Abstract
This study examines whether auditors serve as a conduit for disseminating Securities and Exchange Commission (SEC) views on reporting and disclosure matters as the result of being privy to clients’ SEC comment letters. This examination is important because auditors’ involvement in and private access to clients’ comment letters can enhance the timeliness of dissemination and constrain reporting or disclosure choices that diverge from SEC views. Among clients with a greater expectation of impaired goodwill that do not receive a comment letter with a goodwill-related comment, we find a greater likelihood of goodwill impairment when the audit firm serving the client is exposed to more goodwill-related comments received by other clients. Further examination of the channels of dissemination through the audit firm indicates that the results are driven by auditor exposure through other clients of the audit office in the same industry, the channel with the greatest exposure to the audit team, and clients in different audit offices in different industries, the channel with the broadest potential for spillover (i.e., the greatest number of other audit firm clients). Importantly, we observe these effects after controlling for alternative sources of spillover and when auditor comment letter exposure is not yet publicly available, suggesting that auditors’ private access to client comment letters facilitates timely spillover. Further analyses indicate that spillover through industry clients within the audit office is also apparent in goodwill footnote disclosure.
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Data Availability
Data are publicly available from the sources identified in the paper.
Notes
Throughout the study, a comment letter refers to a complete, unique comment letter conversation. Following Cassell et al. (2013), a comment letter conversation includes a minimum of three total letters, including the initial letter from the SEC and the final “no further comment” letter to end the conversation. Following Cassell, Cunningham, and Lisic (2019), we remove letters seeking an extension, letters with no substantive information, cover letters, duplicate letters, and “Tandy letters.”
In Cassell et al.’s (2013) sample, the average duration of a conversation is approximately 80 days.
While we recognize that not all comment letters request accounting changes and are often requests for additional clarification or disclosure, we argue that an auditor’s exposure to these requests leads to an increased likelihood of identifying evidence for the need to impair at-risk goodwill, which increases the likelihood that the auditor will deem an impairment necessary.
In our arguments, we assume that the receipt of an SEC comment letter increases the risk of restatement or of an SEC enforcement action. We validate this assumption by examining the association between the receipt of a comment letter and subsequent restatement announcements and SEC Accounting and Auditing Enforcement Releases (AAERs). Consistent with this assumption and prior evidence (Blackburne et al. 2021), we find a positive association between comment letters and subsequent restatements and SEC AAERs. We provide the results of this examination in Appendix 1.
Audit partner data from the PCAOB Form AP database is only available for a small portion of our sample period (2016 through 2020). After obtaining and merging this data with the sample for our tests, we note descriptively that although 53.3 percent of the audit partners in our sample have more than one public audit client, only 3.4 percent have more than one public audit client with at-risk goodwill.
SOX 408 mandate that these periodic reviews must include a review of Form 10-K.
The number and composition of these offices have changed over time (see https://www.sec.gov/corpfin/announcement/cf-disclosure-program-realignment).
Ayres et al. (2019a, b) include a dummy variable for expected impairment and an interaction term between their variable of interest and their measure of expected impairment rather than dropping observations not expected to impair. We find, in an untabulated robustness test, that the inferences from the test of our hypothesis are similar if we use this alternative specification; however, the inclusion of numerous interaction terms with the various dissemination paths in our models leads to significant multicollinearity issues. We find high VIFs (above 10) on most of our interaction terms and several control variables when we use this alternative specification.
Since the market and book value of assets are computed at the consolidated entity-level and impairment decisions are made at the reporting unit level, using these measures to identify expected impairment could exclude companies whose goodwill is impaired at the reporting unit level but is not expected at the consolidated level. However, this potential measurement error is a limitation of this and other goodwill studies because of the unavailability of reporting unit-level data. In a robustness test discussed in Section 5, we limit our sample to companies with one business segment and find consistent results with those in our main analyses, except that the significance on SameAF, DiffAO, and DiffAO_DiffInd become significant at the p < 0.10 level (two-tailed). Additionally, we find similar results using alternative measures for expected impairment.
We recognize that a comment letter conversation that becomes public after fiscal year-end but before filing could provide some limited public exposure before completion of the audit. However, we argue that these comments would be known by and could inform the audit firm. Still, we recognize that any disclosure after year-end and before the issuance of the audit report, even with a short window of public exposure, could influence impairment decisions, and, as such, we determine the robustness of our findings to this design choice. To do so, we alternatively capture private and public comment letter exposure as of a nonrecipient client’s audit report date. We find similar results in both sign and significance using this alternative measurement date.
For each of these measures of publicly available comment letter exposure, we include goodwill-related comments received by other clients of a company’s audit firm that are publicly available. We acknowledge that this choice removes some of the comment letter exposure through the audit firm from the respective audit firm measures of exposure to goodwill comments. Although this choice could work against our finding support for our hypothesis, it tightens the identification of exposure through the audit firm. We find, in untabulated results, that inferences are similar if we include all comment letter exposure (private and public) from the past year in the measures of goodwill-related comment exposure through the auditor. These results are consistent with auditors being responsive to comments received by other clients of their firm, whether those comments are public or private.
In an untabulated analysis, we find that results are similar in sign and significance if we instead define industry based on two-digit SIC codes.
To determine the sensitivity of our results to winsorization, we re-estimate our tests without winsorization and find results similar in both sign and significance.
However, the results are similar in sign and significance with the inclusion of these observations.
This materiality threshold is consistent with quantitative materiality levels used by eight of the nine largest U.S. audit firms (Eilifsen and Messier 2015). The results are similar in sign and significance with the inclusion of these firm-year observations.
Inferences are unchanged if observations during the financial crisis (2008) and COVID-19 (2020) are excluded from the model.
Calculated as the estimated regression coefficient of the explanatory variable times the standard deviation of the explanatory variable divided by the mean of the dependent variable per (Mitton 2023) [(0.031*1.257)/0.345 = 0.113].
We recognize that sometimes companies provide limited disclosure about goodwill and impairment in the significant accounting policies footnote. Given the limited disclosure around goodwill in this note and the difficulty of properly capturing “goodwill-related disclosure,” we have focused our analysis on companies that provide a specific footnote pertaining to goodwill.
In additional untabulated analysis, we partition each of the four variables of interest (SameAO_SameInd, SameAO_DiffInd, DiffAO_SameInd, and DiffAO_DiffInd) based on whether the comment letter(s) to which the auditor is exposed in these channels requests additional disclosure or additional information. We note that 54.9 percent request more financial statement disclosure while 48.4 percent request additional information in the comment letter response letter (15.1 percent request both). We find a positive and marginally significant coefficient on SameAO_SameInd_MoreDisclose (p < 0.10) but an insignificant coefficient on SameAO_SameInd_MoreInfo. These results suggest that greater exposure to comments requesting more goodwill-related disclosure received by other office clients within the same industry increases the likelihood of textual changes in the goodwill footnote.
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Acknowledgements
We thank Anne Albrecht, Greg Burton, Brant Christensen, Lauren Cunningham, Michael Drake, Michael Ettredge, Joshua Hunt, Andrew Imdieke (discussant), Joshua Lee, Karen Nelson, Stephen Rowe, Jonathan Shipman, Jim Stice, Jake Thornock, Jenny Tucker, Melissa Western, Michael Wilkins, Michael Willenborg, workshop participants at Brigham Young University, Texas Christian University, the University of Kansas, and the University of Arkansas, and conference participants at the 2019 American Accounting Association Annual Meeting and the 2019 Texas Audit Research Symposium for their helpful comments and suggestions. Kenneth Bills gratefully acknowledges financial support from the Plante Moran Faculty Fellowship at Michigan State University, and Timothy Seidel gratefully acknowledges financial support from the Glen D. Ardis Fellowship at Brigham Young University.
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Appendices
Appendix 1 The association between SEC comment letters and subsequent restatements and SEC AAERs
The study argues that SEC attention and scrutiny on particular accounting or disclosure matters (as evidenced from a comment letter) can increase the risk of restatement of previously filed financial statements or the risk of an SEC Accounting and Auditing Enforcement Release (AAER), which can strain the auditor–client relationship and increase the likelihood of subsequent auditor–client realignments (e.g., Hennes et al. 2014). Research that finds a positive association between SEC comment letters and the initiation of SEC investigations supports this argument (Blackburne et al. 2021). In this appendix, we validate this assumption by examining broadly the association between the initial receipt of an SEC comment letter and restatement announcements as well as SEC AAERs in the following two years. To do this we estimate the following regression model based on prior studies examining accounting misstatements (e.g., Romanus et al. 2008; Newton et al. 2013; Ettredge et al. 2014) using all company-year observations with available data from Audit Analytics between 2005 and 2021, inclusive:
The results of the regression are provided in the table below:
Dependent Variable: RestateFut | ||||
|---|---|---|---|---|
(1) | (2) | |||
Variables | Coefficient | t-stat | Coefficient | t-stat |
CommentLetter | 0.010*** | (5.435) | 0.008*** | (4.787) |
Size | −0.001 | (−0.763) | −0.001 | (−0.930) |
SizeSq | −0.000* | (−1.756) | −0.000 | (−1.622) |
Big4 | −0.025*** | (−9.600) | −0.022*** | (−8.749) |
Spec | −0.009*** | (−3.039) | −0.009*** | (−3.091) |
NAFeeRatio | −0.004 | (−0.551) | −0.005 | (−0.740) |
LnAuditFees | 0.010*** | (4.317) | 0.009*** | (4.191) |
ShortTenure | 0.007*** | (3.976) | 0.006*** | (3.802) |
MatWeak | 0.071*** | (13.887) | 0.069*** | (13.463) |
EPR | −0.002** | (−2.437) | −0.001** | (−2.147) |
Loss | 0.010*** | (4.733) | 0.009*** | (4.515) |
ROA | −0.001 | (−1.417) | −0.001 | (−1.209) |
BTM | 0.001 | (0.353) | 0.001 | (0.575) |
EPSGrowth | −0.009** | (−2.569) | −0.007** | (−2.183) |
Constant | 0.088*** | (13.622) | 0.078*** | (12.465) |
Year FE | Yes | Yes | ||
Industry FE | Yes | Yes | ||
N | 81,716 | 79,795 | ||
Adjusted R-squared | 0.030 | 0.028 | ||
We also obtain SEC AAER data from the authors of Dechow et al. (2011) and estimate the following regression model using all company-year observations with available data from Audit Analytics between 2005 and 2016, inclusive:
The results of the regression are provided in the table below:
Dependent Variable: AAERFut | ||
|---|---|---|
Variables | Coefficient | t-stat |
CommentLetter | 0.317*** | (3.060) |
Size | 0.109 | (0.914) |
SizeSq | −0.013 | (−1.440) |
Big4 | −0.381** | (−2.004) |
Spec | 0.017 | (0.071) |
NAFeeRatio | −1.095* | (−1.899) |
LnAuditFees | 1.159*** | (7.638) |
ShortTenure | 0.056 | (0.425) |
MatWeak | 1.252*** | (7.864) |
EPR | 0.034 | (1.117) |
Loss | 0.146 | (1.080) |
ROA | −0.041 | (−1.336) |
BTM | 0.457** | (2.290) |
EPSGrowth | 0.139 | (0.467) |
Constant | −6.673*** | (−8.489) |
Year FE | Yes | |
Industry FE | Yes | |
N | 66,791 | |
Adjusted R-squared | 0.011 | |
Appendix 2 The association between SEC comment letters and subsequent goodwill impairments
In this appendix, we test whether companies that receive a comment letter with a goodwill-related comment are more likely to record a goodwill impairment. To perform this analysis, we use the following model:
GWCommentLetter is an indicator variable equal to one if the company received a comment letter with a goodwill-related comment during the current fiscal year and zero otherwise. ExpectImpair is a dummy variable equal to one if the company’s pre-impairment book value of assets is less than its book value of equity and zero otherwise. Note that Impair reflects nonrestated impairment charges taken after the initial comment letter. We removed all observations from the sample where a goodwill impairment was recorded prior to the initial comment letter date. We find that the coefficient on GWCommentLetter is positive, consistent with the receipt of goodwill comment letters having a direct effect on the likelihood of impairment. Interestingly, we also find an insignificant coefficient on GWCommentLetter*ExpectImpair, indicating that companies that receive goodwill-related comments from the SEC are just as likely to record an impairment if they have an observable financial indicator of the need for impairment (market-to-book value of assets is less than one) or if they do not. Since the assessment of fair value to determine the need for impairment is performed at the reporting unit level rather than the consolidated financial statement level, companies may require impairment without this observable indicator (i.e., book value of assets exceeds the market value). Direct SEC goodwill scrutiny appears to result in a similar likelihood of impairment for companies with or without this indicator.
Dependent Variable: Impair | ||
|---|---|---|
Variables | Coefficient | t-stat |
GWCommentLetter | 0.037*** | (4.026) |
ExpectImpair | 0.116*** | (12.411) |
GWCommentLetter*ExpectImpair | −0.017 | (−0.633) |
Size | 0.018*** | (7.972) |
ROA_PreImpair | 0.001 | (0.060) |
Loss_PreImpair | 0.057*** | (8.131) |
LnBusSeg | 0.031*** | (4.912) |
Leverage_PreImpair | −0.000 | (−0.043) |
EBITDAChg | −0.218*** | (−14.352) |
IntangPercent | 0.213*** | (12.438) |
AcqGoodwill | −0.020*** | (−3.611) |
ReturnStDev | 0.640*** | (16.783) |
AnnualReturn | −0.110*** | (−22.650) |
InstOwn | 0.034*** | (3.520) |
LnAnalyst | −0.025*** | (−6.254) |
Big4 | 0.009 | (1.138) |
Spec | 0.008 | (0.528) |
AOClientCount | −0.009** | (−2.438) |
OfficeImpair | 0.024*** | (4.905) |
AvgCLIssues | −0.003*** | (−3.302) |
Restate | 0.001 | (0.095) |
AAER | 0.002 | (0.065) |
GWDeficiency | 0.003 | (0.582) |
MeetOrBeat | −0.019*** | (−4.079) |
SmallProfit | 0.017 | (1.579) |
Constant | −0.117*** | (−7.400) |
Year FE | Yes | |
Industry FE | Yes | |
N | 33,253 | |
Adjusted R-squared | 0.136 | |
Appendix 3 Variable definitions
AAER | Indicator variable equal to one if the company receives any AAERs in the current year and zero otherwise |
AAERFut | Indicator variable equal to one if the company receives any AAERs in the subsequent two years and zero otherwise |
AcqGoodwill | Indicator variable equal to one if the company performed an acquisition that increased goodwill during the current year and zero otherwise |
AnnualReturn | The company’s buy-and-hold monthly stock return for the previous 12 months |
AOClientCount | The natural logarithm of one plus total number of clients served by the company’s audit office in the current year |
AvgCLIssues | The average number of issues discussed in the comment letters received by the clients of a company’s auditor in the past year |
Big4 | Indicator variable equal to one if the company’s auditor is a Big 4 auditor and zero otherwise |
BTM | Book to market value of equity |
CommentLetter | Indicator variable equal to one if the company received a comment letter in the current year and zero otherwise |
DiffAO | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients in different audit offices that are not publicly available as of the end of the year |
DiffAO_DiffInd | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients in different industries and different offices that are not publicly available as of the end of the year |
DiffAO_DiffInd_Copied | The natural logarithm of one plus the number of comment letters with a goodwill comment by an audit firm’s clients in different industries and different offices that copied the auditor and are not publicly available as of the end of the year |
DiffAO_DiffInd_NonSevere | The natural logarithm of one plus the number of comment letters with a goodwill comment that did not result in a goodwill impairment by an audit firm’s clients in different industries and different offices that are not publicly available as of the end of the year |
DiffAO_DiffInd_NotCopied | The natural logarithm of one plus the number of comment letters with a goodwill comment by an audit firm’s clients in different industries and different offices that did not copy the auditor and are not publicly available as of the end of the year |
DiffAO_DiffInd_Severe | The natural logarithm of one plus the number of comment letters with a goodwill comment that resulted in a goodwill impairment by an audit firm’s clients in different industries and different offices that are not publicly available as of the end of the year |
DiffAO_SameInd | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients in the same industry but different offices that are not publicly available as of the end of the year |
DiffAO_SameInd_Copied | The natural logarithm of one plus the number of comment letters with a goodwill comment by an audit firm’s clients in same industries but different offices that copied the auditor and are not publicly available as of the end of the year |
DiffAO_SameInd_NonSevere | The natural logarithm of one plus the number of comment letters with a goodwill comment that did not result in a goodwill impairment by an audit firm’s clients in same industries but different offices that are not publicly available as of the end of the year |
DiffAO_SameInd_NotCopied | The natural logarithm of one plus the number of comment letters with a goodwill comment by an audit firm’s clients in same industries but different offices that did not copy the auditor and are not publicly available as of the end of the year |
DiffAO_SameInd_Severe | The natural logarithm of one plus the number of comment letters with a goodwill comment that resulted in a goodwill impairment by an audit firm’s clients in same industries but different offices that are not publicly available as of the end of the year |
DiffInd_DiffMSA | The natural logarithm of one plus the number of comment letters with a goodwill comment that are publicly disclosed and received by companies in a different industry and MSA but served by a different auditor |
DiffInd_SameMSA | The natural logarithm of one plus the number of comment letters with a goodwill comment that are publicly disclosed and received by companies in a different industry but same MSA but served by a different auditor |
EBITDAChg | The change in a company’s EBITDA from time t-1 to time t, scaled by the total market value of equity |
EPR | Basic earnings per share (including extraordinary items) divided by the stock price of the company |
EPSGrowth | Indicator variable equal to one if the company has four consecutive quarters of earnings per share (including extraordinary items) growth and zero otherwise |
ExpectImpair | Indicator variable equal to one if a company’s market-to-book value of assets is less than one and zero; otherwise following Ayres et al. (2019a, b) |
GWCommentLetter | Indicator variable equal to one if the company received a comment letter with a goodwill-related comment during the current fiscal year and zero otherwise |
GWDeficiency | Indicator variable equal to one if an audit deficiency related to goodwill impairment was included in the most recent PCAOB inspection report of a company’s audit firm and zero otherwise |
GWFNChg | Indicator variable equal to one if a company’s goodwill footnote change measured as the cosine of the angle between the vectors of a company’s goodwill footnote in year t and year t-1 following Peterson et al. (2015) is above the median in the sample and zero otherwise |
Impair | Indicator variable equal to one if the company recorded a goodwill impairment during the fiscal year and zero otherwise |
InstOwn | The percentage of a company’s stock that is held by institutional owners |
IntangPercent | The pre-impairment percentage of a company’s assets that is composed of goodwill |
Leverage_PreImpair | The ratio of short-term and long-term debt to pre-impairment book value of equity |
LnAnalyst | The natural logarithm of one plus the number of unique analysts who issued earnings forecasts for the fiscal year-end |
LnAuditFees | The natural logarithm of one plus the amount of audit fees |
LnBusSeg | The natural logarithm of one plus the number of business segments |
Loss | Indicator variable equal to one if the company incurred a net loss and zero otherwise |
Loss_PreImpair | Indicator variable equal to one if the company incurred a pre-impairment loss and zero otherwise |
MatWeak | Indicator variable equal to one if the company received an adverse internal control opinion within the previous two years and zero otherwise |
MeetOrBeat | Indicator variable equal to one if a company met or just beat the most recent analyst consensus earnings forecast |
MTB | The ratio of market value of equity divided by the book value of equity |
NAFeeRatio | The ratio of non-audit fees paid to the external auditor to total fees paid to the external auditor |
OfficeImpair | Indicator variable equal to one if any of the audit office’s other clients in the past year recorded a goodwill impairment and zero otherwise |
Restate | Indicator variable equal to one if the company announced a restatement of its financial statements in the current year |
RestateFut | Indicator variable equal to one if the company announces a restatement on Item 4.02 on Form 8 K in the subsequent two years and zero otherwise |
ReturnStDev | The standard deviation of the monthly stock returns for the previous 12 months |
ROA | Return on assets measured as net income divided by the average total assets for the year |
ROA_PreImpair | Return on assets measured as pre-impairment net income divided by the average total assets for the year |
SameAO | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients that are not publicly available as of the end of the year |
SameAO_DiffInd | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients in the same audit office but different industry that are not publicly available as of the end of the year |
SameAO_DiffInd_Copied | The natural logarithm of one plus the number of comment letters with a goodwill comment by an audit firm’s clients in the same audit office but different industry that copied the auditor and are not publicly available as of the end of the year |
SameAO_DiffInd_NonSevere | The natural logarithm of one plus the number of comment letters with a goodwill comment that did not result in a goodwill impairment by an audit firm’s clients in the same audit office but different industry that are not publicly available as of the end of the year |
SameAO_DiffInd_NotCopied | The natural logarithm of one plus the number of comment letters with a goodwill comment by an audit firm’s clients in the same audit office but different industry that did not copy the auditor and are not publicly available as of the end of the year |
SameAO_DiffInd_Severe | The natural logarithm of one plus the number of comment letters with a goodwill comment that resulted in a goodwill impairment by an audit firm’s clients in the same audit office but different industry that are not publicly available as of the end of the year |
SameAO_SameInd | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients in the same audit office and industry that are not publicly available as of the end of the year |
SameAO_SameInd_Copied | The natural logarithm of one plus the number of comment letters with a goodwill comment by an audit firm’s clients in the same audit office and industry that copied the auditor and are not publicly available as of the end of the year |
SameAO_SameInd_NonSevere | The natural logarithm of one plus the number of comment letters with a goodwill comment that did not result in a goodwill impairment by an audit firm’s clients in the same audit office and industry that are not publicly available as of the end of the year |
SameAO_SameInd_NotCopied | The natural logarithm of one plus the number of comment letters with a goodwill comment by an audit firm’s clients in the same audit office and industry that did not copy the auditor and are not publicly available as of the end of the year |
SameAO_SameInd_Severe | The natural logarithm of one plus the number of comment letters with a goodwill comment that resulted in a goodwill impairment by an audit firm’s clients in the same audit office and industry that are not publicly available as of the end of the year |
SameAF | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients that are not publicly available as of the end of the year |
SameAF_SameInd | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients that are in the same industry and not publicly available as of the end of the year |
SameAF_DiffInd | The natural logarithm of one plus the number of comment letters with a goodwill comment received by an audit firm’s clients that are in a different industry and not publicly available as of the end of the year |
SameInd_DiffMSA | The natural logarithm of one plus the number of comment letters with a goodwill comment that are publicly disclosed and received by companies in the same industry but different MSA but served by a different auditor |
SameInd_SameMSA | The natural logarithm of one plus the number of comment letters with a goodwill comment that are publicly disclosed and received by companies in the same industry and MSA but served by a different auditor |
ShortTenure | Indicator variable equal to one if the current auditor has been the external auditor for less than four years and zero otherwise |
Size | The natural logarithm of one plus total assets (in millions) |
SizeSq | The squared value of Size |
SmallProfit | Indicator variable equal to one if a company has ROA (net income divided by the average assets for the year) between 0 and 1 percent |
Spec | The ratio of audit fees that an audit office generates in a three-digit SIC industry to the total audit fees generated by an audit office in a given year |
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Bills, K.L., Cating, R., Lin, C. et al. The spillover effect of SEC comment letters through audit firms. Rev Account Stud (2024). https://doi.org/10.1007/s11142-023-09819-z
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DOI: https://doi.org/10.1007/s11142-023-09819-z