Abstract
Prior research on SEC comment letters has almost exclusively focused on reviews of periodic filings, such as 10-Ks. Transactional filing reviews, such as those related to mergers and acquisitions (M&A), are a priority of the SEC to which it dedicates significant resources. We help fill the void in the literature by examining the influence of SEC comment letters on one type of transactional filing, Form S-4, on the accounting quality of a newly merged entity. We find that S-4s that receive an SEC comment letter are less likely to have a restatement or a goodwill impairment after a merger or acquisition is completed. Our inferences remain the same using either an entropy-balanced sample or a propensity-score-matched sample based on firm and deal characteristics. These results are stronger for S-4 comment letters with higher intensity and M&A-specific comments. Finally, to explore plausible mechanisms and provide context, we examine specific disclosure changes in S-4 amendments filed during the filing review process and find evidence that the improved M&A accounting quality is related to revisions to the pro forma financial statements, the total purchase price, and goodwill allocations. Overall, our findings provide evidence on the effectiveness of the SEC’s comment letter process related to M&A.
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Notes
These priorities are consistent with the SEC’s mission “to protect investors, maintain fair, orderly, and efficient markets, and facilitate capital formation.” See https://www.sec.gov/Article/whatwedo.html.
Once the SEC has completed its review of the registration statement, the filing is declared “effective,” meaning the transaction can proceed and the newly registered shares can be issued. The date when the transaction goes live is referred to as the “effectiveness date.”
These statistics are from the 2018 Factset Mergerstat Review at https://www.bvresources.com/docs/default-source/book-excerpts/mergerstat_review_2018_excerpt.pdf?sfvrsn=8060cfb2_2. A recent Deloitte M&A trends publication (https://www2.deloitte.com/us/en/pages/mergers-and-acquisitions/articles/ma-trends-report.html) provides survey evidence that M&A activity is on the rise.
See Figure 1 on page 14 of the 2016 GAO Report at https://www.gao.gov/assets/690/680352.pdf.
Ege et al. (2020) use transactional filing review waves as a shock to SEC resource constraints but still focus on the quality of the periodic filing comment letters.
See https://www.sec.gov/corpfin/announcement/cf-announcement%2D%2D-no-review-letters.html for the SEC’s announcement regarding the disclosure of registration statements not selected for review.
Appendix 7. includes some examples of S-4 M&A-specific comments.
In our manual reading of the S-4 filings in our sample, we did not find any other type of transaction, such as recapitalizations, acquisitions of remaining interests, or buybacks.
Our results are robust if we retain these additional observations.
Our descriptive statistics are consistent with the M&A literature, with the exception of tender offer percentage, which is much lower in our sample. This is because tender offers are mostly 100% cash deals, which are excluded from our final sample because they do not require an S-4 filing. Our main results are robust to eliminating all tender offers from our sample and dropping the tender offer indicator variable from the regression models.
Periodic filings, such as 10-Ks, are scheduled for review throughout the fiscal year after they are filed.
Although we have no way to quantify the amount of SEC resources allocated to the S-4 filing review process, the overall resources dedicated to the SEC’s Division of Corporation Finance is approximately $180 million per year and involves 400 full time employees. About 15% (630/4210) of the number of reviews performed by the division in 2020 related to ‘33 Act IPO filings. The proportion of other ‘33 Act filing reviews, including S-4s, is not publicly disclosed (see the 2022 SEC Congressional Budget Justification Report at https://www.sec.gov/files/FY%202022%20Congressional%20Budget%20Justification%20Annual%20Performance%20Plan_FINAL.pdf). Ege et al. (2020) state that a “nontrivial” amount of the division’s resources is dedicated to reviews of acquisitions, and those along with IPO reviews are the types of transactional filing reviews most likely to constrain SEC resources. They further report that 25% of all initial comment letters on transactional filings in Audit Analytics reference acquisition-related filings, which are second only to IPOs.
Similar to Bens et al. (2012), we focus on restatements as one of the main accounting quality measures because restatements capture violations of GAAP. As Bens et al. (2012) argue, two other commonly used measures of accounting quality—abnormal accruals and SEC Accounting and Auditing Enforcement Releases (AAERs)—are not ideal in our setting because abnormal accrual estimations tend to be noisy and AAERs are very infrequent in the M&A setting.
One component of goodwill is the “going concern” value of the target, which is defined as the target’s ability “to earn a higher rate of return on an organized collection of net assets than would be expected if those net assets had to be acquired separately” (Johnson and Petrone 1998). This component of core goodwill derives its value from the elements of the target’s business that do not qualify for asset recognition, such as human capital, unique manufacturing processes, etc., or from the target’s competitive advantages. A second economic component of goodwill is the expected synergies between the combined entities due to the opportunity to share resources and enjoy other complementarities (Linsmeier et al. 2020). The third component of goodwill is errors in identifying and measuring the net assets resulting in goodwill to be either overstated or understated. Shalev et al. (2013) and Zhang and Zhang (2017) show that goodwill allocations are overstated due to compensation incentives to avoid amortization associated with separately identified intangible assets. Dowdell and Press (2004) document the “excessive” write-offs of in-process R&D acquired in a business combination to avoid allocation to goodwill. Koonce et al. (2021) show that, in the presence of multiple intangible assets, executives have incentives to both over-allocate and under-allocate fair value to goodwill and that they use the inherent uncertainty underlying the fair value estimates to justify their preferences. The fourth component represents overpayment, which Henning et al. (2000) estimate represents about 30% of the average recognized goodwill in their sample. Note that the overpayment could be in real terms or in the (stock) consideration exchanged being overvalued.
Despite the forgoing explanation, we acknowledge that a goodwill impairment may also indicate accounting quality in the future (i.e., after deal completion), in addition to being a signal of the level of M&A accounting quality at the time of the SEC’s S-4 review. Merged companies may have incentives to delay a goodwill impairment beyond our future one-year measurement period. However, we feel this would bias against our results. Prior literature suggests that the receipt of an SEC comment letter is a salient cue that the regulators are observing the company (Cunningham et al. 2020; Blackburne et al. 2022), incentivizing the comment letter recipients to recognize an incurred impairment in a timely manner. Alternatively, companies may be incentivized to take a goodwill impairment too early as a “big bath.” As discussed below, we control for big bath incentives as well as other macroeconomic factors that would influence the timing of a goodwill impairment. Another limitation of using future goodwill impairments as a proxy for M&A accounting quality is that it does not capture under-allocation of goodwill or underpricing of M&A, as goodwill is not allowed to be subsequently written up. U.S. GAAP also does not allow amortization of goodwill during our sample period.
Following Cahan (1992), we hand collected data on which of the S-4 M&A deals in our sample also had an antitrust investigation by the Department of Justice or the Federal Trade Commission. Specifically, we performed Google searches for the keyword “antitrust,” which generated mentions of antitrust investigations in online news sources, such as LexisNexis, or the agencies’ official websites. These cases represent about 12.5% of our sample of S-4 M&A deals with a roughly even proportion between the Department of Justice, the Federal Trade Commission, and unidentified.
As robustness tests, we control for other target characteristics, such as leverage, market-to-book ratio, and return on assets, as well as other acquirer characteristics, such as tangible asset ratio, free cash flow, and sales growth. All these variables are measured at the fiscal year-end before the M&A announcement. Although the sample size is significantly reduced by about 27%–33% (depending on the test), the results are consistent with those tabulated.
Word count relates to the number of comments contained in the SEC comment letters. However, we feel this measure better captures the construct of complexity or intensity of the comments than the number of comments estimated in other studies by the number of issue codes in Audit Analytics, which may double count one comment that falls under multiple issue categories.
We use the following M&A-specific comment letter taxonomy codes from Audit Analytics: #177 - Acquisitions, mergers, and business combinations (29%), #208 – Intangible assets and goodwill (20%), and #209 – Pro forma financial information reporting issues (44%). The most common accounting issues referenced in the S-4 comment letters include #935 – fair value (28%), #214 – income taxes (11%), and #212 – revenue recognition (6%). Note these figures represent the percentage of S-4 comment letter conversations that include at least one comment falling into the applicable category. Also see Appendix 7. for some illustrative examples.
The variance-inflation-factors are all less than 3.8 in each model, suggesting that multicollinearity is not a significant concern.
The overall significance of the control variables and the pseudo R-squared in our models is consistent with those in Marquardt and Zur (2015).
This evidence is also consistent with the work of Paugam et al. (2015), which documents a positive association between abnormal goodwill and the frequency and magnitude of future goodwill impairments and deterioration of future performance, suggesting that future goodwill impairments capture the economic effect of overpriced goodwill at the time of the acquisition.
Our results are robust to using a linear probability model, instead of the probit model in Equation (1). The results are also robust if we include additional controls for any restatements and goodwill impairment occurring between the M&A announcement and completion dates.
These figures reflect the percentages of the restatements in our sample, not the total percentage of our sample observations.
Through our manual process of excluding these transactions from our main sample, we found that exchange offer S-4 filings typically involve the exchange of one class of debt securities for a newly registered class of debt securities.
Our results are qualitatively similar if we use the above-median rather than above-the-top-quartile word count for high-intensity comment letters.
All the cross-sectional results hold (untabulated) if we define the measurement window for the M&A accounting quality variables as two years following deal completion.
Compared to the CL = 0 S-4s, the CL = 1 S-4s have a 25% higher proportion of downward purchase price revisions (35/77–1/5) in panel C and a 11% higher proportion of downwards goodwill allocation revisions (39/77–2/5) in panel D.
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Acknowledgments
We thank Patricia Dechow (Editor), two anonymous reviewers, Andrew Acito, Julia Ariel-Rohr, Jason Ashby, In Gyun Baek, Zahn Bozanic, Amanda Carlson, Willie Choi, Derek Christensen, Eric Condie, Matt Ege, Dave Folsom, Rachel Geoffroy, Emily Griffith, Feng Gu, Eric Holzman, Zach King, Jason Kuang, Stacie Laplante, Dan Lynch, Nikki MacKenzie, Brian Monsen, Robbie Moon, John Robinson, Kathy Rupar-Wang, Divesh Sharma, Steve Utke, Dan Wangerin, Terry Warfield, Karla Zehms, and workshop and conference participants at George Mason University, George Washington University, Georgia Tech, Kennesaw State University, UNC–Greensboro, University of Louisville, University of Wisconsin-Madison, Vanderbilt University, Virginia Tech, and the 2019 BYU Accounting Research Symposium for their helpful comments and suggestions. Ling Lisic gratefully acknowledges financial support from the Wayne E. Leininger Professorship at Virginia Tech. We appreciate Giuliano Buzoianu, Sydney Carter, Debbie Ramos, and Martin Schmidt for their excellent research assistance. Johnson is currently serving as the SEC Academic Fellow in the Office of the Chief Accountant. The views expressed by Johnson and his co-authors are their own and do not necessarily represent those of the Commission or any of the SEC staff.
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Appendices
Appendix 1. S-4 comment letter excerpts
These S-4 comment letter excerpts are presented as examples only. This full letter included 47 total comments, including those related to goodwill, pro forma financial statements, and purchase price allocation issues, among other issues. See the full S-4 comment letter dated May 8, 2015, related to the merger of H.J. Heinz Holding Corporation and Kraft Foods Group Inc. at https://www.sec.gov/Archives/edgar/data/1637459/000000000015025505/filename1.pdf.
Registration Statement on Form S-4
2.1 Unaudited Pro Forma Condensed Combined Financial Statements, page 109
27. You state that for “purposes of the unaudited pro forma condensed combined financial statements, Heinz assumed that the carrying value of Kraft’s property, plant and equipment approximated its fair value.” Unless you have additional information to consider that you believe would support an alternate view, please revise your presentation to include adjustments necessary to allocate the estimated purchase price to all net assets acquired in order to comply with Article 11 of Regulation S-X.
2.1.1 Unaudited Pro Forma Condensed Combined Balance Sheet, page 111
28. Please expand your footnote disclosures to clearly identify the underlying amounts related to your pro forma adjustments to cash and cash equivalents, common stock and additional paid-in capital. We note these amounts are discussed within the footnotes identified in the note reference column. However, the footnote descriptions do not provide sufficient information for an investor to recalculate these adjustment amounts.
2.1.2 Note 5. Unaudited Pro Forma Condensed Combined Balance Sheet Adjustments, page 116
29. The guidance of ASC 805–30–30-2 addresses certain business combinations when the acquisition-date fair value of the acquiree’s equity interests may be more reliably measurable than the acquisition-date fair value of the acquirer’s equity interests. In pro forma adjustment 5(b) and as disclosed on page 110, we note you have used the closing share price of Kraft to calculate the preliminary estimate of fair value of common shares issued in order to arrive at the fair value of total consideration transferred, detailed in pro forma adjustment 5(a). We also note that Heinz will use $10 billion in proceeds from the issuance of shares to the Sponsors to fund a special cash dividend of $16.50 per outstanding share of Kraft common stock. You have stated that Kraft’s closing share price of $88.38 on April 8, 2015 “reflects the pre-dividend share amount which inherently includes the $16.50 special cash dividend to be paid on each outstanding share of Kraft common stock upon the consummation of the merger, estimated in this pro forma condensed combined financial information to be $9.8 billion.” Please expand your disclosure to explain why management believes the dividend is inherently included in the closing stock price and should not be separately accounted for in the calculation of fair value of total consideration transferred. In your response, please also address how this statement is supported by the guidance of ASC 805–30–30-1 and 30–2.
30. We note the adjustments to record the fair value of trademarks and other intangible assets represent a significant portion of the purchase price allocation and overall, are a material amount related to the pro forma financial statements reflecting the business combination of Kraft and Heinz. Considering their significance, with regard to pro forma adjustment 5(e), please revise your pro forma footnote disclosure to separately disclose each significant class of intangible asset by fair value and useful life, as applicable.
31. On a similar matter, you have disclosed that an income approach is “primarily” used to determine the estimated fair values of these intangible assets. In connection with your response to our comment above, please provide further disclosure of the different methods used to evaluate each significant class of intangible asset. If multiple methods are used to evaluate fair value, please include sufficient information to enable a reader to understand how each of the methods used differ, the assumed benefits of a valuation prepared under each method and why management has selected these methods as the most meaningful. Your enhanced disclosure should address the weighting of each of the methods used, including the basis for that weighting. Please also expand your disclosure of the significant assumptions used in the development of your valuations to address the uncertainty associated with these assumptions as well as any significant differences in those assumptions used when compared to Kraft’s prior year performance (i.e., a change in expected net revenues, cost of sales or marketing costs that reflect a significant difference from the revenues earned or costs incurred in the prior year).
32. Pro forma adjustment 5(i) includes a statement that the pro forma financial statements “do not include the impact of such changes on Heinz’s existing deferred tax assets, as this analysis has not been completed.” Please clarify whether your pro forma presentation is in compliance with Article 11 of Regulation S-X or otherwise advise as to the meaning of this statement.
2.1.3 Goodwill and Indefinite-Lived Intangibles, page 164
38. While we note that you recognized a $222 million total impairment charge for intangible assets during 2014, the remaining carrying amount of those assets continues to be significant to your total assets. In addition, you have stated: “there is not a significant excess of fair value over the carrying values as of December 28, 2014” because indefinite-lived intangibles were adjusted to their fair values in connection with the 2013 Merger and due to the recent partial impairments. Accordingly, please enhance your disclosure to more fully describe the risk of future impairment to the remaining indefinite-lived intangible assets and goodwill. For instance, describe how you arrive at estimates of future cash flows and how the key assumptions are determined. Discuss the degree of uncertainty associated with the key assumptions and describe potential events or changes in circumstances that could reasonably be expected to negatively affect the key assumptions. Please include expanded, quantified disclosure providing investors with more insight into the assumptions used in your assessment, including the following disclosures where material:
-
how the assumptions compare to recent operating performance,
-
the basis for any assumptions that differ significantly from recent operating performance, including net sales trend and growth rate and operating margin,
-
a discussion of management’s assessment of the sensitivity of the results of your impairment assessment to the assumptions, and
-
the potential impact on future operations.
Refer to Section 501.14 of the Codification of Financial Reporting Policies. See Section 501.02 of the Codification of Financial Reporting Policies that requires disclosure of material uncertainties, including the recoverability of assets.
Appendix 2. Variable definitions
Acq_CL t-1 | An indicator variable that equals 1 if the acquirer received a 10-K or 10-Q comment letter in the year before the M&A announcement and 0 otherwise. |
Acq_GWImpairment t-1 | An indicator variable that equals 1 if the acquirer reports a goodwill impairment (GDWLIP) in the year before the M&A announcement and 0 otherwise. |
Acq_Lev | Acquirer’s pre-M&A leverage. Measured as the sum of long-term and short-term debt scaled by total assets at the fiscal quarter-end before the M&A completion. |
Acq_MTB | Acquirer’s pre-M&A market-to-book ratio. Measured as the ratio of the acquirer’s market value of equity to the book value of equity at the fiscal year-end before the M&A announcement. |
Acq_NCL t-1 | The natural logarithm of one plus the number of 10-K comment letters received by the acquirer in the year before the M&A announcement. |
Acq_NMW t-1 | The natural logarithm of one plus average number of material weaknesses reported by the acquirer in the year before the M&A announcement. |
Acq_NRestate t-1 | The natural logarithm of one plus the number of restatements filed by the acquirer in the year before the M&A announcement. |
Acq_NSegment | The natural logarithm of one plus the number of the acquirer’s business segments at the fiscal year-end before the M&A announcement. |
Acq_Restate t-1 | An indicator variable that equals 1 if the acquirer files a restatement in the year (365 days) before the M&A is announced and 0 otherwise. |
Acq_ROA | Acquirer’s return on assets for the fiscal year before the M&A announcement year, measured as current income before extraordinary items, scaled by the beginning of the period total assets. |
Acq_Size | Acquirer size. Measured as the natural logarithm of the acquirer’s market value of equity (in millions) 30 days before the M&A announcement. |
Anti_Trust | An indicator variable that equals 1 if the S-4 M&A deal also has an antitrust investigation by the Department of Justice or Federal Trade Commission and 0 otherwise (Cahan 1992). |
Big_Bath | An indicator variable that equals 1 if management of the combined firm in year after M&A completion is likely to pursue big-bath accounting (net income in the year after M&A completion is negative and the firm experiences a negative change in income that is below the median among those firms with a negative change in net income) and 0 otherwise (Glaum et al. 2018). |
CL | An indicator variable that equals 1 if a firm received a comment letter during the S-4 filing review process and 0 otherwise. |
Completion_Rate | The proportion of completed S-4 M&A deals to total S-4 M&A deals. |
Diffcountry | An indicator variable that equals 1 if the acquirer and the target are registered in two different countries and 0 otherwise. |
Diffind | An indicator variable that equals 1 if the acquirer and the target have a different two-digit SIC industry classification code and 0 otherwise. |
Duration | The number of days between the M&A announcement and completion dates. |
Exchange_Offer_CL | An indicator variable that equals 1 if an exchange offer filed on Form S-4 received a comment letter and 0 otherwise. |
GDP_Disperse | Average dispersion for the quarter-over-quarter nominal GDP growth rate forecasts for the next four quarters measured at the end of the first quarter after the M&A is completed. GDP forecast dispersion data are from the Survey of Professional Forecasters from the Federal Reserve Bank of Philadelphia. |
GDP_Growth | GDP growth rate (inflation-adjusted) measured at the end of the first quarter after the M&A is completed. GDP growth rate data are from the U.S. Department of Commerce BEA (Bureau of Economic Analysis) database. |
GW t + 1 | An indicator variable that equals 1 if the firm reports goodwill (GDWL) greater than 0 in the first fiscal year after the M&A completion and 0 otherwise. |
GWImpairment t + 1 | An indicator variable that equals 1 if the combined firm reports a goodwill impairment (GDWLIP) within the year (365 days) after the M&A is completed and 0 otherwise. |
GWImpairment t + 2 | An indicator variable that equals 1 if the combined firm reports a goodwill impairment (GDWLIP) within the two years (730 days) after the M&A is completed and 0 otherwise. |
Hi_Wc | An indicator variable that equals 1 if a firm receives a comment letter and average word count of the SEC comment letters is in the top quartile in our sample and 0 otherwise. |
Lo_Wc | An indicator variable that equals 1 if a firm receives a comment letter and average word count of the SEC comment letters is below the top quartile in our sample and 0 otherwise. |
MGWImpairment t + 1 | The magnitude of goodwill impairment reported by the combined firm (GDWLIP) within the year (365 days) after the M&A is completed, scaled by total assets. |
Mulbid | An indicator variable that equals 1 if the number of bidders for the target, reported by SDC is more than one and 0 otherwise. |
N_MNA | An indicator variable that equals 1 if a firm receives a comment letter, but none of the topics relating to M&A issues are referenced 0 otherwise. |
NRestate t + 1 | The natural logarithm of one plus the number of restatements filed by the combined firm within the year (365 days) after the M&A is completed. |
Num_S4A | The natural logarithm of one plus the number of S-4 amendments filed by the company between the initial S-4 filing and M&A completion. |
Pct_Stock | Percentage of stock payment by the acquirer firm. |
Rel_Size | Ratio of the transaction value to the acquirer market value 60 days before the M&A announcement. |
Restate t + 1 | An indicator variable that equals 1 if the combined firm files a restatement within the year (365 days) after the M&A is completed and 0 otherwise. |
Restate t + 2 | An indicator variable that equals 1 if the combined firm files a restatement within two years (730 days) after the M&A is completed and 0 otherwise. |
Restate_FailureAccRule t + 1 | An indicator variable that equals 1 if the combined firm files a restatement within the year (365 days) after the M&A is completed and the topic of the restatement includes accounting rule (GAAP/FASB) application failure and 0 otherwise. |
Restate_MNA t + 1 | An indicator variable that equals 1 if the combined firm files a restatement within the year (365 days) after the M&A is completed and the topic of the restatement relates to the M&A and 0 otherwise. |
S4A | An indicator variable that equals 1 if the firm files an S-4 amendment, and 0 otherwise between the initial S-4 filing and M&A completion. |
Tender | An indicator variable that equals 1 if the deal is categorized as a tender offer in SDC and 0 otherwise. |
Tgt_CL t-1 | An indicator variable that equals 1 if the target firm received a 10-K comment letter in the year (365 days) before the M&A announcement, and 0 otherwise. |
Tgt_GWImpairment t-1 | An indicator variable that equals 1 if the target firm reports a goodwill impairment (GDWLIP) within the year (365 days) before the M&A announcement and 0 otherwise. |
Tgt_Lev | Target’s pre-M&A leverage. Measured as the sum of long-term and short-term debt scaled by total assets at the fiscal quarter-end before the M&A completion. |
Tgt_MTB | Target’s pre-M&A market-to-book ratio. Measured as the ratio of the target’s market value of equity to the book value of equity at the fiscal year-end before the M&A announcement. |
Tgt_NCL t-1 | The natural logarithm of one plus the number of 10-K comment letters received by the target firm within the year (365 days) before the M&A announcement. |
Tgt_NMW t-1 | The natural logarithm of one plus the average number of material weaknesses reported by the target firm within the year (365 days) before the M&A announcement. |
Tgt_NRestate t-1 | The natural logarithm of one plus the number of restatements filed by the target firm within the year (365 days) before the M&A announcement. |
Tgt_NSegment | The natural logarithm of one plus the number of the target firm’s business segments at the fiscal year-end before the M&A announcement. |
Tgt_ROA | Target’s return on assets for the fiscal year before the announcement year, measured as current income before extraordinary items, scaled by the beginning of the period total assets. |
Tgt_Restate t-1 | An indicator variable that equals 1 if the target firm files a restatement within the year (365 days) before the M&A announcement and 0 otherwise. |
Tgt_Size | Target size. Measured as the natural logarithm of the target’s market value of equity (in millions) 30 days before the M&A announcement. |
VIX | The average daily value of the CBOE Volatility Index (VIX) from the OptionMetrics standardized options dataset during the year (365 days) after the M&A is completed. |
Y_MNA | An indicator variable that equals 1 if a firm receives a comment letter with at least one topic relating to M&A issues (i.e., Audit Analytics taxonomy codes 177 - Acquisitions, mergers and business combinations, 208 - Intangible assets and goodwill, or 209 - Pro forma financial information reporting issues) are referenced and 0 otherwise. |
∆Audit_Fees | Change in audit fees calculated as the acquirer’s post-M&A audit fees less the acquirer’s pre-M&A audit fees scaled by the acquirer’s pre-M&A audit fees. |
∆GWA | An indicator variable that equals 1 if the firm revises its goodwill allocation during the S-4 filing review process and 0 otherwise. Neg_∆GWA is an indicator for a negative (downwards) revision. |
∆PP | An indicator variable that equals 1 if the firm revises its purchase price during the S-4 filing review process and 0 otherwise. Neg_∆PP is an indicator for a negative (downwards) revision. |
∆Pro_Forma | An indicator variable that equals 1 if the firm revises its pro forma financial statements during the S-4 filing review process and 0 otherwise. |
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Johnson, B.A., Lisic, L.L., Moon, J.S. et al. SEC comment letters on form S-4 and M&A accounting quality. Rev Account Stud 28, 862–909 (2023). https://doi.org/10.1007/s11142-021-09659-9
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DOI: https://doi.org/10.1007/s11142-021-09659-9