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Review of Quantitative Finance and Accounting

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05.08.2020 | Original Research

At what life-cycle stage does the auditors’ going concern report add value?

verfasst von: Kathleen Bakarich, Jiaxin Liu, Joseph Weintrop

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 3/2021

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Abstract

In this paper, we examine the market reaction to going concern audit opinions (GCAO) issued to firms in different life-cycle stages. We find that for firms in the introduction, decline, and shakeout stages there is information content at the time of the publication of a GCAO, reflected by a significant and negative market reaction for these firms relative to mature stage firms. This differential reaction for these life-cycle stages exists for both first-time and second-time GCAO reports, as well as for a subsample of financially distressed firms. Controlling for confounding events, such as debt covenant violations and earnings surprises, these results provide evidence that the auditors’ going concern report provides valuable information to the market during certain life-cycle stages and is consistent with the notion that information opacity exists in early and late life-cycle stages. Furthermore, we find that the variation in the information content of the audit report is conditional on high investor attention. This study overcomes conflicting evidence from prior literature, as to whether the market reacts to a GCAO issuance and whether the market understands the differences in firms’ business strategies in each life-cycle stage, by showing that only after including life-cycle stages is a significant market reaction observed, and that this reaction differs across the stages.

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We refer readers to the extensive literature review by Carson et al. (2013) which contains a summary of work done to date and a roadmap to future research.

AS refers to the auditing standards to be followed by public company auditors codified by the Public Company Accounting Oversight Board (PCAOB). These auditing standards were reorganized in January 2017. AS 2415 replaces the former PCAOB AU section 341. Upon its founding, the PCAOB adopted the American Institute of Certified Public Accountants’ (AICPA) going concern auditing standard (formerly SAS no. 59, now codified in AICPA auditing standards as AU-C 570) (AICPA 2017).

AS 2415.07 states that auditors should consider management plans that may have mitigating effects on the substantial doubts surrounding the company’s going concern status and whether those plans could be effectively implemented when evaluating the company’s going concern issue (PCAOB 2017).

Using this sample window allows us to include debt covenant violation information from prior literature, which is an important control variable to include as it is likely to mitigate investor’s reaction to a GCAO. See Sect. 4 for a further discussion of this variable.

Some life-cycle theories suggest three or four stages in firm life-cycle (e.g. Anthony and Ramesh 1992; Quinn and Cameron 1983). Given we use the empirical construct from Dickinson (2011), we utilize five life-cycle stages.

ASU 2014–15 issued by the FASB provides guidance about management’s responsibility to evaluate whether there is substantial doubt about an entity’s ability to continue as a going concern. In response, the PCAOB issued Staff Practice Alert No. 13 to reinforce the auditor’s responsibility to follow AU Sec. 341 when evaluating an entity’s ability to continue as a going concern (PCAOB 2014).

The mature stage is used as the benchmark in the prediction models. This is described in more detail in the next section.

Dickinson (2011) documents that mature firms earn 1.6% excess returns in the year following the date that financial statement information of the cash flow life-cycle measure becomes available. Introduction (growth) firms earn − 4.8% (− 1.2%) excess returns in the same time period. Dickinson suggests that the market undervalues (overvalues) mature (introduction and growth) firms.

Dickinson (2011)’s life-cycle measure constructed using cash flows is based on economic theory and is not subject to the assumptions that firms are uniformly distributed across the life-cycle spectrum or that firms transition monotonically through the stages, allowing the observations to move across life-cycle stages non-monotonically. An alternative measure, developed by Anthony and Ramesh (1992), is the composite rankings of firms based on their financial characteristics, such as sales growth, dividend payout, capital expenditure and age. Anthony and Ramesh’s methodology assumes that firms move monotonically across life-cycle stages and that the stages follow a uniform distribution.

We estimated the CAR using the Eventus program on the Wharton Research Database Services (WRDS) with an estimation window containing a maximum length of 256 days and minimum length of 3 days. The estimation period begins 46 days before the event date. We use the value-weighted market index in the OLS market model in estimating CAR.

For the early disclosures that occurred before fiscal year 2005, we obtain the early disclosure dates from Menon and Williams (2010)’s authors. For those that occurred after fiscal year 2005, we searched the Lexis-Nexus database to identify the day on which the GCAO was announced.

Because of data availability for control variables, GCAO firm-years are restricted to 130 observations which results in a low test power for thirty-nine regressors in the model (this is explained the in the “Control Variables” discussion below) (Green 1991).

Firms disclose any debt covenant violations from the past year in their 10-K reports. We use the debt covenant violation data from Nini et al. (2012) as a control variable to address the confounding debt information provided by the 10-K that may affect the market reaction in the window of the GCAO issuance. Nini et al. (2012)’s data identify a violation if the keywords default, waiver, violation, modification, and/or not in compliance are in combination with the word “covenant” in the 10-K report.

We lose 303 GCAOs after calculating three-day cumulative abnormal returns using the Eventus program in the Wharton Research Data Services and the daily security returns in CRSP.

Available at https://faculty.chicagobooth.edu/amir.sufi/chronology.html.

While the definitions of the shakeout stage have been vague in previous studies, these firms appear to have slowing growth and declining prices because of hindered competitive flexibility (Wernerfelt 1985), as they are entering into the post-mature stage. Shakeout firms tend to focus on reorganizing/revitalizing their business, while they also tend to receive fewer going-concern opinions than introduction and decline firms. Dickinson (2011) shows that a significant portion of shakeout firms will revert to the growth and mature stage in the following year(s). In fact, the shakeout firms make up the smallest group of GCAO firms even before we deleted observations missing required control variables. That being said, loss of observations due to control variables are not systematically biasing our sample in terms life cycle stage composition of the sample firms. In fact, the shakeout stage firms represent only 7.9% of the original Compustat, Audit Analytics and CRSP merged sample (untabulated). About 3.85% of firms in our final sample are shakeout firms. The final sample consists of slightly more growth firms (by 3%) and mature firms (by 0.7%) than the original sample.

In an untabulated robustness test discussed in Sect. 7, we combine the shakeout and decline stage firms.

To rule out multicollinearity among the variables, we calculate the VIF values (untabulated) and find that all VIF values are at acceptable levels (all VIFs < 5; CFO VIF = 3.94 and Zscore VIF = 3.39).

The CAR in Menon and Williams (2010) is -0.0628 for first-time GCAOs which is similar to the CAR displayed in Table 5 Panel C in our paper.

We have also conducted an F-test of the equality of coefficients of different stages. The untabulated results show that the coefficients for the introduction and growth stages are significantly different from each other. The same hold for the shakeout and growth stages as well as the decline and growth stages. For example, the F-statistic from testing the introduction and growth stage coefficient equality is 15.36 with p < 0.001(untabulated). The main regression results show that growth and mature stage are not significantly different from each other. Therefore, these results corroborate our main findings that the GCAOs received by introduction and decline stage firms are associated with more negative market reaction than mature stage. Tabulated results are available upon request.

For the ease of presentation, we suppressed the control variables in the results table. The signs of the coefficients of the control variables are qualitatively similar to those in Table 6. The results are available upon request.

Companies having an Altman’s Z-score under 1.8 suggests looming bankruptcy, while above 3 suggests that firms are unlikely to go bankrupt.

We calculate the number of analysts following the firm and the median analyst coverage by year. The high (low) attention sample consists of firm-years with analyst coverage above (below) the median.

We repeat the above tests using an alternative investor attention measure, size, and alternative information opacity measures, analyst forecast dispersion, discretionary accruals, and absolute analyst forecast errors. Results (untabulated) are qualitatively similar, but not as statistically significant for CAR(− 1, + 1). There are both qualitatively and quantitatively similar results using CAR(0, + 2), which suggests that our results are robust to different investor attention and information opacity measures.

However, we recognize the limitation of this test due to the reduced sample size. Conditioning on high attention, we only have 40 GCAOs, and when intersecting with the Big Four auditor-only sample, we are left with only 38 GCAOs. Therefore, the results should be interpreted with caution.

Similar to Menon and Williams (2010), we include the concurrent earnings surprise to control for confounding information in the window of the audit opinion release. We estimate a regression of CAR on a set of control variables that explains the market reaction around the audit report. We estimate the regression for each life cycle stage and examine whether the intercept of each regression is significantly different from zero. Menon and Williams (2010) interpret the intercept as the portion market reaction explained by the GCAO announcement on top of the control variables.

We have also repeated this test for the CAR(0, + 2) window and the results show that both the introduction and decline stages are associated with significant negative market reactions, while the other stages are not.

We estimate the predicted probability of a GCAO following the logit GCAO prediction model developed in Fargher and Jiang (2008). The model predicts that the introduction and decline stages are associated higher likelihoods of receiving GCAOs relative to the mature stage.

These results are robust to the first-time GCAO sample.

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Titel: At what life-cycle stage does the auditors’ going concern report add value?
verfasst von: Kathleen Bakarich
Jiaxin Liu
Joseph Weintrop
Publikationsdatum: 05.08.2020
Verlag: Springer US
Erschienen in: Review of Quantitative Finance and Accounting / Ausgabe 3/2021
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-020-00921-w

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