar analysis for financially distressed firms. For the distressed sample, we find a 3.26% overall increase in the probability of issuance of a going concern opinion, 0.40% due to change in auditor reporting strategy and 2.86% due to change in client risk characteristics.
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usefulness of FASB’s standards (Khan, Li, Rajgopal, and Venkatachalam 2017). Third, we
contribute to the literature on the auditor’s going concern decision (Mutchler, Hopwood and
McKeown 1997; Behn, Kaplan, and Krumwiede 2001; Myers, Schmidt, and Wilkins 2014) by
suggesting that the management’s disclosure may become an important input into the decision.
We note one caveat to our study. In 2015, the PCAOB introduced a new regulation
requiring auditors to disclose the names of engagement partners on audits in a new Form AP
(PCAOB’s Release No. 2015-008, PCAOB 2015). This rule became effective for audit reports
issued on or after January 31, 2017. The PCAOB expects these disclosures to increase
“transparency and accountability for key participants in the audit.” Because the timing of the
Form AP rule coincides with that of ASU 2014-15, we must consider its potential confounding
effects for our analyses. A priori it is not clear that the first-time partner disclosures could affect
overall investor perceptions about financial reporting. These disclosures are expected to become
useful over time as a partner’s past performance becomes available.6 It seems unlikely therefore
that our investor perception results are affected by the new partner disclosures. However, if the
expectation of disclosure of their names causes engagement partners to become conservative in
their going concern decisions, our conservatism results could reflect the joint effect of ASU
2014-15 and the Form AP disclosures. While we acknowledge this possibility, the differences in
our results for different types of management disclosures suggests that ASU 2014-15 has some
effects that are separate from those of Form AP.
The next section discusses background and hypotheses development. Sections 3 and 4
6 At the time of the release of the final rule, PCAOB Board member Jay Hanson remarked “… over time, coupled with information about the partners' experience and history, making [partner identity information] available to investors may incrementally increase their ability to make judgments about audit quality, and, by extension, the credibility of financial statements.”
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present research design and results of our first and second research questions, respectively. Our
conclusions appear in section 5.
II. BACKGROUND AND HYPOTHESES DEVELOPMENT
The Auditor’s Going Concern Opinion
An auditor’s going concern opinion decision follows several steps. Auditing Standard
2415 (SAS No. 59 prior to reorganization by the PCAOB) requires auditors to first evaluate,
based on the audit procedures conducted during the audit, whether there is “substantial doubt”
about the client’s ability to continue as a “going concern” within a reasonable period not to
exceed one year from the date of the financial statements. The concern about substantial doubt
arises if the auditor identifies negative conditions and events (for example, work stoppages and
legal proceedings) which, when viewed in aggregate, raise the possibility that the client may not
survive beyond 12 months from the year end.7
If the evaluation suggests that there could be substantial doubt, the auditor obtains
management plans to address the doubts about survival. If, again in the auditor’s assessment, the
management’s stated plans can be effectively implemented and might alleviate the concerns
about substantial doubt, the auditor would not issue a going concern modified opinion, but
“should consider the need for disclosure of the principal conditions and events that initially
caused him to believe there was substantial doubt” (AS 2415). In practice, auditors have not
typically included disclosures when not issuing an AGC. In the absence of such perceived
alleviation, the auditor issues a going concern modified opinion, which is an audit report
7 See Carson, Fargher, Geiger, Lennox, Raghunandan, and Willekens (2013) for a research synthesis of going concern literature.
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including an explanatory paragraph, containing the phrases that includes the terms "substantial
doubt” and “going concern.”
Management’s Responsibility to Assess Going Concern Status
In 2014, the FASB instituted ASU 2014-15. This new standard was a culmination of
repeated attempts by the FASB to include “guidance on the preparation of financial statements as
a going concern and on management’s responsibility to evaluate and disclose uncertainties about
an entity’s ability to continue as a going concern” in US GAAP (FASB 2014). The ASU 2014-15
requirements, while generally similar to the requirements in the auditing standard for the AGC,
nevertheless have some new features. ASU 2014-15 requires management to consider whether
there is substantial doubt about survival and, if the initial assessment suggests the possibility of
substantial doubt, to assess if management plans could be implemented effectively and could
alleviate the substantial doubt. While this is similar to the auditing standards, there are two
important differences. First, the period for the assessment is 12 months beyond the date of
issuance, or date available for issuance, of the financial statements. This is longer than the
auditor’s look-forward period, 12 months beyond the balance sheet date. Second, the auditing
standard does not have a clear definition of substantial doubt. ASU 2014-15 states that
substantial doubt exists when “it is probable that an entity will be unable to meet its obligations
as they become due within one year after the date that the financial statements are issued” (FASB
2014; Booker and Booker 2016). The definition of “probable” (i.e., a future event is likely to
occur) is intended to be consistent with ASC 450, Contingencies.
If the plans are determined to not alleviate the substantial doubt, management must
disclose that there is substantial doubt about survival, its evaluation about conditions and plans,
and whether financial statements are prepared on a going concern basis (FASB 2014). However,
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even if the plans are determined to alleviate substantial doubt, ASU 2014-15 requires extensive
disclosures that are not required for the auditor: the principal conditions or events that raised
substantial doubt, management’s evaluation of the significance of those conditions or events in
relation to the entity’s ability to meet its obligations, and the plans that are expected to alleviate
the doubt.
Investors’ Response to the New Standard
Because ASU 2014-15 is a FASB standard, its direct target is financial reporting quality
and not audit quality. FASB standards have the general goal of improving “financial accounting
and reporting standards to provide useful information to investors and other users of financial
reports.” Specifically, for ASU 2014-15, the goal is to improve financial reporting quality by
ensuring that the entity’s adoption of the going concern presumption is appropriate, and that
appropriate disclosures about going concern issues are provided.
Although a majority of the attention on the standard has focused on the disclosures by
entities with substantial doubt concerns, the standard applies to all entities. In its discussion of
the standard, the FASB describes two benefits for all entities. First, the standard describes
management’s responsibility to evaluate and disclose “uncertainties about an entity’s ability to
continue as a going concern,” which is a critical presumption for preparing financial statements
under GAAP for all entities. Second, by providing a definition for “substantial doubt,” the
standard is expected to reduce diversity in the “timing and content of existing footnote
disclosures for all entities.” Although viewed as a cost of implementing the standard, the Board
also expects that, because of the significant judgments involved in the evaluation, entities may
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need to implement and document underlying processes and controls.8 This too can add to the
effectiveness of management assessments of going concern.
Thus, financial reporting quality can improve for all entities because their management
has systematically evaluated the going concern presumption, possibly instituting new controls,
procedures and monitoring.9 Although the FASB does not discuss implications for auditing,
comments on the ASU 2014-15 exposure draft suggest that an additional layer of rigor can also
occur because the auditor must in turn audit these changes to the reporting process and footnote
disclosures. Further, although auditors are not required to audit the MD&A, they must read the
new information arising from the standard, to ensure consistency with the information in the
financial statements (Cohen, Gaynor, Holder-Webb, Montague 2008).
We examine whether the market perceives an improvement in financial reporting quality,
thus responding more positively to earnings surprises in the POST period compared with the
PRE period. Earnings reports are valued by investors when the reported numbers “more
accurately reflect true economic value” (Teoh and Wong 1993). Other things equal, the earnings
response coefficient, is positively associated with the precision in the earnings number
(Holthausen and Verrecchia 1988). Thus, financial reporting changes that can be expected to
signal greater precision in the earnings number can increase the earnings response coefficient
8 The accounting firm Ernst & Young notes that, management will need to “evaluate whether it has adequate processes and internal controls in place to comply with the going concern requirements” (EY 2017). 9 Some commenters provided similar views. For example, “… we support the proposed amendments and believe that they will improve the quality of financial reporting about going concern matters. As a result, we believe users of financial statements will have access to more timely and decision-useful information” (BDO). “… we believe the users of financial statements will be provided a clearer understanding of the events or conditions that may impact an entity’s ability to continue as a going concern as well as management’s plans to mitigate those conditions and events at an earlier stage than under the current auditor driven model” (McGladrey).
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(Teoh and Wong 1993; Hackenbrack and Hogan 2002). Hackenbrack and Hogan (2002) argue,
for example, that certain types of auditor changes can signal greater precision, engendering a
higher ERC after the auditor change. Similarly, Chen, Krishnan, Sami, and Zhou (2013) find that
there was an increase in ERC in the first year of implementation of internal control audits for
firms that did not have internal control material weaknesses. The inference is that the market
perceived the internal control audits as having improved the quality of financial information
presented by the firm. The critical question is whether investors perceive ASU 2014-15 as
generating a higher quality of information. We distinguish between firms that receive AGCs and
clean opinions from their auditors.
AGC Firms
For AGC firms, the auditor follows auditing standards to conclude that there is
substantial doubt about survivability that is not alleviated by management plans. Management is
required by Securities and Exchange Commission (SEC) rules, but not (prior to ASU 2014-15)
by the FASB, to provide disclosures when the auditor issues an AGC.10 The filings including the
AGC should also include “appropriate and prominent disclosure of the financial difficulties
giving rise to that uncertainty” and a discussion of a viable plan that has the “capability of
removing the threat to the continuation of the business” and can “enable the issuer to remain
viable for at least the 12 months following the date of the financial statements being reported on
must be included” (SEC 2017). The FASB believes that the lack of guidance in GAAP led to
10 The SEC’s Financial Reporting Manual (SEC 2017) states the following: “Filings that include reports having going concern modifications must also include appropriate and prominent disclosure of the financial difficulties giving rise to that uncertainty. Discussion of a viable plan that has the capability of removing the threat to the continuation of the business must be included. The plan may include a “best efforts” offering so long as the amount of minimum proceeds necessary to remove the threat is disclosed. The plan should enable the issuer to remain viable for at least the 12 months following the date of the financial statements being reported on.”
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considerable diversity in whether, when, and how an entity discloses the relevant conditions and
events in its footnotes.
As discussed, ASU 2014-15 provides more detailed guidance than the SEC about firm
disclosures. Thus any change in investors’ perceptions due to the new standard depends on
whether it provides new information in the first year compared with the previous year. The
FASB notes that the new standard may not “result in new information in many audited financial
statements because the amendments are similar to current U.S. auditing standards” (emphasis
added). This may be particularly true for AGC firms because of the SEC-mandated disclosures
discussed above which were in place in the pre-ASU 2014-15 period. Effectively, the ERC for
the PRE period is based on the AGC and SEC-mandated disclosures, while the ERC in the POST
period is based on the AGC, the SEC-mandated disclosures, and any new disclosures arising
from ASU 2014-15. Because of the existence of some mandated disclosures in the PRE period,
we state our first hypothesis in null form:
H1: ERCs for firms with going concern opinions will not be different in the first post-ASU2014-15 year from that in the previous year.
Non-AGC Firms
For the clean opinion firms, the absence of an AGC in the PRE period provided assurance
of the absence of going concern problems. Under ASU 2014-15, investors have, in addition,
management’s proactive assessment of going concern, possibly after institution of
processes/controls to facilitate this assessment. Such assessment provides an increase in
information which may be viewed positively because it reduces information asymmetry. If so,
the ERC can increase in the post-ASU 2014-15 year. However, the content of the information
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can also influence investor response. Consequently, we develop two hypotheses below for firms
with clean audit opinions.
ASU 2014-15 requires detailed disclosures when the initial assessment raises concern
about substantial doubt that are subsequently found to be alleviated by management plans. As we
discuss in the next section, the non-AGC companies fall into two broad categories, those that (1)
have no going concern disclosures or state explicitly that they have no going concern issues and
(2) describe the nature of the substantial doubt, management plans, and the basis for judging that
the substantial doubt is alleviated. In contrast, clean companies in the PRE period were not
required to make any disclosures. Consequently, there were relatively few voluntary disclosures
by clean companies regarding going concern issues in the PRE period.
For group (1), investors are essentially provided a double assurance in the POST period
that the firm is “clean” because the auditor did not issue a going concern opinion and the
management confirms the absence of going concern issues in the near future. In contrast, only
the auditor provided the assurance in the PRE period. Therefore, we posit that investors are more
confident that clean firms are in fact free of going concern uncertainties. The double assurance
can increase the precision of the earnings number (Teoh and Wong 1993). As a result, we expect
the earnings of these clean firms to be more informative in the POST period. Our second
hypothesis is as follows:
H2: ERCs for firms with no auditor going concern opinions and with no negative management disclosures regarding going concern will be higher in the first post-ASU 2014-15 year than in the previous year.
We acknowledge however that there are counter arguments. First, the evaluation of
whether there is substantial doubt involves significant judgement because it is based on
qualitative and quantitative factors. Thus managers may not disclose going concern issues
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because they regard a potentially significant problem as not significant. Second, managers have
incentives to hide or delay bad news due to career concerns (Kothari, Leone, and Wasley 2005).
For example, the empirical evidence from Canada and U.K., where management is required to
disclose going concern issues, indicates that the proportion of firms that report going concern
uncertainties is quite small, and the information disclosed by the management is not
incrementally useful (Uang et al. 2006; Ontario Securities Commission 2010). If the market
considers it likely that firms would not disclose all the relevant information even when required
to do so, the new policy may not change the market’s perception of earnings informativeness,
and there would be no change in ERC in the POST period. Third, the threshold requiring the
disclosure about going concern uncertainty only when it is probable (i.e., the future event or
events is likely to occur) may be too high to reveal any new information about the uncertainty as
investors are likely to have already known about it.11
For group (2) above, disclosures in the POST period provide information relating to
going concern problems. In the PRE period, investors knew only the outcome of the auditor’s
going concern evaluation process. If the auditor decided to not issue a going concern opinion
after incorporating management’s plans, investors simply saw the absence of a going concern
opinion without knowing the underlying contextual details, unless management provided
voluntary disclosures. Mayew et al. (2015) document that some firms discussed going concern
issues in their MD&As, and this disclosure has incremental predictive ability for bankruptcy
11 Board Member Thomas Linsmeier voted against the ASU 2014-15 proposal, arguing that “by requiring disclosure only when it is probable that an entity will be unable to meet its obligations as they become due within one year after the date the financial statements are issued (or available to be issued), the guidance in this Update will provide information about going concern uncertainties that is too late to be of significant benefit to users of financial statements” (FASB 2014).
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even after controlling for the auditor opinion.12 Therefore, if firms have already disclosed
sufficient information in their MD&As or elsewhere in the 10-K, ASU 2014-15 may not provide
new information. However, the proportion of voluntary going concern disclosures in the MD&A
for clean companies in Mayew et al. (2015) is small. Because the disclosures are now mandatory
(rather than voluntary), and the new policy would likely have legal consequences if management
does not comply with it, it is reasonable to expect that firms are more likely to disclose going
concern information in the POST period than in the PRE period.
Even if management’s disclosures provide new information, the “bad news” nature of
these disclosures might lower ERC. For example, Choi and Jeter (1992) and Dong, Robinson,
and Robinson (2015) document lower ERCs for firms with qualified/going concern audit
opinions. Therefore, although we expect the new policy to provide new information to the
market, whether this information would change market’s valuation of non-AGC firms’ earnings
is an empirical question. Accordingly, our third hypothesis is in null form:
H3: For the firms whose managements discuss going concern issues when the auditor does not issue a going concern opinion, there is no change in ERCs in the first post-ASU2014-15 year from the previous year.
Auditors’ Response to the New Standard
The auditor’s going concern opinion decision is complex, and characterized by grey areas
requiring judgment (Carcello and Neal 2000; Goh, Krishnan, and Li 2013; Carson et al. 2013).
Specifically, auditors can be viewed as determining a range of financial distress over which an
AGC can be issued, and choosing a “threshold” above which to issue it. Researchers have argued
12 Specifically, the proportion of voluntary disclosures in Mayew et al. (2015) is only about 0.2 percent when the auditor does not issue a going concern opinion. In our sample, 2.6% of firms with no AGCs in the POST period disclosed going concern issues.
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that, given the judgement needed in the process, auditors may move the threshold in response to
different factors. Lowering (raising) the threshold would result in a higher (lower) probability of
issuing a going concern opinion, other things equal. Francis and Krishnan (1999) argue that
uncertainties relating to estimating accruals causes a lowering of the threshold engendering
“reporting conservatism.” Similarly, Goh et al. (2013) argue that the existence of internal control
material weaknesses increases the auditor’s uncertainty surrounding the substantial doubt
assessment, causing it to lower its threshold for the going concern opinion, other things equal.
Blay (2010) argues that the fear of losing a client, other things equal, makes the auditor less
conservative. In addition to responding to uncertainties surrounding the required assessments,
auditors may also move the threshold in response to regulatory changes. For example, the
passage of the Private Securities Litigation Reform Act of 1995 relieved litigation pressure on
auditors, possibly making them less conservative than before (Francis and Krishnan 2002;
Geiger and Raghunandan 2002).
Prior to ASU 2014-15, management plans were incorporated in the auditor’s going
concern decision, but the plans were proffered to the auditor in response to the latter’s expressed
concerns about substantial doubt. The important question is whether the active role forced on
management by the new standard is likely to affect the auditor’s going concern opinion decision.
We posit that several forces may be at work. First, auditors are aware that management must
assess its going concern status, and report it. This can result in greater faith in the information
provided by management, thus moving the threshold to the right (i.e., less conservatism).
Second, auditors will face more scrutiny from regulators (i.e., SEC, PCAOB) and more attention
from the financial statement users in the first year of adoption of a new standard. It is likely that
standard setters will pay more attention to going concern assessments to evaluate the efficacy of
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the standard and to ensure that firms are applying the new standard appropriately. Such
heightened scrutiny could cause auditors to become more conservative. Further, some
commenters responding to 2013 exposure draft expressed the concern that the new management
disclosures can increase auditors’ litigation exposure. Third, we conjecture that auditors now
have less pressure to avoid issuing a going concern opinion for fear of losing the client because
managements are also responsible for disclosing going concern issues. That is, auditors that may
have delayed disclosing bad news (i.e., issuing a going concern opinion) to please the client
would feel free to issue a going concern opinion without worrying about losing the client
particularly if the client is forced to disclose problems on its own. This would increase reporting
conservatism.
Given the conflicting predictions, we state our fourth hypothesis in the null form.
H4: After controlling for change in client characteristics, auditors’ reporting conservatism is not different in the first post-ASU2014-15 year compared with the previous year.
III. INVESTOR PERCEPTIONS IN THE PRE- AND POST-PERIODS
Management Disclosures pertaining to Going Concern
ASU 2014-15 became effective for fiscal years ending after December 15, 2016, and for
annual periods and interim periods thereafter. We assemble a sample of PRE and POST firm-
year observations using December 15, 2016 as the cutoff. Because of the fairly intense data
coding that is required, we confine our sample to observations that were available on the date
that we started the process, July 1, 2017. We started with all observations that were available for
year ends from November 1, 2015 to January 31, 2017. Fiscal years ending between November
1, 2015 and December 15, 2016 comprise the PRE period, and fiscal years ending between
December 16, 2016 and January 31, 2017 comprise the POST period.
20
Table 1 presents our sample selection procedure. We start with 12,282 firm-year
observations available in Audit Analytics for the PRE and POST periods. We then eliminate (1)
1,419 observations that relate to funds or trusts, use non-U.S. GAAP, or have missing SIC Codes
and (2) 6,252 observations due to unavailability of data on Compustat, CRSP, and/or IBES. This
results in 4,611 firm-year observations comprising 2,328 observations for the PRE period and
2,283 observations for the POST period.
Next, we hand-collected data on management disclosures about going concern from 10-K
filings for every firm-year in the sample. While the POST period had mandatory disclosure
requirements, Mayew et al. (2015) document that managers provided voluntary disclosures
relating to going concern (during 1995-2012) in the MD&A sections of their Form 10-K filings.
Because our empirical models are intended to capture changes in investor perceptions from the
PRE to the POST periods, we examine 10-K filings in both periods to document the disclosures.
Using Python, we conducted keyword searches for phrases such as “substantial doubt” and
“going concern.”13 We classified the observations into five groups, those with (1) explicit
statements that they had no GC issues (MExpNoGC), (2) no explicit statement about the
presence or absence of going concern issues, which we interpret as indicating the absence of GC
issues (MSilent)14, (3) “mild” suggestions of GC problems (MildMGC), (4) discussions about
13 Two authors were involved in coding the disclosures. We read each paragraph that contained the phrase “going concern.” Many of these paragraphs did not in fact pertain to going concern problems. For example, many companies use the phrase “going concern” when referring to the new standard. Consequently, a large number of “going concern” phrases were eventually not used in the coding of going concern assessments by management. Where there were differences between the authors in coding, they were reconciled through discussion. 14 A number of firms mention ASU 2014-15 and state that its adoption had no material effect on their financial statements. Since this is not an explicit statement about the absence or presence of going concern issues, we code these observations as silent.
21
GC concerns and mitigating factors (MGCMit) that alleviate the substantial doubt, and (5)
explicit statements about substantial doubt relating to going concern (MGCExp).15 A “mild”
suggestion of GC arises when a firm uses modal words (e.g., “may” or “could”) or conditional
sentences in stating its going concern issues.16
Table 2, Panel A shows the frequency of the management disclosure groups, cross-
classified by AGC, for the combined sample of PRE and POST period firm-years. Not
surprisingly, managements’ explicit statements about substantial doubt overlaps almost
completely with auditors’ issuance of AGCs. Of the 110 firms with auditors’ AGCs, the
management of 103 firms also explicitly acknowledge going concern problems. Of the remaining
seven firms, six acknowledge going concern issues somewhat mildly (MildMGC) and one
(which belongs to the PRE period) had no comments about going concern (MSilent).
Among the 4,501 clean firm-year observations that did not receive an auditor’s going
concern opinion, managements’ disclosures vary. A majority (4,299) of them fall in the
“MSilent” group, and 101 firms belong to the MExpNoGC group, stating explicitly that the firm
has no going concern issues. We find 86 firms with mild acknowledgment of going concern
15 MGCExp firms: “These raise substantial doubt regarding our ability to continue as a going concern”; “There is substantial doubt about its ability to continue as a going concern.” The structure and content of going concern statement made by the management is almost identical to the going concern statements included in the auditor’s report. 16 Some examples of MildGC: “If the condition were to persist for any appreciable period of time, our viability as a going concern could be threatened.”; “Our ability to continue as a going concern is dependent upon our ability to obtain additional equity or debt financing.”
22
problems, and 12 firms disclosing going concern problems but with mitigating plans to alleviate
the problems.17 Three explicitly mention going concern problems.18
In Table 2, Panel B, we focus on clean firms, (AGC=0) and present the distribution of
management going concern disclosures for the PRE and POST periods separately. Although the
individual numbers are small, the changes from the PRE to POST years reflect the effect of the
new standard. First, the MSilent category decreased from 97.5% to 93.5%.19 Although this
category dominates in both years, the introduction of ASU 2014-15 provides a different
interpretation for MSilent in the PRE and POST periods. In the PRE period, investors were not
able to draw any inferences from the lack of disclosure about the going concern issues in the 10-
Ks. In the POST period, however, management is required to assess going concern and disclose
where needed. Thus, no disclosure in the POST period actively implies the absence, in
management’s judgment, of going concern issues.
Second, although the number of observations with any kind of management going
concern disclosure is not large, the standard elicited specific statements, for example about the
17 ASU 2014-15 says: “If, after considering management’s plans, substantial doubt is alleviated as a result of management’s plans, management must disclose conditions that raised substantial doubt as well as management’s plans that alleviated substantial doubt in the footnotes” (205-40-50-12); “If, after considering management’s plans, substantial doubt is not alleviated, management must include a statement in the footnotes indicating that there is substantial doubt about the entity’s ability to continue as a going concern” (205-40-50-13). Therefore, some firms may have mitigating plans which are not sufficient enough to alleviate adverse conditions and thus still state going concern problems. These firms will fall within the MGCExp group rather than within “MGC with Mitigating Factors.” 18 The three firms include the following sentences in their 10-Ks: (1) “Our recurring losses from operations have raised substantial doubt regarding our ability to continue as a going concern”; (2) “our planned operations raise doubt about our ability to continue as a going concern”; (3) “the company’s planned operations raise doubt about its ability to continue as a going concern.” 19 We considered whether the observations including some form of going concern disclosures were the result of early adoption of the standard. Five firms mention that they adopt the standard early. Others made no mention of early adoption of the standard, making it likely that they are voluntary disclosures.
23
absence of going concern issues, or about management plans and mitigating factors, which were
not available in the PRE period. Overall, these specific disclosures increased from 2.5% to 6.5%.
The proportion of firms explicitly stating the absence of going concern increased from 0.57% to
3.96%, and the proportion of firms explicitly disclosing some going concern issues (mild, with
mitigation, or unalleviated substantial doubt) increased from 1.93% in the PRE period to 2.57%
in the POST period. The proportion of disclosures for “MGC with mitigating factors” (MGCMit)
increased significantly after ASU 2014-15 became effective (from 0 to 0.54%), and we
conjecture that this is a major change introduced by the new policy.20 Unfortunately, the small
number of observations restricts our ability to conduct meaningful statistical tests for each
category. Consequently, in the regressions reported later, we combine these three groups into one
group (MGCALL).
Location of Disclosure
ASU 2014-15 requires disclosure about going concern problems in the footnotes.
However, information about going concern issues also appear in other sections of Form 10-K,
especially in the Risk Factors and MD&A sections.21 Table 2, Panel C provides information
about the location of the disclosures. For the companies with auditor going concern opinion
20 The Sears example discussed earlier falls in the “MGC with Mitigating Factors” (MGCMit) group. “…We believe that the actions discussed above are probable of occurring and mitigating the substantial doubt raised by our historical operating results and satisfying our estimated liquidity needs 12 months from the issuance of the financial statements.” Sears’ auditor, Deloitte, did not issue an AGC, possibly because the substantial doubt was alleviated. Thus, management disclosure provides additional information to investors. 21 The FASB included question 7 in its 2013 exposure draft for ASU 2014-15, specifically seeking comments about the location of the disclosures in the 10-K: “For SEC registrants, would the proposed footnote disclosure requirements about going concern uncertainties have an effect on the timing, content, or communicative value of related disclosures about matters affecting an entity’s going concern assessment in other parts of its public filings with the SEC (such as risk factors and MD&A)? Please explain.”
24
(AGC=1), footnote disclosures dominate in both periods (91.5% and 100% in the PRE and
POST periods respectively) possibly because of the SEC requirement. However, among AGC=0
companies, there is a distinct increase in footnote disclosures in the POST period. Where
management explicitly states that there are no going concern problems, 84.6% of the disclosures
in the PRE period and 99% in the POST period appear in the footnotes. Among the clean
(AGC=0) companies with some going concern problems, 9.1% provide footnote disclosure in the
PRE period. The corresponding percentage for the POST period is 35.1%.
Empirical Model
We examine if the adoption of ASU 2014-15 enhanced investors’ perceptions about
financial reporting quality, leading them to re-evaluate the quality of reported earnings. We
estimate the earnings response coefficient (ERC), the market’s responsiveness to earnings
announcements by the slope coefficient in a regression of unexpected returns on unexpected
earnings (see for example, Balsam, Krishnan, and Yang 2003; Francis and Ke 2006; Baber,
Krishnan, and Zhang 2014).
The basic ERC model is as follows:
𝐶𝐶𝐶𝐶𝐶𝐶 = 𝛽𝛽0 + 𝛽𝛽1𝑈𝑈𝑈𝑈 + � 𝛽𝛽𝑘𝑘𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐7
𝑘𝑘=2+ � 𝛽𝛽𝑘𝑘 𝑈𝑈𝑈𝑈 ∗ 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
13
𝑘𝑘=8+ 𝜀𝜀 (1)
where CAR is the three-day cumulative abnormal return around the earnings announcement date,
and UE is a measure of earnings surprise.22 The earnings announcement date is for the first
quarter following the 10-K filing in which the management disclosures (voluntary in the PRE
period and mandatory in the POST period) are included. The parameter 𝛽𝛽1 is the coefficient of
22 We use an event study design with three-day cumulative returns rather than a long-term association study design because our goal is to investigate the information content of earnings announcement rather than value-relevance (Collins and Kothari 1989; Hackenbrack and Hogan 2002).
25
interest, namely the earnings response coefficient. CAR is computed as the common stock return
less the value-weighted market return summed over the three-day period centered on the
earnings announcement date UE is earnings per share less the most recent analyst forecast
deflated by the beginning stock price for the first quarter.
Earnings Responsiveness to Auditors’ Going Concern opinion in the PRE and POST Periods
In order to compare the ERCs of going concern firms and clean firms (hypotheses H1), we
extend the model to estimate ERC for each group:
𝐶𝐶𝐶𝐶𝐶𝐶 = 𝛼𝛼0 + 𝛼𝛼1𝑈𝑈𝑈𝑈 ∗ 𝐶𝐶𝐴𝐴𝐶𝐶 + 𝛼𝛼2𝑈𝑈𝑈𝑈 ∗ 𝐶𝐶𝐶𝐶𝑐𝑐𝐴𝐴𝐴𝐴𝑐𝑐 + � 𝛼𝛼𝑘𝑘𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐9
𝑘𝑘=3+ � 𝛼𝛼𝑘𝑘𝑈𝑈𝑈𝑈 ∗ 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
15
𝑘𝑘=10+ 𝜐𝜐 (2)
where AGC indicates firm-year observations with auditor going concern opinions. AClean
indicates firm-year observations that did not receive going concern opinions from the auditors.
Control variables are discussed below.
The coefficients 𝛼𝛼1 and 𝛼𝛼2 indicate the mean ERC for the AGC and AClean groups,
respectively. Since our goal is to compare ERCs for the PRE period and POST periods, we
estimate model (2) separately for the PRE and POST periods and examine differences in
coefficients between the two periods.23 Specifically, the difference in 𝛼𝛼1 between the PRE and
POST periods indicates whether the ERC for AGC firms change. Hypothesis H1 predicts no sign
for the difference in 𝛼𝛼1.
Next, to test hypotheses H2 and H3, we examine whether the ERC changes for firms with
different management going concern disclosures. We restrict this analysis to clean firms because,
as discussed, there is an almost-complete overlap between the auditor’s going concern opinion
and management’s substantial-doubt going concern disclosures. We use two types of
23 Thus the model allows all the coefficients to vary across the two periods.
26
classifications for management going concern disclosures for clean firms. First, we classify
management going concern disclosures into two groups: MCLEAN and MGCALL (see Table 2
Panel A). MCLEAN indicates that the management explicitly states that the firm does not have
going concern problems or that the management does not discuss going concern-related issues in
the 10-K. MGCALL indicates firms where the management discloses going concern issues
mildly, in conjunction with mitigating factors, or as an assertion that substantial doubt exists.
The corresponding ERC model is as follows:
𝐶𝐶𝐶𝐶𝐶𝐶 = 𝛿𝛿0 + 𝛿𝛿1𝑈𝑈𝑈𝑈 ∗ 𝑀𝑀𝐶𝐶𝑀𝑀𝑈𝑈𝐶𝐶𝑀𝑀 + 𝛿𝛿2𝑈𝑈𝑈𝑈 ∗ 𝑀𝑀𝐴𝐴𝐶𝐶𝐶𝐶𝑀𝑀𝑀𝑀 + � 𝛿𝛿𝑘𝑘𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐9
𝑘𝑘=3+ � 𝛿𝛿𝑘𝑘 𝑈𝑈𝑈𝑈 ∗ 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
15
𝑘𝑘=10+ € (3)
In model (3), 𝛿𝛿1 indicates the mean ERC for the MCLEAN group while 𝛿𝛿2 indicates the mean
ERC for the MGCALL group. As before, we run model (3) separately for the PRE and POST
periods and compare the coefficients on the two interaction terms between the two periods.
Hypothesis H2 predicts a higher 𝛿𝛿1 in the POST period compared with the PRE period, and
Hypothesis H3 yields no prediction for the direction of change in 𝛿𝛿2.
For our second classification, we separate the MCLEAN group into two subgroups,
MExpNoGC, the firms which state explicitly that they have no going concern issues, and
MSilent, the firms that have no going concern disclosures.24 The corresponding ERC model for a
three-way classification is as follows:
𝐶𝐶𝐶𝐶𝐶𝐶 = 𝛾𝛾0 + 𝛾𝛾1𝑈𝑈𝑈𝑈 ∗ 𝑀𝑀𝑈𝑈𝑀𝑀𝑀𝑀𝑀𝑀𝑐𝑐𝐴𝐴𝐶𝐶 + 𝛾𝛾2𝑈𝑈𝑈𝑈 ∗ 𝑀𝑀𝑀𝑀𝑀𝑀𝑐𝑐𝐴𝐴𝑐𝑐𝑐𝑐+𝛾𝛾3𝑈𝑈𝑈𝑈 ∗ 𝑀𝑀𝐴𝐴𝐶𝐶𝐶𝐶𝑀𝑀𝑀𝑀 + � 𝛾𝛾𝑘𝑘𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐11
𝑘𝑘=4
+ � 𝛾𝛾𝑘𝑘𝑈𝑈𝑈𝑈 ∗ 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐17
𝑘𝑘=12+ 𝜉𝜉 (4)
24 These include firms that refer to the standard and state that its adoption had no material effects on their financial statements. We refer to them as “silent” to distinguish them from the firms that state explicitly that they do not have any going concern issues.
27
Similar to models (2) and (3), we run model (4) for the PRE and POST periods separately and
compare the ERCs of different management going concern disclosure groups for the two periods.
Based on previous studies, we include the following control variables in the model: book
to market ratio (BM) (Collins and Kothari 1989), firm size, measured by the logarithm of the
market value of common equity (LNMV), firm beta (BETA) to proxy for systematic risk (Baber
et al. 2014), leverage (LEV) measured by the debt to assets ratio (Easton and Zmijiewski 1989),
a dummy variable that indicates clients of large auditors (BIG7), and a dummy variable LOSS
(Hayn 1995; Hackenbrack and Hogan 2002) to indicate either a negative net income or negative
cash flows from operations. We include main effects for control variables and their interactions
with earnings surprise (UE) because the control variables can engender cross-sectional
variability in ERCs.
Empirical Results
Table 3, Panel A provides descriptive statistics. All continuous variables are winsorized
at the 1 percent and 99 percent levels. Columns 1-2 report the means and medians for the PRE
sample and the POST sample respectively. Column 3 presents statistics for testing differences in
means and medians across the two periods. Our main variables of interest, CAR and UE, do not
show significant change from the PRE to POST periods. The means (medians) for firm size
(LNMV), leverage (LEV) and systematic risk (BETA) are higher in the POST period than in the
PRE period. The book to market ratio (BM) is lower in the POST period than in the PRE period.
Panel B of Table 3 presents pairwise Pearson correlations among the main variables. None of the
correlations exceeds 0.5 (or -0.5).
Table 4 reports the results of estimating equation (2) to examine changes in ERC between
the PRE and POST periods for the AGC and AClean firms. Panel A shows the regression
28
estimates, and Panel B shows the resulting (incremental) ERC estimates for subgroups, holding
all other variables constant. Columns (1) and (2) in Panel A show the model estimates for the
PRE and POST periods, respectively. In both periods and for both AGC and AClean firms, ERCs
are positive and statistically significant.25 ERC for AGC firms increased from 0.913 to 2.085
between the PRE and the POST periods. As we show in Panel B, this increase is not statistically
significant at conventional levels (p-value 0.11). It seems therefore that the ASU 2014-15
management disclosures for AGC companies in the POST period does not add to the SEC-
mandated disclosures, that were provided in both periods, in influencing investor perceptions.
The ERC for AClean firms increased from 1.532 to 2.544 in the POST period. This
increase is statistically significant with p-value 0.03 (Panel B) indicating that the market
perceives earnings quality to be higher in the POST period than in the PRE period, for firms that
did not receive a going concern opinion from the auditor. However, the difference in the change
in ERC between AGC firms and AClean firms is not significant.26
Next, we restrict our sample to clean firms that did not receive going concern opinions
from their auditors, and investigate changes in ERC for firms with different management going
concern disclosures. The results for estimating equations 3 and 4 are presented in Table 5 Panel
A, and the tests for differences in ERCs between groups are shown in Panel B. Columns 1-2 of
Table 5 panel A present results for the PRE and POST periods respectively, using a two-way
classification of management going concern disclosures. For the MCLEAN group (i.e., firms
with clean audit opinions as well as clean management assessments), the ERC increases,
25 The ERC for the AGC sample is smaller in magnitude than that for the AClean sample in both periods. F-tests indicate that the difference is significant (p-value=.08) for the PRE period but not for the POST period (p-value=.23). 26 We use the lincom command in STATA to examine linear combinations of the coefficient estimates.
29
consistent with H2, from 1.708 in the PRE period to 2.990 in the POST period. The increase in
ERC is statistically significant at the 1% level (Panel B). For the MGCALL group (i.e., firms
with clean audit opinions but with going concern disclosures by management), the ERC
increases from 0.622 in the PRE period to 2.937 in the POST period. Again, the increase is
statistically significant at the 1% level, as shown in Panel B. It seems therefore that, investors
value the increased information offered by these firms, possibly because it reduces asymmetric
information between investors and management, despite the potential negative news conveyed
by the revelation that management had considered the possibility of substantial doubt. The
magnitude of increases for the two groups is not different (p-value= 0.12 in Panel B).
Columns 3-4 in Table 5 Panel A shows the results when a three-way classification of
management going concern disclosures is used. The MCLEAN group is now decomposed into
those with explicit statements of no going concern issues (MExpNoGC) and those that have no
disclosures relating to going concern (MSilent). Tests of difference in ERCs between groups is
shown in Panel B. All three groups show statistically significant increases in ERC, suggesting
that investors value the increased information from the ASU 2014-15 disclosures for firms with
no AGCs. Interestingly, the magnitude of the increase is higher for the two groups with explicit
disclosures than for the silent group. Holding other things constant, the ERC increases by 2.369
and 1.968 respectively for groups with disclosures about going concern issues and explicit
disclosures about the absence of going concern issues. For the silent group, the ERC increases by
1.278. We also examined whether the magnitude of the increases in ERC differed across the
three groups. Pair-wise comparisons are shown in Panel B. The only significant difference is that
between the increase in ERC for the MSilent and MGCALL groups. We conclude that there is
some evidence that the new ASU 2014-15 disclosure are considered useful by investors.
30
In sum, our results indicate the following: (1) investors value the increased information
provided by ASU 2014-15 disclosures by firms without AGCs, but not for firms with AGCs and
(2) among the clean firms, the largest increase is for those that disclose going concern issues
mildly, in conjunction with mitigating factors, or as an assertion that substantial doubt exists.
IV. AUDITOR GOING CONCERN OPINIONS IN THE PRE- AND POST-PERIODS
Empirical Model
Our second research question (hypothesis H4) relates to auditor response to the new
standard. Following the methodology in Francis and Krishnan (2002) and Geiger et al. (2005),
we use coefficients from estimating AGC models to examine changes in conservatism from the
PRE to POST period.
The probability of a going concern audit report depends on client characteristics (X) and
the weight the auditor attaches to each characteristic (β). Specifically, the probability of a going
concern opinion for client i in year t can be described as:
P(𝐶𝐶𝐴𝐴𝐶𝐶𝑖𝑖𝑖𝑖 = 1)=F(𝑋𝑋𝑖𝑖𝑖𝑖 ∙ 𝛽𝛽𝑖𝑖) (5)
where F(∙) denotes the distribution function of a logistic model.
Following prior work, we include financial, market, and other variables in the X vector
(e.g., Francis and Krishnan 1999; DeFond et al. 2002). These variables could also proxy for
“contrary” and “mitigating” factors identified in AS 2415 (DeFond et al. 2002). We include firm
size (TASSET) because smaller firms are more likely than larger firms to receive AGCs. Several
variables capture financial distress: return on assets (ROA), leverage (LEV), and operating cash
flows (OCF). We include the number of years the company has been traded (AGE) as younger
firms are less likely to survive as a going concern (Dopuch, Holthausen, and Leftwich 1987). The
31
ratio of cash and short-term investments to total assets (INVEST) proxy for liquidity. To control
for a firm’s ability to raise funds in the near future, we include a new financing variable (FUTFIN).
We include three market variables, firm returns (RETURN), firm beta (BETA2) and standard
deviation of returns (STDRES), to capture firm performance, systematic risk and firm specific
risk, respectively. The market variables can capture information included in the footnotes and may
be correlated with the auditor’s private information set (Dopuch et al. 1987). We include the lag
between the fiscal year end and the audit report date (REPLAG) because companies that receive
AGC are associated with longer reporting lags (Carcello et al. 1995). Finally, we include the
previous year’s audit opinion, GCLAG, indicating a going concern opinion in the previous year
(Carcello and Neal 2000).
We estimate (5) separately for the PRE and POST periods. Using the estimated coefficients
(�̂�𝛽𝑖𝑖) from (5), we estimate the probability of issuance of a going concern opinion in each period.
The estimated change in predicted probability of a going concern opinion (Δ𝑃𝑃) is given by:
Δ𝑃𝑃 = 𝑃𝑃�𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃� − 𝑃𝑃(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃) (6)
The change in the probability of issuing a going concern opinion can be due to (i) change in client
risk characteristics (X) or (ii) change in auditors’ reporting strategy which would be reflected in
β. Following Francis and Krishnan (2002), we decompose the change in probability into the two
components as follows: 27
Δ𝑃𝑃 = �𝑃𝑃�𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃, �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃� − 𝑃𝑃�𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃�� + [𝑃𝑃�𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃� − 𝑃𝑃�𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃�] (7)
The first term in brackets, ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅, represents the change in probability of a going concern opinion
due to changes in auditors’ reporting strategy. The second term in brackets, ∆𝑃𝑃𝐶𝐶𝑃𝑃𝑖𝑖𝐶𝐶𝑘𝑘, captures
27 Thus we add and subtract the term 𝑃𝑃�𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃� to equation (6).
32
the change in probability of a going concern opinion due to change in client risk characteristics.
Thus, we estimate the logistic model for PRE and POST, and compute Δ𝑃𝑃, ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅, 𝐴𝐴𝑐𝑐𝑎𝑎 ∆𝑃𝑃𝐶𝐶𝑃𝑃𝑖𝑖𝐶𝐶𝑘𝑘.
We then examine whether the changes in the probabilities are statistically significant using t-tests
for the means and Wilcoxon rank-sum tests for medians. Our focus is on ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅 which captures
the impact of changes in auditor behavior rather than of changes in client characteristics.
Hypotheses 4 does not indicate a sign for ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅. A positive (negative) ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅 would indicate that
auditors are more (less) conservative in the POST period compared with the PRE period.
In order to obtain coefficients for the AGC model, we assemble two samples surrounding
the ASU 2014-15 implementation date, one consisting of all firms for which complete data is
available (the “full” sample) and the second consisting of a subset of financially distressed firms
from the full sample (the “distressed” sample). Although the going concern opinion is most
salient for financially distressed firms, we believe that the full sample (consisting of stressed as
well as healthy firms) is useful for our context because the FASB emphasizes that ASU 2014-15
can be beneficial for all entities. However, both samples exclude firms in the financial industry
because the variables used to measure financial distress in the going concern model are not as
applicable to the financial sector (Francis and Krishnan 2002).
The full sample comprises 2,697 observations in the PRE period and 2,640 observations
in the POST period.28 Following prior literature (Reynolds and Francis 2001; DeFond et al.
2002), we define financially stressed firms as those with negative net income and/or negative
28 Since the goal is to obtain coefficients for the GC model to use in the computation of changes in probabilities, we want to retain as large a sample as possible. Thus, these samples are larger than those in the previous section because we do not require availability of IBES data.
33
cash flow from operations. The distressed sample comprises 1,258 observations in the PRE
period and 1,218 observations in the POST period.
Descriptive Statistics
Table 6, Panel A presents auditors’ going concern opinion (AGC) rates for the PRE and
POST periods for the full and distressed samples. For the full sample, the AGC rate increased
from 5.52% to 6.40% from the PRE to POST periods. Not surprisingly, AGC rates are higher for
the distressed sample. The rate increased from 11.53% to 13.63% from the PRE to POST
periods.
Table 6, Panels B and C present descriptive statistics for the full and distressed samples,
respectively. In Panel B, none of the financial variables (with the exception of LEV and OCF) is
significantly different between the PRE and POST periods. Two market based variables, are
significantly different. BETA2 and RETURN have significantly higher values in the POST
period, suggesting higher systematic risk, and higher stock returns on average.29 GCLAG is
higher in the POST period than in the PRE period. For the distressed sample (Panel C), in
addition to the differences noted above for the full sample, there is a decrease in the proportion
of clients audited by the BIG7 and the median firm size (TASSET) is lower in the POST period
compared with the PRE period.
Panel D of Table 6 presents correlations among the variables. We show correlations for
the full sample below the diagonal and correlations for the distressed sample above the diagonal.
29 The market variables are estimated over the 200-day window ending 21 days before the fiscal year end. Consequently, we label the beta variable as BETA2 to distinguish it from the BETA used in the ERC model.
34
The variance inflation factors (VIF) are below 4.5 for all variables, indicating that
multicollinearity is not a concern.
Logit Estimates for PRE and POST Periods
Table 7, Panel A presents estimates for the going concern opinion models for the full
(columns 1-2) and distressed (columns 3-4) samples. The pseudo R-Squared for the four models
vary between 0.52 to 0.62. Overall, the sign of the coefficients on the variables are consistent
with prior work. In addition, most of the variables have the same sign in the PRE and POST
periods, with some differences in their magnitudes and levels of statistical significance.
Tests Based on the Decomposition of Going Concern Rates
Table 8 reports changes in going concern reporting probabilities for the PRE and POST
periods. Panels A and B show the results for the full and distressed samples, respectively. Panel
A shows that the mean and median change in the probability of going concern opinion, Δ𝑃𝑃, are
1.22% and 0.04% respectively, and both are significantly different from zero. Columns 3-4 and
columns 5-6 show the mean and medians for the two components of the change, the change in
auditor reporting strategy and change in client risk characteristics. Our focus is on ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅, the
proxy for changes in auditor reporting strategy. In Panel A, both the mean (0.16%) and median
(0.11%) for ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅 are positive and significant. Also, 86% of the sample has a positive ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅.
The change due to change in client risk characteristics ((∆𝑃𝑃𝐶𝐶𝑃𝑃𝑖𝑖𝐶𝐶𝑘𝑘) columns 5-6), for which we
have no a priori expectation, has a positive mean and a negative median. About 37% of the
sample has a positive ∆𝑃𝑃𝐶𝐶𝑃𝑃𝑖𝑖𝐶𝐶𝑘𝑘.
Table 8, Panel B shows similar results for the distressed sample. The mean overall
probability of going concern opinion increases by 3.26% from the PRE to POST periods. The
mean change in probability due to change in auditor reporting strategy �∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅� is 0.40% and is
35
statistically significant. The median change of 0.37% is also significant.30 Also, 74% of the
distressed sample has a positive ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅. The mean change in probability due to change in client
risk characteristics is 2.86%, and is statistically significant. However, the median is insignificant.
Thus, the new standard seems to have increased auditor reporting conservatism after accounting
for the effect of changes in client characteristics.
Next we report a similar analysis for the sub-sample of firms for which we manually
collected data on management’s assessment of going concern. For this analysis, we merge the
full and distressed samples separately with our sample from Table 4, and compute the change in
probabilities.
Table 9, Panels A and B report the results for the change in probabilities. We continue to
refer to the samples as “full” and “distressed” samples although the sample sizes are different
from those in Table 8. As with our first research question, we separately classify companies into
MCLEAN and MGCALL. We also provide estimates for the sub-categories but the number of
observations for some of the sub-categories are very small.
The numbers in Panels A and B suggest the following. First, all subgroups show an
increase in the overall probability ∆𝑃𝑃 of receiving a going concern opinion (mean, median or
both) with the exception of MSilent for the distressed sample. We ignore the “MGC with
Mitigating Factors” group because it has only 12 (11) observations in the full (distressed)
sample. Second, focusing on the auditor reporting component ∆𝑃𝑃𝑃𝑃𝑅𝑅𝑅𝑅, we find that both the
MSilent and MExpNoGC groups are treated more conservatively in the POST period in both
panels. Among the firms with going concern disclosures, the auditor reporting component is not
30 We use the Wilcoxon Rank Sum test to check whether the median is significantly different from zero.
36
significant in Panel A, except for the median for the MildMGC. In Panel B, the auditor reporting
component is positive and significant for the MGCALL group as a whole. The median for the
MildMGC and mean for the MGCExp groups are positive and significant. However, these tests
should be viewed with some caution, because the sample sizes are small. Third, the client risk
component ∆𝑃𝑃𝐶𝐶𝑃𝑃𝑖𝑖𝐶𝐶𝑘𝑘 is generally positive and significant for the firms with disclosures about
going concern issues (except for MGC with mitigating factors, which has only 12 and 11
observations for the full and distressed sample respectively), but are negative or not significant
for the firms whose managers are not concerned about going concern issues. We note also that
the magnitude of ∆𝑃𝑃𝐶𝐶𝑃𝑃𝑖𝑖𝐶𝐶𝑘𝑘 across the groups gives credibility to our model as well as to our
coding of the disclosures. It is much larger for MGCALL than for MCLEAN. Also, it is larger
for the MGCExp Group than for the MildMGC group.
We conclude that, where management is providing assurance of the absence of going
concern issues, the auditor works harder to possibly ratify this assurance. In contrast, where the
management discloses going concern issues, the auditor does not change reporting strategy.
V. CONCLUSIONS
ASU 2014-15 requires managements of companies to evaluate their going concern status
for a period of one year from the date the financial statements are issued (or become available),
and provide footnote disclosures about the assessments. The rule became effective for fiscal
years ending after December 15, 2016. Prior to this standard, only auditors were required to
make going concern assessments (AS 2415, PCAOB 2017).
The FASB argues that requiring management to evaluate going concern status will
enhance the “timeliness, clarity, and consistency of related disclosures” (FASB 2014). Some
37
accounting firms (including the Big 4) that responded to the FASB’s exposure draft for the
standard supported the proposal, commenting that the management is in a unique position to
make this assessment because of its first-hand knowledge about significant risks, and its plans to
mitigate the risks. Management also has superior information about other relevant factors such as
new product development, strategy, and negotiation with lenders that could affect going concern
status of a company (Hutton, Lee, and Shu 2012).
We examine two research questions: Does the new standard affect market perceptions,
measured by the earnings response coefficient (ERC)? Does it affect auditors’ propensity to issue
a going concern opinion after controlling for changes in client characteristics? Our findings
indicate a significant increase in the ERC for firms with clean audit opinions whose management
also did not disclose going concern issues, indicating that the “double” assurance offered by the
auditor and management that the firm is “clean” is considered informative by investors. In
contrast, companies with AGCs see no change in ERCs. Since companies with AGC have been
required by the SEC to provide relevant disclosures, we conjecture that the market does not
perceive any new information provided by ASU 2014-15 disclosures as being useful.
We further examine whether the nature of the management disclosures by companies
with clean audit opinions differentially affects their ERCs. Clean companies can be silent (i.e.,
make no statement about going concern implying the absence of any issues), make an explicit
statement that there are no going concern issues, or provide disclosures about potential
substantial doubt, management plans and alleviation of the substantial doubt. We find that, while
the ERCs increase for all groups, the two groups with explicit disclosures have a greater increase
than the silent group. However, the difference in the increase in ERC is statistically significant
only between the silent group and the group with some disclosures about going concern. Overall,
38
we conclude that there is some evidence that management disclosures under ASU 2014-15 are
useful to investors.
We also document that auditor’s propensity to issue a going concern opinion has
increased during the post-adoption period. We separate this increase into two components, one
capturing the auditor’s weighting of these characteristics (i.e., reporting conservatism) and one
capturing the change due to changes in client characteristics. We find that there is a significant
increase in reporting conservatism, suggesting that the requirement that management should
provide disclosures about going concern affects auditor behavior.
We acknowledge some limitations of our study. First, as with any archival study, we only
establish associations, not causality. Second, our sample sizes are small for some of our analyses.
Because the coding process is extremely time-consuming we restricted the data collection to the
initial sample, which required data from IBES. Consequently, the management disclosures in our
sample may not be representative of the whole population. Third, the PCAOB mandated
disclosure of the identity of audit engagement partners effective January 31, 2017. The PCAOB
expects that this disclosure will result in increased accountability thus improving audit quality.
To the extent that the disclosure of their identities also affects partners’ going concern reporting
causing them to become more cautious, our results could be reflecting the joint effects of ASU
2014-15 and engagement partner identity disclosures.
39
References
Balsam, S., J. Krishnan, and J. S. Yang. 2003. Auditor industry specialization and earnings quality. Auditing: A Journal of Practice & Theory, 22 (2): 71–97. Baber, W. R., J. Krishnan, and Y. Zhang. 2014. Investor perceptions of the earnings quality consequences of hiring an affiliated auditor. Review of Accounting Studies 19 (1): 69–102. Behn, B. K., S. E. Kaplan, and K. R. Krumwiede. 2001. Further evidence on the auditor's going-concern report: The influence of management plans. Auditing: A Journal of Practice & Theory 20 (1): 13–28. Blay, A. 2010. Independence threats, litigation risk, and the auditor’s decision process. Contemporary Accounting Research 22 (4): 759–789. Booker, K. D., and Q. Booker. 2016. Changes to going concern disclosures: Accounting guidance shifts responsibilities to management. The CPA Journal 86 (2): 42–45. Carcello, J. V., D. R. Hermanson, and H. F. Huss. 1995. Temporal changes in bankruptcy-related reporting. Auditing: A Journal of Practice & Theory 14 (2): 133–143. Carcello, J. V., and T. L. Neal. 2000. Audit committee composition and auditor reporting. The Accounting Review 75 (4): 453–467. Carson, E., N. L. Fargher, M. A. Geiger, C. S. Lennox, K. Raghunandan, and M. Willekens. 2013. Audit reporting for going-concern uncertainty: A research synthesis. Auditing: A Journal of Practice & Theory 32 (Supplement 1): 353–384. Chen, L. H., J. Krishnan, H. Sami, and H. Zhou. 2013. Auditor attestation under SOX Section 404 and earnings informativeness. Auditing: A Journal of Practice & Theory 32 (1): 61–84. Choi, S. K., and D. C. Jeter. 1992. The effects of qualified audit opinions on earnings response coefficients. Journal of Accounting and Economics 15 (2/3): 229–247. Cohen, J. R., L. M. Gaynor, L. L. Holder-Webb, and N. Montague. 2008. Management’s Discussion and Analysis: Implications for audit practice and research. Current Issues in Auditing 2 (2): A26–A35.
Collins, D. W., and S. P. Kothari. 1989. An analysis of intertemporal and cross-sectional determinants of earnings response coefficient. Journal of Accounting and Economics 11 (2-3): 143–189. DeFond, M., and J. Zhang. 2014. A review of archival auditing research. Journal of Accounting and Economics 58 (2–3): 275–326.
40
DeFond, M. L., K. Raghunandan, and K. R. Subramanyam. 2002. Do non–audit service fees impair auditor independence? Evidence from going concern audit opinions. Journal of Accounting Research 40 (4): 1247–1274. Dong, B., D. Robinson, M. Robinson. 2015. The market's response to earnings surprises after first-time going-concern modifications. Advances in Accounting 31 (1): 21–32. Dopuch, N., R. W. Holthausen, and R. W. Leftwich. 1987. Predicting audit qualifications with financial and market variables. The Accounting Review 62 (3): 431–454. Easton, P. D., and M. E. Zmijewski. 1989. Cross-sectional variation in the stock market response to accounting earnings announcements. Journal of Accounting and Economics 11 (2-3): 117–141. EY. 2017. Technical Line, FASB — final guidance: How to apply the FASB’s guidance on management’s going concern evaluation. EY Accounting Link (2017-01, January 12). Farber, H. 1990. The decline of unionization in the United States: What can be learned from recent experience? Journal of Labor Economics 8 (1): S75-S105. Financial Accounting Standards Board (FASB). 2013. Proposed Accounting Standards Update—Presentation of Financial Statements (Topic 205): Disclosure of Uncertainties about an Entity’s Going Concern Presumption (2013-300). FASB, Norwalk, CT. FASB 2014. Disclosure of Uncertainties about an Entity’s Ability to Continue as a Going Concern (August). FASB, Norwalk, CT. http://www.fasb.org/resources/ccurl/599/128/ASU%202014-15.pdf Francis, J. R., and J. Krishnan. 1999. Accounting accruals and auditor reporting conservatism. Contemporary Accounting Research 16 (1): 135–165. Francis, J. R., and J. Krishnan. 2002. Evidence on auditor risk-management strategies before and after the Private Securities Litigation Reform Act of 1995. Asia Pacific Journal of Accounting and Economics 9 (December): 135–158. Francis, J. R., and B. Ke. 2006. Disclosure of fees paid to auditors and the market valuation of earnings surprises. Review of Accounting Studies 11 (4): 495–523. Geiger, M. A., and K. Raghunandan. 2002. Going-concern opinions in the "New" legal environment. Auditing: A Journal of Practice & Theory 16 (1): 17–26. Geiger, M. A., K. Raghunandan, and D. V. Rama. 2005. Recent changes in the association between bankruptcies and prior audit opinions. Auditing: A Journal of Practice & Theory 24 (1): 21–35.
41
Goh, B. W., J. Krishnan, and D. Li. 2013. Auditor reporting under Section 404: the association between the internal control and going concern audit opinions. Contemporary Accounting Research 30 (3): 970–995. Hackenbrack, K. E., and C. E. Hogan. 2002. Market response to earnings surprises conditional on reasons for an auditor change. Contemporary Accounting Research 19 (2): 195–223. Hayn, C. 1995. The information content of losses. Journal of Accounting and Economics 20 (2): 125–153. Holthausen, R. W., and R. E. Verrecchia. 1988. The effect of sequential information releases on the variance of price changes in an intertemporal multi-asset market. Journal of Accounting Research 26 (1): 82–106. Hutton, A. P., L. F. Lee, and S. Z. Shu. 2012. Do managers always know better? The relative accuracy of management and analyst forecasts. Journal of Accounting Research 50 (5): 1217–1244. Khan, U., B. Li, S. Rajgopal, and M. Venkatachalam. 2017. Do the FASB’s standards add shareholder value? The Accounting Review 93 (2): 209–247. Knechel, W. R., and A. Vanstraelen. 2007. The relationship between auditor tenure and audit quality implied by going concern opinions. Auditing: A Journal of Practice & Theory 26 (1): 113–131. Kothari, S. P., A. J. Leone, and C. E. Wasley. 2005. Performance matched discretionary accrual measures. Journal of Accounting and Economics 39 (1): 163–197. Mayew, W. J., M. Sethuraman, and M. Venkatachalam. 2015. MD&A disclosure and the firm’s ability to continue as a going concern. The Accounting Review 90 (4): 1621–1651. Myers, L. A., J. Schmidt, and M. Wilkins. 2014. An investigation of recent changes in going concern reporting decisions among Big N and non-Big N auditors. Review of Accounting and Finance 43 (1): 155–172. Mutchler, J. F., W. Hopwood, and J. McKeown. 1997. The influence of contrary information and mitigating factors on audit opinion decisions on bankrupt companies. Journal of Accounting Research 35 (2): 295–310. Ontario Securities Commission. 2010. OSC Staff Notice 52-719 Going Concern Disclosure Review http://www.osc.gov.on.ca/en/SecuritiesLaw_sn_20101214_52-719_improve-disclosure.htm PCAOB 2014. Matters Related to the Auditor’s Consideration of a Company’s Ability to Continue as a Going Concern. Staff Audit Practice Alert No. 13 (September). https://pcaobus.org/Standards/QandA/09222014_SAPA_13.pdf
42
PCAOB 2015. Improving the Transparency of Audits: Rules to Require Disclosure of Certain Audit Participants on a New PCAOB Form and Related Amendments to Auditing Standards. Release No. 2015-008 (December). https://pcaobus.org/Rulemaking/Docket029/Release-2015-008.pdf PCAOB. 2017. Consideration of an Entity's Ability to Continue as a Going Concern. https://pcaobus.org/Standards/Auditing/Pages/AS2415.aspx Reynolds, J. K. and J. R. Francis. 2001. Does size matter? The influence of large clients on office-level auditor reporting decisions. Journal of Accounting and Economics 30 (3): 375–400. Securities and Exchange Commission (SEC). 2017. Financial Reporting Manual. Division of Corporate Finance. https://www.sec.gov/files/cffinancialreportingmanual_0.pdf Steele, A. 2017. Sears stock stumbles after going-concern warning. The Wall Street Journal (March 24). Teoh, S. H., and T. J. Wong. 1993. Perceived audit quality and the earnings response coefficient. The Accounting Review 68 (2): 346–366. Uang, J-Y., D. B. Citron, S. Sudarsanam, and R. J. Taffler. 2006. Governance and auditor reputation. European Financial Management 12 (5): 789–816.
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Table 1 Sample Selection for RQ1
Sample Selection Criteria N Firm-year observations available in Audit Analytics for fiscal years ending after November 1, 2015 as of the data collection date, July 1, 2017
12,282
Less: Firm-year observations that relate to Funds or Trusts, use non-US GAAP, or have missing SIC codes or with multiple observations for the same Firm-Year (1,419) Firms with missing data on Compustat (2,173) Firms with missing data on CRSP (2,001) Firms with missing data on I/B/E/S (2,078)
Final Sample
4,611 Comprising PRE period (year ends between November 1, 2015 and December 15, 2016 ) 2,328 POST period (year ends between December 16, 2016 and January 31, 2017) 2,283
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Table 2 Description of Management Going Concern Disclosures
Panel A: Cross-classification of Auditor Going Concern Opinion (AGC) and Management Going Concern Disclosure
Type of Management Disclosurea AGC=0b AGC=1b Total MExpNoGC (Explicit statement that there are no going concern issues)
101 0 101
MSilent (No explicit statement about going concern issues) 4,299 1 4,300 MCLEAN (No going concern issues) 4,400 1 4,401 MildMGC (Mild mention of going concern issues) 86 6 92 MGCMit (Discussion of Mitigating Factors) 12 0 12 MGCExp (Explicit statement that substantial doubt persists) 3 103 106 MGCALL (Some going concern issues) 101 109 210 Total 4,501 110 4,611
Panel B: Distribution of Management Going Concern Disclosures for Clean firms in the PRE and POST Periods
Type of Management Disclosure (See Panel A for definitions of each)
PRE POST Total N % N % N
MExpNoGC 13 0.57 88 3.96 101 MSilent 2,224 97.50 2,075 93.47 4,299 MildMGC 43 1.89 43 1.94 86 MGCMit 0 0.00 12 0.54 12 MGCExp 1 0.04 2 0.09 3 Total 2,281 100.00 2,220 100.00 4,501
45
Panel C: Distribution of Management Going Concern Disclosures by Location in 10-K filing, Classified by PRE and POST Period Type of Management Disclosure (See Panel A for definitions of each)
AGC=1b AGC=0b PRE POST PRE POST
Location of Disclosure in 10-K Location of Disclosure in 10-K
RFc MD&Ad FNe Totalf RFc MD&Ad FNe Totalf RFc MD&Ad FNe Totalf RFc MD&Ad FNe Totalf
MExpNoGC 2 6 11 13 1 28 87 88 MSilent 1 2,224 2,075 MildMGC 4 3 2 4 2 2 2 2 35 12 4 43 36 8 6 43 MGCMit 7 5 12 12 MGCExp 36 32 41 42 58 53 61 61 1 1 1 1 2 2 Total 47 63 2,281 2,220
a MExpNoGC and MSilent are combined into MCLEAN, and MildMGC, MGCMit and MGC are combined into MGCALL. b AGC=1 indicates auditor’s going concern opinion. AGC=0 indicates auditor’s clean opinion. c Risk Factors Section. d Management Discussions & Analysis Section. e Footnotes to financial statements. f The numbers in this column are from Panels A and B. The sum of the numbers in RF, MD&A, and FN columns will not equal the total column because many
companies provide disclosure in more than one section. In seven cases (5 in the pre-period and 2 in the post-period) we also found GC disclosures in Item 1 of Form 10-K. In one case, GC disclosure also appeared in Item 9A of Form 10-K. Note: In many cases, there is variation in the content of the disclosures across the sections. For example, management can explicitly state “substantial doubt” in a footnote, and use milder statements (e.g., we may be unable to continue as a going concern) or refer to the auditor’s opinion (e.g., our independent registered public accounting firm included an explanatory paragraph expressing that there is substantial doubt…) in the MD&A. For the purposes of this table, we simply record each occurrence regardless of content. For the coding of the variables used in the regressions, we rely on the “strongest” disclosure.
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Table 3 Descriptive Statistics and Correlations
Panel A: Descriptive Statistics
PRE POST PRE vs. POST Mean
(Median) Mean
(Median) t-statistica
(Wilcoxon Z)b (1) (2) (3)
CAR 0.0002 0.0002 0.03 (0.003) (-0.001) (-0.77) UE -0.0001 -0.0001 -0.02 (0.0004) (0.0005) (1.11) LNMV 7.092 7.212 2.20** (7.026) (7.170) (2.56)** BM 0.521 0.443 -5.75*** (0.424) (0.387) (-5.02)*** LEV 0.593 0.616 2.74*** (0.609) (0.623) (2.48)** BETA 1.095 1.352 16.87*** (1.030) (1.310) (17.10)*** LOSS 0.370 0.365 -0.35 (0) (0) (-0.35) BIG7 0.888 0.888 -0.05 (1) (1) (-0.05) N 2,328 2,283
*** p<0.01, ** p<0.05, * p<0.1 a Tests for differences in means. b Tests whether the observations in the two periods are from populations with different medians. See Appendix A for the definition of variables. All continuous variables are winsorized at 1% and 99%.
47
Panel B: Pairwise Correlation Matrix CAR UE LNMV BM LEV BETA LOSS BIG7 MCLEAN MGCALL CAR 1.00 UE 0.14 1.00 LNMV 0.00 0.04 1.00 BM 0.05 -0.05 -0.17 1.00 LEV 0.02 0.01 0.12 -0.20 1.00 BETA -0.03 -0.02 -0.02 0.01 -0.04 1.00 LOSS -0.01 -0.03 -0.43 0.02 -0.17 0.32 1.00 BIG7 0.00 0.03 0.34 -0.07 -0.05 0.15 -0.03 1.00 MCLEAN 0.05 0.08 0.27 0.05 -0.02 -0.06 -0.23 0.13 1.00 MGCALL -0.05 -0.08 -0.27 -0.05 -0.02 0.06 0.23 -0.13 -1.00 1.00 Sample is restricted to observations with all the variables available to calculate control variables. See Appendix A for the definition of variables. All the continuous variables are winsorized at 1% and 99%.
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Table 4 Change in ERC for Auditor Going Concern Opinion Groups
Panel A: Parameter Estimates
Variables
PRE POST (1) (2)
UE*AGC 0.913* 2.085*** (1.956) (3.645) UE*AClean 1.532*** 2.544*** (4.664) (7.494) AGC -0.022 -0.008 (-1.337) (-0.580) LNMV 0.0013 -0.0006 (1.251) (-0.654) BM 0.013*** 0.011** (3.159) (2.345) LEV 0.018*** 0.005 (2.654) (0.694) BETA -0.013*** -0.001 (-2.979) (-0.460) LOSS 0.002 0.006 (0.420) (1.355) BIG7 0.004 0.003 (0.824) (0.512) UE*LNMV 0.075 0.360*** (0.900) (3.366) UE*BM 0.035 -0.082 (0.209) (-0.415) UE*LEV -0.084 -0.661 (-0.187) (-1.336) UE*BETA -0.274* 0.498** (-1.691) (2.512) UE*LOSS -0.951** -1.990*** (-2.024) (-4.127) UE*BIG7 0.990*** -0.190 (3.068) (-0.527) Intercept -0.017* -0.006 (-1.775) (-0.596) N 2,328 2,283 R-squared 0.058 0.073
Dependent variable: CAR Robust t-statistics in parentheses; *** p<0.01, ** p<0.05, * p<0.1; See Appendix A for the definition of variables. All continuous variables are winsorized at 1% and 99%.
49
Panel B: Differences in ERCs between the PRE and POST Periods Subsample
PRE
POST
Difference
Z-statistica (p-value)
AGC firms 0.913 2.085 1.172 1.59 (0.11)
AClean firms 1.532 2.544 1.012 2.15** (0.03)
Difference in Differences (AGC vs. AClean)
0.160 -0.31 (0.76)
*** p<0.01, ** p<0.05, * p<0.1; a Postestimation test for difference between PRE and POST periods.
50
Table 5 Change in ERC for Management Going Concern Disclosure Groups
Panel A: Parameter Estimates
Variables PRE POST PRE POST (1) (2) (3) (4) UE*MCLEAN 1.708*** 2.990*** (4.941) (8.341) UE*MExpNoGC 1.400* 3.368*** (1.662) (5.685) UE*MSilent 1.709*** 2.987*** (4.941) (8.303) UE*MGCALL 0.622 2.937*** 0.622 2.991*** (1.130) (4.986) (1.130) (4.971) MCLEAN 0.020 0.025* (1.168) (1.804) MExpNoGC 0.026 0.015
(1.082) (0.905) MSilent 0.020 0.026*
(1.164) (1.835) LNMV 0.001 -0.001 0.001 -0.002
(1.134) (-1.455) (1.135) (-1.594) BM 0.012*** 0.008* 0.012*** 0.007
(3.120) (1.659) (3.125) (1.608) LEV 0.018*** 0.006 0.018*** 0.006
(2.688) (0.909) (2.695) (0.906) BETA -0.012*** -0.0004 -0.012*** -0.0002
(-2.652) (-0.140) (-2.652) (-0.075) LOSS 0.002 0.006 0.002 0.007
(0.354) (1.502) (0.338) (1.563) BIG7 0.006 0.0002 0.006 0.0007
(1.214) (0.0371) (1.217) (0.119) UE*LNMV 0.029 0.481*** 0.029 0.501***
(0.344) (3.902) (0.343) (3.925) UE*BM -0.005 -0.019 -0.005 -0.002
(-0.029) (-0.085) (-0.028) (-0.007) UE*LEV -0.124 -0.863 -0.131 -0.840
(-0.244) (-1.405) (-0.253) (-1.385) UE*BETA -0.405** 0.542** -0.404** 0.532**
(-2.004) (2.054) (-1.993) (2.014) UE*LOSS -1.135** -2.373*** -1.133** -2.394***
(-2.298) (-4.795) (-2.292) (-4.855) UE*BIG7 0.942** -0.018 0.944** -0.059
(2.533) (-0.034) (2.534) (-0.114) Intercept -0.039** -0.024 -0.039** -0.024
(-1.977) (-1.383) (-1.978) (-1.362) N 2,281 2,220 2,281 2,220 R-squared 0.064 0.086 0.064 0.087
Dependent variable: CAR; Robust t-statistics in parentheses; *** p<0.01, ** p<0.05, * p<0.1; See Appendix A for the definition of variables. All continuous variables are winsorized at 1% and 99%.
51
Panel B: Comparison of ERCs between PRE and POST Models Subsample
PRE
POST
Difference
(POST-PRE)
Z-statistica (p-value)
Two-way classification of Management Going Concern disclosures
MCLEAN firms 1.708 2.990 1.282
2.58***
(0.01) MGCALL firms 0.622 2.937 2.315
2.88***
(0.00) Difference in Differences (MCLEAN vs. MGCALL)
-1.033
-1.58 (0.12)
Three-way classification of Management Going Concern disclosures
MExpNoGC firms 1.400 3.368 1.968 1.92* (0.06)
MSilent firms 1.709 2.987 1.278 2.57*** (0.01)
MGCALL firms 0.622 2.991 2.369 2.92*** (0.00)
Difference in Differences (MExpNoGC vs. MSilent)
0.690 0.77 (0.44)
Difference in Differences (MExpNoGC vs. MGCALL)
-0.401 -0.38 (0.70)
Difference in Differences (MGCALL vs. MSilent)
1.091 1.64* (0.10)
*** p<0.01, ** p<0.05, * p<0.1 a Postestimation test for difference between PRE and POST periods.
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Table 6 Going Concern Opinion Rates and Descriptive Statistics
Panel A: Going Concern Opinion Rates
AGC
Full Samplea Distressed Sampleb
PRE POST Total PRE POST Total 0 2,548 2,471 5,019 1,113 1,052 2,165 94.48% 93.60% 94.04% 88.47% 86.37% 87.76% 1 149 169 318 145 166 311 5.52% 6.40% 5.96% 11.53% 13.63% 12.61%
Total 2,697 2,640 5,337 1,258 1,218 2,476
Panel B: Descriptive Statistics for Full Sample PRE POST PRE vs. POST
Variable Mean
(Median) Mean
(Median) t-statistica
(Wilcoxon Z)b (1) (2) (3)
ROA -0.107 -0.115 -0.84 (0.014) (0.013) (-0.70)
LEV 0.533 0.552 2.30** (0.513) (0.528) (1.99)**
TASSET 6.370 6.397 0.48 (6.329) (6.408) (0.54)
RETURN -0.020 0.128 24.1*** (-0.002) (0.112) (24.83)***
STDRES 0.030 0.030 -0.66 (0.026) (0.024) (-1.23)
BETA2 0.965 1.236 17.14*** (0.968) (1.213) (16.83)***
AGE 18.634 19.121 0.99 (15) (16) (1.46)
INVEST 0.252 0.253 0.14 (0.144) (0.148) (-0.10)
OCF 0.002 -0.019 -2.90*** (0.070) (0.067) (-2.02)**
REPLAG 63.429 62.996 -1.11 (60) (60) (-1.54)
FUTFIN 0.543 0.550 0.50 (1) (1) (0.50)
GCLAG 0.034 0.051 3.15*** (0) (0) (3.16)***
BIG7 0.835 0.834 -0.02 (1) (1) (-0.02)
N 2,697 2,640
53
Panel C: Descriptive Statistics for Distressed Sample PRE POST PRE vs. POST
Variable
Mean (Median)
Mean (Median)
t-statistica (Wilcoxon Z)b
(1) (2) (3) ROA -0.309 -0.327 -1.06 (-0.160) (-0.162) (-0.83) LEV 0.528 0.553 1.72* (0.493) (0.479) (1.72)* TASSET 5.470 5.345 -1.58 (5.115) (5.358) (-1.91)* RETURN -0.068 0.119 16.82*** (0.107) (-0.062) (16.47)*** STDRES 0.040 0.041 0.59 (0.036) (0.036) (0.56) BETA2 1.011 1.320 11.03*** (1.341) (1.018) (10.52)*** AGE 13.423 13.389 -0.06 (9) (9) (0.64) INVEST 0.349 0.358 0.71 (0.251) (0.228) (0.65) OCF -0.131 -0.176 -3.47*** (-0.031) (-0.017) (-2.85)*** REPLAG 68.719 68.860 0.24 (68) (68) (0.04) FUTFIN 0.621 0.600 -1.05 (1) (1) (-1.05) GCLAG 0.068 0.106 3.31*** (0) (0) (3.32)*** BIG7 0.777 0.748 -1.68* (1) (1) (-1.68)* N 1,258 1,218
*** p<0.01, ** p<0.05, * p<0.1 a Full sample comprises non-financial firms for which financial and market variables are available. b Distressed sample comprises non-financial firms with negative net income and/or negative cash flows from operations for which financial and market variables are available. c Tests for differences in means; d Tests whether the observations in the two periods are from populations with different medians. Variables are defined in Appendix A. All continuous variables are winsorized at 1% and 99%.
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Panel D: Correlation Matrix AGC ROA LEV TASSET RETURN STDRES BETA2 AGE INVEST OCF REPLAG FUTFIN GCLAG BIG7 AGC 1.00 -0.49 0.22 -0.34 -0.14 0.35 -0.13 -0.11 0.02 -0.43 0.32 0.09 0.58 -0.20 ROA -0.53 1.00 -0.18 0.50 0.15 -0.42 -0.01 0.20 -0.39 0.79 -0.27 -0.17 -0.32 0.18 LEV 0.16 -0.12 1.00 0.16 -0.07 0.08 0.06 0.11 -0.34 -0.01 0.03 0.19 0.09 0.07 TASSET -0.32 0.49 0.24 1.00 0.05 -0.44 0.38 0.23 -0.38 0.56 -0.55 0.05 -0.30 0.49 RETURN -0.14 0.17 -0.06 0.03 1.00 0.11 0.16 -0.01 0.05 0.10 -0.10 0.03 -0.02 0.01 STDRES 0.39 -0.56 0.02 -0.57 0.05 1.00 0.02 -0.18 0.14 -0.36 0.40 0.13 0.31 -0.27 BETA2 -0.08 -0.06 0.07 0.23 0.15 0.10 1.00 -0.02 0.10 0.03 -0.35 0.12 -0.11 0.32 AGE -0.13 0.25 0.06 0.32 0.02 -0.32 -0.08 1.00 -0.29 0.22 -0.09 -0.14 -0.11 -0.01 INVEST 0.11 -0.44 -0.32 -0.43 0.02 0.30 0.12 -0.26 1.00 -0.54 0.00 0.04 0.06 0.01 OCF -0.48 0.84 -0.01 0.50 0.13 -0.50 -0.04 0.24 -0.53 1.00 -0.25 -0.19 -0.31 0.19 REPLAG 0.31 -0.36 -0.05 -0.64 -0.09 0.51 -0.25 -0.21 0.14 -0.34 1.00 0.03 0.25 -0.40 FUTFIN 0.08 -0.17 0.26 0.05 0.00 0.12 0.10 -0.16 -0.02 -0.18 0.03 1.00 0.13 0.04 GCLAG 0.60 -0.37 0.07 -0.28 -0.04 0.35 -0.08 -0.12 0.12 -0.36 0.25 0.11 1.00 -0.19 BIG7 -0.20 0.21 0.12 0.50 0.01 -0.33 0.27 0.05 -0.09 0.22 -0.44 0.05 -0.18 1.00 Numbers above the diagonal are Pearson's correlation for distressed sample while the numbers below the diagonal are for full sample.
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Table 7 Logit Estimates
Panel A: Logit Estimates for Full and Distressed Samples
Variables
Exp. Sign
Full Sample Distressed Sample PRE POST PRE POST
(1) (2) (3) (4) ROA - -1.671*** -0.968 -1.476*** -0.780
(-3.531) (-1.584) (-3.399) (-1.343) LEV + 0.837* 1.537*** 0.870** 1.443***
(1.875) (3.951) (2.115) (3.853) TASSET - -0.229* -0.208* -0.256* -0.117
(-1.651) (-1.693) (-1.728) (-0.964) RETURN - -1.549*** -1.806*** -1.342*** -1.678***
(-3.003) (-3.537) (-2.699) (-3.446) STDRES + 27.470*** 12.660 19.370** 8.737
(2.930) (1.643) (2.518) (1.176) BETA2 + -0.284 0.152 -0.207 0.077
(-0.837) (0.784) (-0.656) (0.408) AGE - -0.040*** -0.027** -0.034** -0.022*
(-2.675) (-2.393) (-2.221) (-1.849) INVEST - -3.349*** -1.576** -3.094*** -1.662***
(-4.099) (-2.362) (-4.118) (-2.635) OCF - -2.397*** -1.801** -2.133*** -1.895***
(-3.393) (-2.386) (-3.236) (-2.607) REPLAG + 0.030*** 0.041*** 0.030*** 0.038***
(2.701) (3.569) (2.647) (3.518) FUTFIN - -0.946*** -0.518* -0.842*** -0.354
(-3.100) (-1.834) (-2.791) (-1.288) GCLAG + 3.817*** 3.597*** 3.409*** 3.419*** (8.953) (10.330) (8.371) (10.380) BIG7 + 0.515 0.056 0.568 0.031 (1.447) (0.151) (1.633) (0.085) Intercept ? -5.010*** -6.377*** -4.605*** -6.063***
(-3.601) (-5.212) (-3.357) (-5.282) N 2,697 2,640 1,258 1,218 Pseudo R2 0.603 0.620 0.527 0.540 Dependent variable: AGC Robust Z-statistics in parentheses *** p<0.01, ** p<0.05, * p<0.1 Variables are defined in Appendix A. All continuous variables are winsorized at 1% and 99%.
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Table 8 Changes in Probability of Going Concern Opinion from PRE to POST Periods
Panel A: Full Sample
Change in probability of going concern opinion
(∆𝑃𝑃)a
Component due to change in auditor reporting
strategy (∆𝑃𝑃Rep)b
Component due to change in client risk characteristics
(∆𝑃𝑃CRisk)c ∆P p-value ∆PRep p-value ∆PCRisk p-value
(1) (2) (3) (4) (5) (6) Mean 1.22% 0.000*** 0.16% 0.009*** 1.06% 0.000*** Median 0.04% 0.000*** 0.11% 0.000*** -0.04% 0.000*** % Positive 61% 86% 37% N=2,452
Panel B: Distressed Sample
Change in probability of going concern opinion
(∆𝑃𝑃)
Component due to change in auditor reporting
strategy (∆𝑃𝑃Rep)
Component due to change in client risk characteristics
(∆𝑃𝑃CRisk) ∆P p-value ∆PRep p-value ∆PCRisk p-value
(1) (2) (3) (4) (5) (6) Mean 3.26% 0.000*** 0.40% 0.026** 2.86% 0.000*** Median 0.23% 0.000*** 0.37% 0.000*** -0.09% 0.701 % Positive 57% 74% 45% N=920 *** p<0.01, ** p<0.05, * p<0.1 a P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃)-P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃); b P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃)-P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃); c P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃)-P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃)
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Table 9 Changes in Probability of Going Concern Opinion from PRE to POST Periods,
Partitioned by Management Disclosures about Going Concern
Panel A: Full Sample
Change in probability of going concern opinion
(∆𝑃𝑃)a
Component due to change in auditor reporting
strategy (∆𝑃𝑃Rep)b
Component due to change in client risk characteristics
(∆𝑃𝑃CRisk)c ∆P p-value ∆PRep p-value ∆PCRisk p-value (1) (2) (3) (4) (5) (6)
Firms with clean management disclosures (silent or explicit statements about absence of going concern issues) MSilent (N=1,395) Mean 0.09% 0.544 0.21% 0.000*** -0.12% 0.452 Median 0.03% 0.002*** 0.10% 0.000*** -0.05% 0.000*** % Positive 52% 80% 35% MExpNoGC (N=70) Mean 2.99% 0.095* 0.95% 0.017** 2.04% 0.276 Median 0.24% 0.023** 0.33% 0.000*** -0.03% 0.998 % Positive 67% 81% 44% MCLEAN (N=1,465) – Includes the two groups above Mean 0.23% 0.162 0.24% 0.000*** -0.01% 0.933 Median 0.03% 0.000*** 0.11% 0.000*** -0.05% 0.000*** % Positive 53% 80% 35% Firms with management disclosures about going concern issues ( Mild, mitigating factors, or Explicit statements about substantial doubt) MildMGC (N=33) Mean 7.72% 0.025** 0.37% 0.703 7.35% 0.039** Median 0.33% 0.008*** 0.37% 0.000*** -0.04% 0.153 % Positive 70% 82% 48% MGC with Mitigating Factors (N=12) Mean -10.27% 0.089* -0.18% 0.869 -10.09% 0.117 Median -1.02% 0.233 -0.15% 0.910 -1.37% 0.301 % Positive 50% 42% 42% MGCExp (N=52) Mean 14.78% 0.001*** 1.07% 0.302 13.71% 0.002*** Median 5.44% 0.003*** -0.13% 0.747 4.12% 0.008*** % Positive 67% 44% 63% MGCALL (N=97) - Includes the three groups above Mean 9.28% 0.001*** 0.67% 0.307 8.60% 0.002*** Median 2.05% 0.001*** 0.18% 0.209 0.41% 0.013** % Positive 66% 57% 56%
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Panel B: Distressed Sample
Change in probability of going concern opinion
(∆𝑃𝑃)a
Component due to change in auditor reporting
strategy (∆𝑃𝑃Rep)b
Component due to change in client risk characteristics
(∆𝑃𝑃CRisk)c ∆P p-value ∆PRep p-value ∆PCRisk p-value (1) (2) (3) (4) (5) (6)
Firms with clean management disclosures (silent or explicit statements about absence of going concern issues) MSilent (N=453) Mean 0.55% 0.157 0.41% 0.006*** 0.13% 0.759 Median 0.10% 0.106 0.37% 0.000*** -0.18% 0.000*** % Positive 55% 77% 40% MExpNoGC (N=47) Mean 4.82% 0.055* 1.23% 0.062* 3.59% 0.182 Median 0.95% 0.009*** 0.66% 0.000*** 0.04% 0.271 % Positive 72% 74% 55% MCLEAN (N=500) - Includes the two groups above Mean 0.95% 0.025** 0.49% 0.000*** 0.46% 0.324 Median 0.15% 0.015** 0.39% 0.000*** -0.16% 0.000*** % Positive 56% 76% 42% Firms with management disclosures about going concern issues ( Mild, mitigating factors, or Explicit statements about substantial doubt) MildMGC (N=21) Mean 12.65% 0.016** 1.79% 0.103 10.86% 0.036** Median 4.12% 0.002*** 1.34% 0.000*** 2.44% 0.047** % Positive 76% 76% 71% MGC with Mitigating Factors (N=11) Mean -9.54% 0.110 0.91% 0.672 -10.46% 0.108 Median -3.83% 0.206 -0.83% 0.898 -1.65% 0.148 % Positive 45% 36% 45% MGCExp (N=52) Mean 15.39% 0.000*** 1.66% 0.081* 13.74% 0.001*** Median 6.29% 0.001*** 0.30% 0.251 5.03% 0.006*** % Positive 69% 48% 62% MGCALL (N=84) - Includes the three groups above Mean 11.44% 0.000*** 1.59% 0.022** 9.85% 0.001*** Median 4.72% 0.000*** 1.06% 0.034** 2.44% 0.008*** % Positive 68% 54% 62% *** p<0.01, ** p<0.05, * p<0.1; a P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃)-P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃); b P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃)-P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃); c P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃)-P(𝑋𝑋𝑃𝑃𝑃𝑃𝑃𝑃 , �̂�𝛽𝑃𝑃𝑃𝑃𝑃𝑃)
59
APPENDIX A Variable Definitions
Variable Definitions
AGC 1 if a firm received a going concern modified opinion (i.e., unqualified opinion with an explanatory paragraph) from the auditor and 0 otherwise (Source: Audit Analytics).
MGCExp 1 if management explicitly stated that the firm has going concern problems and 0 otherwise (Source: 10-K). See text for details.
MildMGC 1 if the management made a mild reference to going concern problems and 0 otherwise (Source: 10-K). See text for details.
MGCMit 1 if the management refers to going concern problems along with mitigating factors that alleviate the problems and 0 otherwise (Source: 10-K). See text for details.
MGCALL 1 if the MGCExp=1 or MildMGC=1 or MGCMit=1 and 0 otherwise (Source: 10-K).
MSilent 1 if there is no disclosure of management's opinion on going concern issues and 0 otherwise (Source: 10-K).
MExpNoGC 1 if management explicitly stated that the firm has no going concern problems and 0 otherwise (Source: 10-K).
MCLEAN 1 if MSilent=1 or MExpNoGC=1 and 0 otherwise (Source: 10-K).
POST 1 if fiscal years end after December 15, 2016, the effective date of ASU 2014-15 and 0 otherwise.
CAR The cumulative abnormal return, measured over the three-trading-day period centered on the quarterly earnings announcement date, where the abnormal return is the firms’ return less the CRSP value-weighted market return.
UE The quarterly earnings surprise, computed as earnings per share excluding extraordinary items less the mean of the most recent analyst forecast, deflated by the stock price.
LNMV Log of the market value of common equity. BM The book-to-market ratio.
LEV Total liabilities (Compustat data item LT) divided by total assets (Compustat data item AT).
BETA Firm's beta, estimated over the 200-day window ending 21 days before the earnings announcement for the first quarters, with a minimum requirement of at least 70 trading days.
LOSS 1 if net income or cash flows from operations (Compustat data item OANCF) is negative, and 0 otherwise.
BIG7 1 if the firm is audited by one of the Big 7 auditors (i.e., Big 4, Grant Thornton, BDO, and RSM) and 0 otherwise.
ROA Net income (Compustat data item NI) divided by total assets (Compustat data item AT).
TASSET Natural log of total assets. AGE Number of years since the company was listed in a stock exchange (Source: CRSP).
INVEST Sum of the firm’s cash and investment securities (Compustat data item CHE+IVAEQ), scaled by total assets.
OCF Operating cash flow (Compustat data item OANCF) divided by total assets.
60
REPLAG Number of days between fiscal year-end and auditor’s signature date (Source: Audit Analytics).
FUTFIN 1 if the firm has new financing, where new financing is defined as 10% increase of either equity (Compustat data item SSTK) or debt (Compustat data item DLTIS) and 0 otherwise.
GCLAG 1 if the auditor issues a going concern opinion in the previous year and 0 otherwise. STDRESa Standard deviation of the residual from the market model. BETA2a Slope coefficient of market model regression. RETURNa Common stock returns over the estimation window of the market model (%). a For market variables (STDRES, BETA2, and RETURN), market model is estimated over the 200-day window ending 21 days before the fiscal year end, with a minimum requirement of at least 70 trading days.