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Non-GAAP Reporting and Debt Market Outcomes: Evidence from Regulation G

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Schmalenbach Business Review Aims and scope

Abstract

We exploit the introduction of Regulation G (RegG) by the U.S. Securities and Exchange Commission (SEC) in 2003 to study the association between non-GAAP earnings disclosure and debt market outcomes. Specifically, we focus on a subset of 199 S&P 500 firms to analyse the association between non-GAAP earnings disclosure and long-term issuer credit ratings as well as bond spreads before and after the regulatory intervention. We find that post-RegG, correlation between non-GAAP earnings disclosure and bond spreads changes from positive to negative but do not document any change in its correlation with respect to credit ratings. Our study provides first evidence that post-RegG, bond investors, but not rating agencies, seem to view non-GAAP earnings disclosure favourably as part of their credit risk assessment. In practical terms, our results document a specific benefit of RegG and may inform the SEC that its goal of more accurate security pricing extends to the bond markets, which is an under-researched area in the context of non-GAAP regulation.

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Notes

  1. While RegG applies to all different kinds of non-GAAP measures, we focus only on non-GAAP earnings as a specific subset of the non-GAAP universe (refer to Sect. 2 for further discussions).

  2. Specifically, firms’ choices relate to: (a) whether or not to disclose non-GAAP earnings in a given quarter; (b) whether to start or stop non-GAAP reporting after the adoption of RegG; and, finally (c) how to report them (i. e., the choice among a plethora of different non-GAAP reporting attributes).

  3. In general, furnished information is subject to less strict requirements than filed information (see SEC 2002a).

  4. By contrast, information filed with the SEC (i. e., not published in press releases) is subject to further restrictions. For instance, Item 10 contains additional requirements on the emphasis with which non-GAAP earnings are presented as well as how they are labelled. Similarly, Item 12 of Form 8‑K augments the requirements of RegG to the extent that if a furnished press release happens to contain a non-GAAP measure, management needs to articulate how this measure is useful to investors and—if applicable—disclose how it uses the respective measure for internal purposes. Taken together, it could be that the stricter requirements for filed and furnished information also impact firms’ disclosure choices via press releases but there is no explicit regulatory reasoning for it; i. e., RegG defines the boundaries for non-GAAP reporting in press releases.

  5. The C&DIs are provided in a question-and-answer format and cover a whole range of issues in relation to the regulatory framework applicable to non-GAAP financial measures. Examples include the clarification of what exactly constitutes a misleading non-GAAP measure, and to which GAAP measure a given non-GAAP measure should be reconciled to.

  6. Beyond the increased litigation costs discussed here, other potential costs of non-GAAP disclosure might be of proprietary nature. For instance, Isidro and Marques (2016) argue that reporting strong non-GAAP profitability is constrained by the fact that it might attract competitors to enter the market or overproduce, thereby ultimately competing away profits. As for the benefits, there is a broad literature stream on the link between voluntary disclosure and cost of capital (e. g., Botosan 1997, 2006; Lambert et al. 2007, 2012; Barth et al. 2013), which we draw on here by associating non-GAAP earnings disclosure with bond spreads and credit ratings as proxies for the cost of debt.

  7. Under the assumption that special items are uninformative to investors, this amounts to a reduction in the willingness to disclose non-GAAP earnings when they are informative.

  8. Note that Continuers report non-GAAP information during both pre-RegG and post-RegG periods, but post-RegG, they may still decide whether to disclose non-GAAP figures or not per each quarter.

  9. This approach ensures that our results are not confounded, e. g., by more creditworthy firms entering the S&P 500 after the enactment of RegG. We acknowledge that it may introduce survivorship bias into our analysis though.

  10. We retain only the most recent analyst forecasts from IBES. In cases where IBES shows two equally recent forecasts, we select the one with higher analyst coverage.

  11. For some firms, Compustat and IBES tickers did not match. In these cases, we manually searched IBES via firm name and collected the corresponding IBES ticker. In some rare cases where more than one IBES ticker was available, all corresponding observations were deleted as a precautionary measure.

  12. Other “potentially cleaner” proxies for the cost of debt would be offering yields or credit default swap (CDS) spreads. For both proxies, however, we do not have sufficient data since the CDS market was still in its infancy during our sample period. Until 2004, CDS represented only a minor share of the global derivatives market (Bank for International Settlements (BIS) 2016) and data for academic research was typically obtained from private sources (e. g. Norden and Weber 2004).

  13. Specifically, we select all bonds that have an offering date between January 1950, which is the earliest possible, and December 2005 to ensure that we take into account all bonds outstanding during our sample period.

  14. For illustration of Excel’s Yield function, refer to Bodie et al. (2011, p. 480). Note that by calculating yield to maturity, we assume that bonds are not being called prior to maturity.

  15. We drop observations with negative spread, which mostly result from spikes in the risk-free Treasury rate in the third and fourth quarters of 2000.

  16. We realise that our spreads are slightly lower than the ones reported by Barth et al. (2012), albeit average ratings are similar, and the sample period partly overlaps. We find that this is mainly attributable to the fact that we match annualised yield to maturity with annualised risk-free rates, while Barth et al. (2012) deduct a three-month risk-free rate from an annualised yield to maturity. When we discount our annual rate to proxy for the three-month rate and use this proxy instead of our annualised three-month rate, our average spread across the whole sample period increases to 4.5%. This comes relatively close to the 5.16% by Barth et al. (2012). Using this approach, our results presented in Table 4 remain significant but only for Continuers.

  17. Black et al. (2017) delete all firms that report non-GAAP earnings only once in either the pre-RegG or post-RegG time-period. This would greatly reduce our sample size. Instead, we keep firms that report non-GAAP earnings only once. However, in order for firms to be counted as a non-GAAP “reporter” for the respective sub-period, we require them to report non-GAAP earnings at least twice.

  18. Note that Non-Reporters did engage in non-GAAP reporting in some quarters. This is because we define firms as Non-Reporters for each time-period if they report non-GAAP earnings once or less.

  19. Our cut-off point of 2.5 relates to the argument by Zhang and Zheng (2011) that the most pronounced difference in reconciliation quality is between reconciliation scores of 2 and below vs. reconciliation scores of 3 or 4.

  20. In addition, there are 38 firms, which had good reconciliation quality in both time-periods and 6 firms whose reconciliation quality worsened from the pre-RegG to the post-RegG time-period.

  21. To mitigate the effect of potential outliers, we winsorise Rating and Spread as well as all other continuous variables (relevant for the supplementary analyses in Sect. 6) at the 1st and 99th percentile.

  22. For instance, Jorion et al. (2005) argue that rating agencies have access to internal information such as budgets or forecasts, as well as advance notification of major corporate events.

  23. In particular, for the entire sample, the negative sign on bond spreads during the post-RegG time-period turns insignificant whereas for Continuers it remains significant at the 1%-level.

  24. Specifically, the IMR serves as an instrumental variable that mitigates endogeneity associated with the subset of variables that jointly determine non-GAAP disclosure and credit ratings or bond spreads, respectively.

  25. Unlike Isidro and Marques (2015), we do not include a variable proxying for the ownership of inside investors because we do not have access to the data. Further, our specification does not include dummies on U.S. stock market listing as well as the use of IFRS, which we do not need due to our U.S. setting. In addition, we do not include a proxy for institutional ownership due to severe loss of observations. However, in unreported robustness checks, we include institutional ownership and find that NonGAAP_Post_RegG always remains negative and significant at the 1% level.

  26. Isidro and Marques (2015) use intangible assets because these are known to be associated with increased non-GAAP disclosure (see also Lougee and Marquardt 2004). However, we use tangibility instead and expect an opposite sign for the variable, since the coverage for net PPE is much larger than for intangible assets in the Compustat database.

  27. Again, we caution that, although the coefficient resembles the difference-in-difference estimator, the described self-selection issues implicit in our setting impede any causal identification. Hence, results should be interpreted with caution.

  28. Note that only the 3398 observations displayed for the contemporaneous association with credit ratings in column 2 reconcile with the number of observations shown in Table 5; i. e., 2237 (Continuers) + 1161 (Non-Reporters). The reasons are that: (a) in the lead specifications, we always lose more than the number of first quarter observations because we do not have observations for every firm-quarter; and, (b) not all 3398 observations pertaining to Continuers and Non-Reporters have data on bond spreads.

  29. For instance, in another context, Barth et al. (2012) also show that rating agencies process accounting information differently than bond investors do. Specifically, they document that rating agencies distinguish between credit risk from the retained and non-retained portions of asset securitisations while the bond market does not.

  30. As for (c), the interaction term of NonGAAP_Post_RegG remains negative and highly significant but the combined effect of NonGAAP and NonGAAP_Post_RegG weakens to significance at the 10% level for the lead specification and to insignificance with respect to the contemporaneous association.

  31. Additionally, we also replace our year-fixed effects with quarter-fixed effects and our results change as follows: when applying the standard two-tailed significance tests, the coefficient on NonGAAP_Post_RegG only remains significant at the 10% level in the contemporaneous association whereas it becomes insignificant in the lead-specification. Yet, given our directional hypothesis and when using one-tail tests, the coefficient is significantly negative at the 10% and 5%-levels for the lead- and contemporaneous specifications, respectively.

  32. A common example of an adjustment that would not qualify as non-GAAP reporting in our paper is adjusted sales (growth rate). For instance, in Q2/1999, Avery Dennison adjusts its sales for currency effects but does not present an adjusted net income or EPS figure. Hence, it does not qualify as a non-GAAP earnings disclosure for the purpose of our paper.

  33. While Curtis et al. (2013) also require a prominent presentation, they apply slightly stricter rules since they only count firms as non-GAAP reporters if non-GAAP measures are stated within the first ten lines of any press release. An analysis of our sample shows that if firms state non-GAAP earnings on the first page of a press release, they also typically do this within the first ten lines.

References

  • Ahmed, A.S., E. Kilic, and G.J. Lobo. 2011. Effects of SFAS 133 on the risk relevance of accounting measures of banks’ derivative exposures. The Accounting Review 86(3):769–804.

    Article  Google Scholar 

  • Alissa, W., S.B. Bonsall, K. Koharki, and M.W. Penn. 2013. Firms’ use of accounting discretion to influence their credit ratings. Journal of Accounting and Economics 55(2):129–147.

    Article  Google Scholar 

  • Allee, K.D., N. Bhattacharya, E.L. Black, and T.E. Christensen. 2007. Pro forma disclosure and investor sophistication: External validation of experimental evidence using archival data. Accounting, Organizations and Society 32(3):201–222.

    Article  Google Scholar 

  • Andrade, S.C., G. Bernile, and F.M. Hood III. 2014. SOX, corporate transparency, and the cost of debt. Journal of Banking & Finance 38:145–165.

    Article  Google Scholar 

  • Ashbaugh-Skaife, H., D.W. Collins, and R. LaFond. 2006. The effects of corporate governance on firms’ credit ratings. Journal of Accounting and Economics 42(1):203–243.

    Article  Google Scholar 

  • Bank for International Settlements (BIS). 2016. Statistical release: OTC derivatives statistics at end-June 2016. https://www.bis.org/publ/otc_hy1611.pdf.

    Google Scholar 

  • Bao, J., J. Pan, and J. Wang. 2011. The illiquidity of corporate bonds. The Journal of Finance 66(3):911–946.

    Article  Google Scholar 

  • Barth, M.E., Y. Konchitchki, and W.R. Landsman. 2013. Cost of capital and earnings transparency. Journal of Accounting and Economics 55(2–3):206–224.

    Article  Google Scholar 

  • Barth, M.E., G. Ormazabal, and D.J. Taylor. 2012. Asset securitizations and credit risk. The Accounting Review 87(2):423–448.

    Article  Google Scholar 

  • Baumker, M., P. Biggs, S.E. McVay, and J. Pierce. 2013. The disclosure of non-GAAP earnings following RegG: An analysis of transitory gains. Accounting Horizons 28(1):77–92.

    Article  Google Scholar 

  • Bhattacharya, N., E.L. Black, T.E. Christensen, and C.R. Larson. 2003. Assessing the relative informativeness and permanence of pro forma earnings and GAAP operating earnings. Journal of Accounting and Economics 36(1–3):285–319.

    Article  Google Scholar 

  • Bhattacharya, N., E.L. Black, T.E. Christensen, and R.D. Mergenthaler. 2007. Who trades on pro forma earnings information? The Accounting Review 82(3):581–619.

    Article  Google Scholar 

  • Black, D.E., E.L. Black, T.E. Christensen, and W.G. Heninger. 2012. Has the regulation of pro forma reporting in the US changed investors’ perceptions of pro forma earnings disclosures? Journal of Business Finance & Accounting 39(7‐8):876–904.

    Article  Google Scholar 

  • Black, D.E., T.E. Christensen, J.T. Ciesielski, and B.C. Whipple. 2018. Non‐GAAP reporting: Evidence from academia and current practice. Journal of Business Finance & Accounting 45(3–4):259–294.

    Article  Google Scholar 

  • Black, E.L., T.E. Christensen, P.V. Kiosse, and T.D. Steffen. 2017. Has the regulation of non-GAAP disclosures influenced managers’ use of aggressive earnings exclusions? Journal of Accounting, Auditing & Finance 32(2):209–240.

    Article  Google Scholar 

  • Bodie, Z., A. Kane, and A. Marcus. 2011. Investments and portfolio management: Global edition, 9th edn., Singapore: McGraw-Hill.

    Google Scholar 

  • Botosan, C.A. 1997. Disclosure level and the cost of equity capital. The Accounting Review 72(3):323–350.

    Google Scholar 

  • Botosan, C.A. 2006. Disclosure and the cost of capital: What do we know? Accounting and Business Research 36(Sup1):31–40.

    Article  Google Scholar 

  • Bozanic, Z., and P. Kraft. 2017. Qualitative corporate disclosure and credit analysts’ soft rating adjustments. https://ssrn.com/abstract=2962491. Working Paper.

    Book  Google Scholar 

  • Brown, L.D., and K. Sivakumar. 2003. Comparing the value relevance of two operating income measures. Review of Accounting Studies 8(4):561–572.

    Article  Google Scholar 

  • Brown, N.C., T.E. Christensen, W.B. Elliott, and R.D. Mergenthaler. 2012. Investor sentiment and pro forma earnings disclosures. Journal of Accounting Research 50(1):1–40.

    Article  Google Scholar 

  • Cascino, S., M. Clatworthy, B. García Osma, J. Gassen, S. Imam, and T. Jeanjean. 2014. Who uses financial reports and for what purpose? Evidence from capital providers. Accounting in Europe 11(2):185–209.

    Article  Google Scholar 

  • Cazier, R.A., T.E. Christensen, K.J. Merkley, and J.S. Treu. 2017. Litigation risk and non-GAAP reporting. https://ssrn.com/abstract=2928260. Working Paper.

    Book  Google Scholar 

  • Christensen, T.E., M.S. Drake, and J.R. Thornock. 2014. Optimistic reporting and pessimistic investing: Do pro forma earnings disclosures attract short sellers? Contemporary Accounting Research 31(1):67–102.

    Article  Google Scholar 

  • Core, J.E. 2001. A review of the empirical disclosure literature: Discussion. Journal of Accounting and Economics 31(1–3):441–456.

    Article  Google Scholar 

  • Curtis, A.B., S.E. McVay, and B.C. Whipple. 2013. The disclosure of non-GAAP earnings information in the presence of transitory gains. The Accounting Review 89(3):933–958.

    Article  Google Scholar 

  • Dhaliwal, D.S., C.A. Gleason, S. Heitzman, and K.D. Melendrez. 2008. Auditor fees and cost of debt. Journal of Accounting, Auditing & Finance 23(1):1–22.

    Article  Google Scholar 

  • Dyreng, S.D., R. Vashishtha, and J. Weber. 2017. Direct evidence on the informational properties of earnings in loan contracts. Journal of Accounting Research 55(2):371–406.

    Article  Google Scholar 

  • Elliott, W.B. 2006. Are investors influenced by pro forma emphasis and reconciliations in earnings announcements? The Accounting Review 81(1):113–133.

    Article  Google Scholar 

  • Entwistle, G.M., G.D. Feltham, and C. Mbagwu. 2006. Financial reporting regulation and the reporting of pro forma earnings. Accounting Horizons 20(1):39–55.

    Article  Google Scholar 

  • Florou, A., and U. Kosi. 2015. Does mandatory IFRS adoption facilitate debt financing? Review of Accounting Studies 20(4):1407–1456.

    Article  Google Scholar 

  • Franco, F., O. Urcan, and F.P. Vasvari. 2016. Corporate diversification and the cost of debt: The role of segment disclosures. Accounting Review 91(4):1139–1165.

    Article  Google Scholar 

  • Guest, N.M., S.P. Kothari, and R. Pozen. 2018. High non-GAAP earnings predict abnormally high CEO pay. https://ssrn.com/abstract=3030953. Working Paper.

    Google Scholar 

  • Heckman, J. 1979. Sample selection bias as a specification error. Econometrica 47(1):153–161.

    Google Scholar 

  • Heflin, F., and C. Hsu. 2008. The impact of the SEC’s regulation of non-GAAP disclosures. Journal of Accounting and Economics 46(2):349–365.

    Article  Google Scholar 

  • Isidro, H., and A. Marques. 2015. The role of institutional and economic factors in the strategic use of non-GAAP disclosures to beat earnings benchmarks. European Accounting Review 24(1):95–128.

    Article  Google Scholar 

  • Isidro, H., and A. Marques. 2016. Signalling financial performance with alternative performance measures. http://www.business.uwa.edu.au/__data/assets/pdf_file/0003/2958330/Ana-Marques.pdf. Working Paper.

    Google Scholar 

  • Jorion, P., Z. Liu, and C. Shi. 2005. Informational effects of regulation FD: Evidence from rating agencies. Journal of Financial Economics 76(2):309–330.

    Article  Google Scholar 

  • Jung, B., N. Soderstrom, and Y.S. Yang. 2013. Earnings smoothing activities of firms to manage credit ratings. Contemporary Accounting Research 30(2):645–676.

    Article  Google Scholar 

  • Kolev, K., C.A. Marquardt, and S.E. McVay. 2008. SEC scrutiny and the evolution of non-GAAP reporting. The Accounting Review 83(1):157–184.

    Article  Google Scholar 

  • Lambert, R., C. Leuz, and R.E. Verrecchia. 2007. Accounting information, disclosure, and the cost of capital. Journal of Accounting Research 45(2):385–420.

    Article  Google Scholar 

  • Lambert, R., C. Leuz, and R.E. Verrecchia. 2012. Information asymmetry, information precision, and the cost of capital. Review of Finance 16(1):1–29.

    Article  Google Scholar 

  • Leone, M. 2010. What’s on the SEC’s radar? http://ww2.cfo.com/accounting-tax/2010/09/whats-on-the-secs-radar/.

    Google Scholar 

  • Li, N. 2010. Negotiated measurement rules in debt contracts. Journal of Accounting Research 48(5):1103–1144.

    Article  Google Scholar 

  • Longstaff, F.A., S. Mithal, and E. Neis. 2005. Corporate yield spreads: Default risk or liquidity? New evidence from the credit default swap market. The Journal of Finance 60(5):2213–2253.

    Article  Google Scholar 

  • Lougee, B.A., and C.A. Marquardt. 2004. Earnings informativeness and strategic disclosure: An empirical examination of “pro forma” earnings. The Accounting Review 79(3):769–795.

    Article  Google Scholar 

  • Malone, L., A. Tarca, and M. Wee. 2016. IFRS non-GAAP earnings disclosures and fair value measurement. Accounting & Finance 56(1):59–97.

    Article  Google Scholar 

  • Marques, A. 2006. SEC interventions and the frequency and usefulness of non-GAAP financial measures. Review of Accounting Studies 11(4):549–574.

    Article  Google Scholar 

  • Mercer, M. 2004. How do investors assess the credibility of management disclosures? Accounting Horizons 18(3):185–196.

    Article  Google Scholar 

  • Moody’s. 2017. Credit opinion: Siemens Aktiengesellschaft: Update to credit analysis. https://www.moodys.com/credit-ratings/Siemens-Aktiengesellschaft-credit-rating-676500.

    Google Scholar 

  • Norden, L., and M. Weber. 2004. Informational efficiency of credit default swap and stock markets: The impact of credit rating announcements. Journal of Banking & Finance 28(11):2813–2843.

    Article  Google Scholar 

  • Rainsbury, E.A. 2017. The impact of the FMA guidelines on non‐GAAP earnings disclosures. Australian Accounting Review 27(4):480–493.

    Article  Google Scholar 

  • S&P Global Ratings. 2013a. Corporate methodology. https://www.standardandpoors.com/en_US/web/guest/article/-/view/sourceId/8314109.

    Google Scholar 

  • S&P Global Ratings. 2013b. Corporate methodology: Ratios and adjustments. https://www.standardandpoors.com/en_US/web/guest/article/-/view/sourceId/8330212.

    Google Scholar 

  • Securities and Exchange Commission (SEC). 2001. Cautionary advice regarding the use of ‘pro-forma’ financial information in earnings releases. https://www.sec.gov/rules/other/33-8039.htm. Securities and Exchange Commission Release Nos. 33-8039, 34-45124, FR-59.

    Google Scholar 

  • Securities and Exchange Commission (SEC). 2002a. Final rule: Conditions for use of non-GAAP financial measures. https://www.sec.gov/rules/final/33-8176.htm.

    Google Scholar 

  • Securities and Exchange Commission (SEC). 2002b. SEC brings first pro forma financial reporting case—Trump hotels charged with issuing misleading earnings release. https://www.sec.gov/news/headlines/trumphotels.htm.

    Google Scholar 

  • Securities and Exchange Commission (SEC). 2009. SEC charges Safenet, Inc. and two former senior officers in earnings management and options backdating schemes. https://www.sec.gov/litigation/litreleases/2009/lr21290.htm.

    Google Scholar 

  • Sengupta, P. 1998. Corporate disclosure quality and the cost of debt. Accounting Review 73(4):459–474.

    Google Scholar 

  • Shivakumar, L., O. Urcan, F.P. Vasvari, and L. Zhang. 2011. The debt market relevance of management earnings forecasts: Evidence from before and during the credit crisis. Review of Accounting Studies 16(3):464–486.

    Article  Google Scholar 

  • Turner, L.E. 2000. Speech by SEC staff: Remarks to the 39th annual corporate counsel institute. https://www.sec.gov/news/speech/spch418.htm. Northwestern University School of Law, Evanston, Ill.

    Google Scholar 

  • United States District Court for the Northern District of California. 2005. In re Netflix Inc. securities litigation. http://securities.stanford.edu/filings-documents/1031/NFLX04-02/2005422_r06x_04CV2978.pdf. U.S. Dist. Lexis 30992.

    Google Scholar 

  • White, M.J. 2016. Focusing the lens of disclosure to set the path forward on board diversity, non-GAAP, and sustainability. https://www.sec.gov/news/speech/chair-white-icgn-speech.html.

    Google Scholar 

  • Young, S. 2014. The drivers, consequences and policy implications of non-GAAP earnings reporting. Accounting and Business Research 44(4):444–465.

    Article  Google Scholar 

  • Zhang, H., and L. Zheng. 2011. The valuation impact of reconciling pro forma earnings to GAAP earnings. Journal of Accounting and Economics 51(1):186–120.

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge valuable comments by Erv Black, Ted Christensen, Liz Demers, Brigitte Eierle, Peter Fiechter, Andrei Filip, Beatriz García-Osma, Martin Glaum, Martin Jacob, Anette Mikes, Richard Morris, Maximilian Müller, Wolfgang Schultze, Ana Simpson, Steven Young, and workshop participants at the University of Augsburg, the University of St. Gallen, the Doctoral Summer Program in Accounting Research (SPAR) 2016 at WHU in Vallendar, the EAA Annual Congress 2017 in Valencia, the VHB Annual Meeting 2017 in St. Gallen, the International Accounting Symposium 2017 in Madrid, the CARF conference 2017 in Lucerne, the ACA Symposium 2017 in St. Gallen, the IAS Midyear Meeting 2018 in Tampa, the EAA Annual Congress 2018 in Milan, and the AAA Annual Meeting 2018 in Washington D.C.

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Authors and Affiliations

  1. Institute of Accounting, Control and Auditing, University of St.Gallen, Tigerbergstr. 9, 9000, St. Gallen, Switzerland

    Felix Thielemann & Tami Dinh

  2. School of Accounting, UNSW Sydney, Kensington Campus, NSW 2052, Sydney, Australia

    Helen Kang

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  1. Felix Thielemann
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Appendices

Appendix A

1.1 Data Collection on Non-GAAP Reporting (Quality)

Information on non-GAAP reporting is hand-collected from the relevant press-releases available on the LexisNexis database. We focus on press releases since RegG explicitly applies to this type of medium (refer to Sect. 2) and prior studies (e. g., Zhang and Zheng 2011) have also focused on it. We expand the keyword search employed by Zhang and Zheng (2011) and use the following keywords to search LexisNexis’ PR Newswire and Businesswire functions: “pro forma”, “pro-forma”, “proforma”, “adjusted”, “recurring”, “one time” and “one-time”. To narrow down the search to our sample, additional keywords used were “company name” and/or “firm ticker”. Following Zhang and Zheng (2011), we then collect several items relating to non-GAAP reporting. First, we had to determine whether a press release qualifies as non-GAAP reporting for our purpose. We only focus on non-GAAP earnings; i. e., we ignore adjusted sales or any other metrics whose impact might, but is not explicitly, translate into an adjusted net income or EPS figure.Footnote 32

Further, only adjustments or the aggregated adjusted income figure that are either reported in absolute Dollar amounts or on an EPS basis qualify as non-GAAP earnings disclosure. Thus, we count firms as non-GAAP reporters if they do not publish an adjusted income figure but, instead, state the amount of adjustments in absolute Dollar amounts or as an EPS. The rationale behind this approach is that once adjustments are reported on an EPS basis or in absolute Dollar amounts, it is extremely easy for investors to infer total non-GAAP earnings. In addition, adjusted profit figures are only counted as non-GAAP if they are presented with reasonable prominence. We expect this to be the case if the first reference to non-GAAP earnings/adjustments is made on the first page of the respective press releases.Footnote 33 The following statement by Avon in its Q4/2003 press release serves to illustrate our point:

Avon said that earnings per share in the quarter rose 36%, to $1.09 per diluted share, versus $0.80 per diluted share in the fourth quarter of 2002. As previously announced, earnings in the quarter included a benefit of $0.06 per share from a tax audit settlement.

According to our approach, this clearly counts as non-GAAP reporting because investors can easily infer that the adjusted earnings Avon is hinting at must be $1.03 per diluted share, despite the fact that this number is not explicitly presented in the press release. By contrast, in Q1/2002 Avon claims that:

For the first quarter, excluding non-recurring tax-related items in both periods, cash flow was $10 million lower than last year’s performance …

This is not considered non-GAAP reporting by our standards as the adjustments presented refer to cash flows and not earnings, though they might also affect earnings. In addition, this statement was buried on the second page of the press release, as opposed to the first statement, which was prominently presented in the second paragraph on the first page. Finally, following Zhang and Zheng (2011) and Lougee and Marquardt (2004), we ignore press releases if: (a) non-GAAP earnings only relate to retrospective effects of initial public offerings, mergers and acquisitions; (b) they do not pertain to the current quarter, e. g., if a current quarter is compared with a prior quarter in which non-GAAP adjustments were being made; or, (c) they purely reflect a change in accounting method, tax status or capital structure.

Conditional on a firm releasing non-GAAP earnings, we record its relative emphasis to GAAP numbers and use the Zhang and Zheng (2011) methodology to measure reconciliation quality between non-GAAP and GAAP earnings, assigning a reconciliation score that ranges from 0–4, with 4 representing the highest level of quality. The methodology of the reconciliation score is outlined in Table A.1. Further, we collect the number of non-GAAP adjustments firms make and whether the final reported non-GAAP earnings figure meets or beats GAAP earnings (Beat_GAAP) as well as analyst forecasted earnings (Beat_Analyst).

Table A.1 Reconciliation Scores. (According to Zhang and Zheng 2011)
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Appendix B

 

Table B.1 Description of Variables
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Thielemann, F., Dinh, T. & Kang, H. Non-GAAP Reporting and Debt Market Outcomes: Evidence from Regulation G. Schmalenbach Bus Rev 71, 169–203 (2019). https://doi.org/10.1007/s41464-019-00074-x

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