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Review of Accounting Studies

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05-10-2020

Measuring disclosure using 8-K filings

Authors: Jing He, Marlene A. Plumlee

Published in: Review of Accounting Studies | Issue 3/2020

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Abstract

We construct four voluntary and two mandatory disclosure measures for 260,880 firm-quarters from 2005 through 2016 using 8-K data. The first voluntary disclosure measure is the count of 8-Ks, a proxy used in prior studies. The second and third are the count and word count of the 8-K items classified as voluntary (Items 2.02, 7.01, and 8.01) and the associated exhibits. The final voluntary disclosure measure is the count of the voluntary 8-K items and exhibits that include management guidance, conference calls, non-GAAP measures, or investor day disclosures. We document basic properties of these measures, including their cross-sectional and time-series correlations and persistence, and associations with firm-level characteristics. We show that, although the four measures are highly correlated, each captures unique aspects of firms’ disclosures. Based on how the measures are constructed and supported by our findings, we contend that the word-count-based 8-K measure provides a superior proxy for firm-level voluntary disclosure.

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The studies examine links between voluntary disclosure and various constructs, including (1) firm performance (e.g., Kasznik and Lev 1995; Miller 2002; Berger and Hann 2007), (2) the cost of capital and liquidity (e.g., Botosan and Plumlee 2002; Hail and Leuz 2006), (3) investor sentiment (e.g., Bergman and Roychowdhury 2008; Brown et al. 2012), (4) proprietary information costs (e.g., Bamber and Cheon 1998; Verrecchia and Weber 2006), (5) investor clientele (Kalay 2015), (6) index assignment, institutional holdings, and shareholder activism (e.g., Boone and White 2015; Bourveau and Schoenfeld 2017; Schoenfeld 2017). This is, of course, only a partial list.

See the following papers associated with each numeral above. (1) Lang and Lundholm (1993, 1996); Bushee and Noe (2000); and Lundholm and Myers (2002). (2) Miller (2002) and Francis et al. (2008). (3) Bergman and Roychowdhury (2008); Brown et al. (2012); Brown et al. (2004); Tasker (1998); Kalay (2015); Vashishtha (2014); and Kirk and Markov (2016). (4) Leuz and Schrand (2009); Balakrishnan et al. (2014); Guay et al. (2016); Segal and Segal (2016); Schoenfeld (2017); Bourveau et al. (2018); Bao et al. (2019); He et al. (2019); Gleason et al. (2020).

For example, see https://www.sec.gov/news/press-release/2014-248 for SEC enforcement actions against companies for failing to make required 8-K disclosures. Further, prior studies (e.g., Lerman and Livnat 2010; Beyer et al. 2010) document significant market reactions to 8-K filings, suggesting investors view them as information events.

The literature suggests a link between voluntary and mandatory disclosure, based on both theoretical (e.g., Gigler and Hemmer 1998; Friedman et al. 2019) and empirical findings (e.g., Francis et al. 2008; He et al. 2019). Beyer et al. (2010); Heitzman et al. (2010); and others have questioned whether traditional voluntary disclosure measures capture mandatory disclosure. If voluntary disclosure decisions relate to mandatory disclosures, failing to control for the latter could lead to a correlated omitted variable, which would call into question the reliability of the associations inferred from these voluntary disclosure proxies.

The SEC defines a “material” event as one that is expected to influence a reasonable investor’s investment decision.

With respect to the additional voluntary 8-K Items, 7.01 and 8.01, the SEC states the following. For Item 7.01 “Regulation FD Disclosure”: “Unless filed under Item 8.01, disclose under this item only information that the registrant elects to disclose through Form 8-K pursuant to Regulation FD.” For Item 8.01 “Other Events”: “The registrant may, at its option, disclose under this Item 8.01 any events, with respect to which information is not otherwise called for by this form, that the registrant deems of importance to security holders. The registrant may, at its option, file a report under this Item 8.01 disclosing the nonpublic information required to be disclosed by Regulation FD” (emphasis added). This classification is generally consistent with prior work (Lerman and Livnat 2010). Lerman and Livnat consider 2.02 and 7.01 as semi-voluntary, as these items are “triggered by the firm’s voluntary disclosure of material events” (footnote four, p. 755) and Item 8.01 as voluntary. Since our interest is in identifying the nature of firms’ underlying disclosures, we classify both Items 2.02 and 7.01 as voluntary.

We report results using data by calendar quarter, although it also is possible to report using annual (e.g., Bourveau et al. 2018; He et al. 2019) or monthly data (e.g., Ellahie et al. 2019).

See, for example, Bergman and Roychowdhury (2008); Brown et al. (2012); Brown et al. (2004); Tasker (1998); Kalay (2015); Vashishtha (2014); and Kirk and Markov (2016).

Another potential disadvantage of using one of the four specific channels to measure disclosure is the difficulty in determining whether the absence of a disclosure via a given channel is because a firm has not made a disclosure or because the firm is not included in the database. Many studies, particularly those that rely on management guidance, address this concern by limiting the set of firms included in the sample to those that have issued management guidance in a prior period. For example, Bergman and Roychowdhury (2008) limit their sample to “all firm-quarters that follow the initial appearance of the corresponding firm on the First Call CIG database,” and Bao et al. (2019) limit their management guidance sample to “firms that issue at least one management guidance in the past four quarters.” In contrast, our only data requirements are that a firm filed an 8-K with the SEC during the sample period and that Compustat reported total assets and net income.

McMullin et al. (2019) rely on 8-K data to isolate mandatory disclosures. Similar to studies that rely on 8-K data to identify voluntary items, they use 8-K item numbers to identify mandatory items. They isolate mandatory disclosure by excluding 8-K items that managers have more discretion over (e.g., items 2.02, 7.01, and 8.01).

Kasznik and Lev identify 565 firms with large earnings surprises (171 good news and 394 bad news) and collect “all public disclosures made by the sample firms” over the 60 days prior to the earnings releases. Lang and Lundholm (2000) identify 41 firms that issue equity (and a matched set of firms) and collect “all available public disclosures … from 18 months before to 18 months after the registration date of the offering.” Miller identifies 80 firms with sustained earnings increases and hand-collects “all available public disclosures for the 80 firms … using the Dow Jones News Retrieval Service (DJNR).”

Other studies use textual analysis to develop disclosure measures, frequently based on 10-Ks (e.g., Brown and Tucker 2011; Li et al. 2013). We do not include 10-K-based measures, as they are mandatory, annual filings. While 8-Ks also are mandatory, they are triggered by both voluntary and mandatory events. Further, textual analysis measures are subject to researcher judgment when converting text into measures, which introduces imprecision and replication difficulties. See Loughram and McDonald (2015) for a detailed discussion.

For example, as discussed earlier, the SEC requires a firm to file an 8-K when it enters into a material definitive agreement (8-K Item 1.01) or when a director departs (8-K Item 5.02). We classify these items as mandatory, since the SEC requires the reporting of the underlying event. The SEC also requires a firm to file an 8-K when it chooses to disclose information (e.g., when it issues an earnings announcement or management guidance). These items (2.02, 7.01, or 8.01) are classified as voluntary, since the 8-K triggering event is a firm disclosure choice.

Firms could meet the SEC filing requirement related to voluntary disclosures by “disseminating the information through another method that is reasonably designed to provide broad, non-exclusionary distribution of the of the information to the public (17 CFR 243.101 (e))” (emphasis added). Mathis (2019) examines whether firms use 8-K filings to report the disclosure of management guidance, a voluntary disclosure channel included in our study. His findings suggest that firms frequently elect to report management guidance in an 8-K. For example, in Panel B of his Table 1, he finds that between 68% and 79% of his sample of 76,244 management forecasts issued between 2005 and 2015 are reported in 8-Ks. He requires that the 8-K filing date be equal to the management forecast date, which would “artificially decrease the percentage of the observations represented as filed.” Nonetheless, his evidence suggests that not all management guidance will be included in our 8-K-based disclosure measures.

The sample begins in 2005, after the SEC changed 8-Ks and its filing requirements that expanded the covered items. For most items, the filing deadline was also shortened to four business days. The SEC also adopted a “limited safe harbor from liability for failure to file certain of the required Form 8-K reports” and stated: “These amendments are responsive to the ‘real time issuer disclosure’ mandate in Section 409 of the Sarbanes-Oxley Act of 2002. They are intended to provide investors with better and faster disclosure of important corporate events.” (SEC website). Our method could be extended to an earlier period, when all public companies were required to file electronically on EDGAR, with a few exceptions.

When we match the remaining unmatched Exhibit 99s, we are matching 8-Ks with more than three items, one of which is an Item 2.02, 7.01, or 8.01. Since our primary focus is on constructing voluntary disclosure measures based on those item numbers, we do not match Exhibit 99 in 8-Ks with only mandatory items.

Our decision rule to match first with Item 2.02, then Item 8.01, and then Item 7.01 is based on reading the 8-Ks filed by a random sample of 20 firms across the entire sample period and 300 additional 8-Ks that include item numbers 2.02, 7.01, or 8.01. Within those 8-Ks, we find that Item 2.02s are most likely filed with an Exhibit 99, then Item 8.01s, and then Item 7.01s. Of the 54.5% of this sample with two items, one of which is an Item 9.01, 32.7% of the non-9.01 items are Item 2.02, 25.0% of them are Item 8.01, and 14.6% of them are Item 7.01.

The main reasons for this are (1) the text does not mention an exhibit number; (2) the 8-K uses an irregular format for the exhibit such as “exhibit 1, 2, and 3,” rather than “exhibit 1, exhibit 2, exhibit 3”; or (3) instead of referring to an exhibit number, the 8-K refers to a letter such as “exhibit (A).”

Consistent with Bozanic et al. (2018), our objective is to capture a broader set of voluntary disclosures (their “forward-looking statements”) beyond earnings forecasts.

We also perform a keyword search of the voluntary 8-K items and exhibits related to nine additional topics (Appendix 4, Panel A details the topics and the search terms). These results provide preliminary data related to the content of the voluntary items and exhibits, beyond the four disclosure channels discussed above.

For example, if a firm files two 8-Ks in a quarter, one with an Item 7.01 with two exhibits and one with an Item 2.02 with one exhibit, VDisc_Ct would be five. The word count variable would be the number of words in the two items and three exhibits. The two mandatory disclosure measures (MDisc_Ct, MDisc_WC) are constructed similarly, based on the mandatory items and exhibits.

The maximum value of VDisc_Sum for any firm-quarter is the number of voluntary 8-K items within the quarter times four, by construction. Within our sample, the maximum value of VDisc_Sum is 52.

Miller (2002) finds that nearly 80% of the forward-looking statements in his sample are qualitative. We find that about 50% of our management guidance is quantitative, although this varies by the item number where the guidance is reported.

Some firms in our sample issue 8-Ks with only voluntary or only mandatory items during a given calendar quarter. In those cases—when we have nonzero values for VDisc_Ct (MDisc_Ct) and “missing” values for MDisc_Ct (VDisc_Ct)—we set MDisc_Ct (VDisc_Ct) equal to zero. Similarly, during some quarters, firms issue no 8-Ks, although they issue 8-Ks before and after those firm quarters, and we set VDisc_Ct and MDisc_Ct equal to zero as well.

Documenting that VDisc_Sum is zero at the 25th percentile when VDisc_Ct is 2.0 at the 25th percentile means that firms’ measured disclosure using VDisc_Sum or any of the four disclosure channels used in the construction of that measure would be zero, although firms report voluntary items in their 8-Ks.

For example, %Variable in the MgmtGuide_Ct row and Within Item 2.02 columns reports the proportion of all the disclosures of management guidance that are reported with Item 2.02s. These proportions across the voluntary items sum to 100%: 68.7% within Item 2.02, 19.0% within Item 7.01, and 12.3% within Item 8.01. %2.02 in the MgmtGuide_Ct row and Within Item 2.02 columns reports the proportion of 2.02s that include a disclosure of management guidance. The sum of these exceed 100%, as firms frequently report more than one disclosure channel in a given voluntary 8-K item.

In an additional analysis, we performed a keyword search of the three voluntary 8-K items and associated exhibits and collected the frequency with which firms reported nine additional special topics of interest to researchers, academics, and researchers. See Appendix 4 for the detailed discussion of this analysis.

We do not form expectations, as our examination is focused on documenting the properties of the disclosure measures in this settings. Nonetheless, we acknowledge that there are various theoretical studies that lead to signed predictions. For example, a number of studies suggest voluntary disclosure reduces information asymmetry and increases stock liquidity (e.g., Glosten and Milgrom 1985; Amihud and Mendelson 1986; Diamond and Verrecchia 1991; Kim and Verrecchia 1994), which would suggest a negative association between voluntary disclosure and information asymmetry.

In this and in following models, we estimate but do not report the 8K_Ct and VDisc_Sum models that include a control for concurrent mandatory disclosure (MDisc_Ct). Doing so does not change the tenor of our results.

In untabulated analyses, we also employ analyst forecast errors and dispersion in analysts’ forecasts as proxies for information asymmetry (Chen et al. 2015; Schoenfeld 2017). The results of estimating those models (with the standard controls) are substantively similar to those documented using bid-ask spreads. The coefficients on (1) LVDisc_WC and VDisc_Sum are statistically negative/negative, (2) 8K_Ct are positive, and (3) LMDisc_WC are statistically positive. The analyst sample is limited to 95,956 firm quarters.

In untabulated analysis, we estimate models (1)–(3) when MgmtGuide_Ct, ConfCall_Ct, NonGAAP_Ct, InvestDay_Ct, and QMGuide_Ct are each included as VolMeasure. NonGAAP_Ct is negatively associated with bid-ask spreads, the Amihud illiquidity measure, and the COEC. MgmtGuide_Ct and QMGuide_Ct are negatively associated with the Amihud illiquidity measure and positively or not associated with bid-ask spreads and the COEC. ConfCall_Ct and InvestDay_Ct are negatively associated with bid-ask spreads and the Amihud illiquidity measure and positively or not associated with the COEC.

To avoid a significant reduction in the sample, #Anl is set equal to zero when I/B/E/S data is missing. Following the method of Khanna et al. (2015), we include Ind_#Anl, an indicator variable that equals one if I/B/E/S data is available and zero otherwise. We do the same with RD; RD is set equal to zero when Compustat research and development data is missing. We include Ind_RD, an indicator variable that equals one if R&D data is available and zero otherwise. Similarly, we calculate PLit based on the inputs from the Kim and Skinner (2012) model. If the full set of Compustat and return variables are available, we set Ind_PLit equal to one and zero if the return-based variables are unavailable.

For example, the persistence of q-1 (q-4) VDisc_Ct is 0.601 (0.541), while the persistence of q-1 (q-4) VDisc_WC is 0.242 (0.227). Similarly, the persistence of q-1 (q-4) MDisc_Ct is 0.319 (0.263), while the persistence of q-1 (q-4) MDisc_WC is 0.133 (0.134).

The issue of verifying whether a given proxy captures the underlying construct it is designed to capture is not unique to voluntary disclosure proxies.

Identifying firm-periods with no voluntary disclosure versus firm-periods that lack available data has been an ongoing issue with some voluntary disclosure proxies (e.g., management guidance). This has led to the practice of eliminating firms from the sample because researchers cannot discern whether the data source failed to include some firms or whether the firms did not issue the voluntary disclosure. Given the SEC’s mandate that firms provide 8-Ks for voluntary disclosure events, we can capture when firms filed with the SEC but did not issue a voluntary item within an 8-K, leading to a credible “zero disclosure.”

Chen et al. (2015) employ this theorem to support the use of disaggregated information from financial statements to build their disclosure quality measure.

Table 2 Panel A documents that VDisc_Sum equals zero (no measurable disclosure) at the 25th percentile when VDisc_Ct equals 2.0 at the 25th percentile. VDisc_Ct is a simple count of the 8-K voluntary items and exhibits disclosed within a calendar quarter, which more directly measures voluntary disclosures. If a study relies on VDisc_Sum, these observations with voluntary disclosure will be classified as having none.

This is generally true when comparing VDisc_WC and VDisc_Sum, although the construction of VDisc_Sum, relative to VDisc_WC, supports the use of VDisc_WC.

Table 9 documents differences in the persistence of the four voluntary disclosure measures, the components of those measures, and disclosures via the four disclosure channels. Panel B of Appendix 4 documents the content of voluntary disclosures as well as how the content varies across the voluntary 8-K items. These results show that firms’ actual voluntary disclosures vary across disclosure channels and across 8-K items.

For example, Bergman and Roychowdhury (2008) and Brown et al. (2012) examine the link between managers’ disclosure decisions and investor sentiment. Each study appeals more broadly to the voluntary disclosure literature, although the studies rely on different channels of voluntary disclosures (long-range management guidance and non-GAAP earnings, respectively) and report conflicting results: management guidance decreases with investor sentiment, and non-GAAP earnings increase with investor sentiment, respectively. In fact, however, each study selects a voluntary disclosure measure related to the specific aspect of voluntary disclosure of interest. While the results appear contradictory, they both suggest firms strategically disclose; the “conflicting” results are due to the type of voluntary disclosure (of future expectations and of historical information). These studies reflect the importance of tying the construct of interest to an appropriate proxy.

This is a common practice across many research streams. For example, in the voluntary disclosure literature, a number of studies include an 8-K-based measure as an alternative to management guidance-based measures (e.g., Guay et al. 2016; Bourveau et al. 2018) or include a management guidance-based measure as alternative to 10-K-based disclosure (e.g., Francis et al. 2008).

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Title: Measuring disclosure using 8-K filings
Authors: Jing He
Marlene A. Plumlee
Publication date: 05-10-2020
Publisher: Springer US
Published in: Review of Accounting Studies / Issue 3/2020
Print ISSN: 1380-6653
Electronic ISSN: 1573-7136
DOI: https://doi.org/10.1007/s11142-020-09551-y

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