SMU Classification: Restricted 

Measuring Disclosure Using 8-K Filings

Presented by

Marlene Plumlee University of Utah

The views and opinions expressed in this working paper are those of the author(s) and not necessarily those of the School of Accountancy, Singapore Management University.

Measuring Disclosure Using 8K Filings

Jing He

Department of Accounting & MIS

University of Delaware

jinghe@udel.edu

Marlene A. Plumlee

School of Accounting

University of Utah

marlene.plumlee@eccles.utah.edu

November 2019

We appreciate valuable feedback from Philip Berger, David Burgstahler, Mike Cooper, Tricia O’Malley, Russell Lundholm (the editor), two anonymous reviewers, seminar participants at the 2017 AAC Convention, workshop participants at CUHK and UCLA, and numerous invaluable discussions with Atif Ellahie, Rachel Hayes, Mac Gaulin, Daniele Macciocchi, Xiaoxia Peng, David Plumlee, and Jordan Schoenfeld. All remaining errors are the responsibility of the authors.

Measuring Disclosure Using 8K Filings

ABSTRACT

We construct four voluntary disclosure and two mandatory disclosure measures for 260,880 firm-quarters from 2005 through 2016 using 8K data. The first voluntary disclosure measure is the count of 8Ks, a proxy used in prior studies. The second and third voluntary disclosure measures are the count and word count of the 8K items that are 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 8K items and exhibits that include management guidance, conference calls, non-GAAP measures, or investor day disclosures. We document some basic properties of these measures (including their correlations and persistence) and cross-sectional and time-series associations between the measures and firm-level characteristics frequently examined in the disclosure literature. The results suggest that, even though the measures are highly correlated, each of them also capture different aspects of firms’ disclosure activities. Further, we document consistent associations between the level of the voluntary disclosure measures and various firm characteristics, the signs of those associations, and differences in the magnitudes and the signs of those associations across the disclosure measures. We also construct concurrent mandatory disclosure measures based on the mandatory items and exhibits within 8Ks to use as controls. Finally, we provide preliminary descriptive evidence of the content of information provided within the three voluntary 8K items and evidence of their persistence.

Keywords: voluntary disclosure; mandatory disclosure, 8K filings

JEL codes: M41; D83

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1 Introduction

An extensive literature focuses on understanding the sources and implications of voluntary disclosures

provided by firms.1 As noted by Beyer, Cohen, Lys, and Walther (2010), Berger (2011), and others,

empirical research in this area relies on a number of firm-level measures of voluntary disclosure, including

(1) survey rankings/AIMR scores, (2) researcher-constructed measures, (3) the presence or number of

specific firm-level disclosures or events (management earnings guidance, non-GAAP earnings, conference

calls, or investor days), and (4) various measures based on 8K filings.2 While all of these measures capture

cross-sectional variation in disclosure, they are subject to limitations that might reduce their usefulness in

disclosure research. Some of the measures have limited availability, either in terms of the coverage universe

of firms or time periods (e.g., AIMR scores and researcher-constructed measures). Others are constructed

using disclosures provided via one of four specific disclosure channels (i.e., through management guidance,

non-GAAP earnings, conference calls, investor day events), which limit the usefulness of these measures

in terms of capturing broader aspects of firms’ disclosure choices, unless firms’ make consistent choices

across the channels.

More recent studies turn to data from 8Ks (current reports) to construct voluntary disclosure measures

(e.g., Guay et al. 2016; Segal and Segal 2016; Bourveau et al. 2018; Bao, Kim, Mian, and Su 2019; He,

Plumlee, and Wen 2019). Relying on 8K data to construct voluntary disclosure proxies reduces concerns

about the limited availability of the data and allows for a broader span of disclosure channels in the

construction of the measure. In addition, 8Ks include disclosures of events the Securities and Exchange

Commission (SEC) requires firms to disclose that can be used to construct concurrent firm-level mandatory

disclosure measures, which then can be used to incorporated in the empirical analysis of voluntary

1 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, Christensen, Elliott, and Mergenthaler 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. 2 See (1) Lang and Lundholm 1993, 1996; Bushee and Noe 2000, (2) Miller 2002; Francis, Nanda, and Olsson 2008, (3) Bergman and Roychowdhury 2008; Brown et al. 2012; Brown, Lo, and Hillegeist 2004; Tasker 1998; Kalay 2015; Vashishtha 2014; Kirk and Markov 2016, and (4) Leuz and Schrand 2009; Balakrishnan, Core, and Verdi 2014; Guay, Samuels, and Taylor 2016; Segal and Segal 2016; Gleason, Ling, and Zhao 2019; Cadman, Heinle, and Macchioccio 2018; Schoenfeld 2017; Bourveau, Lou, and Wang 2018.

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disclosure.3 Motivated by the use of 8K data in empirical research and the potential benefits of constructing

measures that capture a diverse set of disclosures, both voluntary and mandatory, available for all firms that

file with the SEC, we construct 8K-based disclosure measures that replicate and extend measures used in

the literature. We also present descriptive statistics and the results of univariate and multivariate analysis

that documents basic properties of these measures. Further, we provide preliminary analyses of the

information content of the voluntary disclosure components of the 8K filings.

The SEC requires firms to file 8Ks to notify investors of a series of voluntary and mandatory material

(firm) events.4 When filing an 8K, firms select one or more item numbers from the 32 possible reporting

items that identifies the type of event that is being reported. Each item number includes a description of the

underlying 8K triggering event and detailed instructions about the information to be included in the 8K (see

Table 1 for a full list of the item numbers and the descriptions). We exploit these SEC filing requirements

to identify and obtain firm disclosures from the SEC’s EDGAR website and then classify each item number

as either voluntary or mandatory, based on the nature of the triggering event. We rely on the explicit

wording in the SEC regulations regarding the items to make this assessment. For example, with respect to

item 1.01 Entry into a Material Definitive Agreement, the 8K states,

If the registrant has entered into a material definitive agreement not made in the ordinary course of business of the registrant, or into any amendment of such agreement that is material to the registrant, disclose the following information” (emphasis added).

Item 1.01 is classified as a mandatory item since the SEC requires a firm to report the underlying event

itself. Similarly, with respect to Item 2.02 Results of Operations and Financial Condition, the 8K states,

If a registrant, or any person acting on its behalf, makes any public announcement or release (including any update of an earlier announcement or release) disclosing material non-public information regarding the registrant’s results of operations or financial condition for a completed quarterly or annual fiscal period, the registrant shall disclose the date of the announcement or release, briefly identify the announcement or release and include the text of that announcement or release as an exhibit.” (emphasis added).

3 The disclosure literature suggests a link between voluntary and mandatory disclosure, based on both theoretical (e.g., Gigler and Hemmer 1998; Freidman, Hughes, and Michaeli 2019) and empirical findings (e.g., Francis et al. 2008; He et al. 2019). Beyer et al. (2010), Heitzman, Wasley, and Zimmerman (2010), and others have questioned whether traditional voluntary disclosure measures also capture mandatory disclosure. If voluntary disclosure decisions are related 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. 4 The SEC defines a “material” event as one that is expected to influence a reasonable investor’s investment decision.

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In this case, the triggering event is a voluntary disclosure of information, so we classify Item 2.02 as a

voluntary item. Using this process, we classify three 8K items as voluntary: Item numbers 2.02, 7.01, and

8.01 and look to the item numbers and related exhibits as voluntary disclosures.5 The remaining item

numbers are classified as providing mandatory disclosures.. If firms follow the SEC’s requirements,

including the selection of the 8K item number, our 8K-based measures should capture disclosures that firms

have determined to be both material and either voluntary or mandatory.

We construct four firm-specific voluntary disclosure measures. Our first measure, which mirrors a

proxy used in prior work (e.g., Leuz and Schrand 2009; Li 2013; Balakrishnan et al. 2014; Guay et al.

2016), is the number of 8Ks a firm files during a calendar quarter.6 This yields a relatively crude measure

of voluntary disclosure, however, as a single 8K might include (1) multiple reportable transactions or events

disclosed via multiple item numbers, (2) additional exhibits, or (3) information related to either mandatory

or voluntary items. Hence, we construct two additional voluntary disclosure measures using data from 8K

items classified as voluntary. These measures better isolate voluntary disclosures and reflect when the 8K

includes multiple item numbers and additional exhibits. Specifically, our second (third) voluntary

disclosure measure is the count (the word count) of the items and the attached exhibits that firms report

within 8K item numbers 2.02, 7.01, and 8.01, the voluntary item numbers. Our fourth voluntary disclosure

measure is the number of times that a firm’s voluntary 8K item indicates the presence of any of the four

voluntary disclosure channels drawn from prior work: management guidance, conference calls, non-GAAP

measures, and investor day events. We focus on these four specific channels as prior research commonly

uses the frequency of these disclosures as proxies for firm-specific voluntary disclosure.7 Finally, we create

5 With respect to the additional voluntary 8K Items, 7.01 and 8.01, the 8K 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” and 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, page 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. 6 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, Hayes, and Plumlee 2019). 7 See, for example, Bergman and Roychowdhury (2008); Brown et al. (2012); Brown et al. (2004); Tasker (1998); Kalay (2015);

Vashishtha (2014); Kirk and Markov (2016).

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two mandatory disclosure measures: the count and word count of the items and exhibits that firms report

within 8K item numbers classified as mandatory.

8K-based measures offer several advantages in capturing firm-level voluntary disclosure over

alternatives used in the literature. First, 8Ks incorporate a broad range of firm disclosures made across

multiple venues, including the specific channels (i.e., management guidance, conference calls, non-GAAP

measures, investor day events) exploited by earlier studies to capture voluntary disclosure. Second, since

8Ks are available for the universe of firms that file with the SEC, measures based on these data can provide

significantly greater coverage, in terms of both the number of firms and disclosures per firm, than other

voluntary disclosure measures. Our sample, which also requires two Compustat data items (total assets and

net income), includes 10,290 firms across 48 calendar quarters for a total of 260,880 firm-quarters. Third,

8K-based measures employ disclosures attributable directly to firms, consistent with Kasznik and Lev

(1995), Lang and Lundholm (2000), and Miller (2002). The reliance on firm-filed 8Ks instead of alternative

information sources (e.g., analyst-based AIMR scores or researcher-constructed scores) to identify

voluntary disclosures should yield measures that reflect heterogeneity in quality and timeliness that is

attributable to firms’ disclosure choices. Finally, since firms also use 8Ks to report mandatory disclosures,

8K data also can be used to construct concurrent mandatory disclosure measures.

8K-based measures capture significant aspects of firms’ voluntary disclosure activities. Even so, we

have a limited understanding of the empirical properties of these measures, the associations among them,

and how they are related to firm-specific characteristics commonly linked with voluntary disclosure. This

study seeks to provide such information. Documenting the basic properties of these disclosure measures

provide insights into firms’ disclosure propensities. Further, such evidence serves as a useful starting point

for researchers as they seek the most appropriate measure to use in their studies. In empirical analysis, we

document the statistical properties of the four voluntary disclosure measures we construct, and we examine

the cross-sectional and time-series correlations among the voluntary disclosure and the concurrent

mandatory disclosure measures. We also use univariate and multivariate analysis to investigate relations

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between the disclosure measures and firm-level characteristics that the literature frequently links with

disclosure, including firm size, performance, and risk.

While we document significant positive correlations among our voluntary disclosure measures, our

analysis, including within subsamples that are based on data availability and on sorting by the rank of firm

characteristics, suggests unique aspects of each. For example, we show that 8K-based voluntary disclosure

measures for the set of firm-quarters that lack management forecast date from I/B/E/S used in many studies

to form a voluntary disclosure measure are systematically different from the same set of disclosure measures

from firm-quarters with the I/B/E/S data. Further, data limitations in constructing proxies for specific firm

characteristics that the literature views as theoretically related to voluntary disclosure (e.g., analyst

following, research and development intensity) also reflect systematic differences in the disclosure

measures as well. Our analysis also documents that the relation between the magnitude of the voluntary and

mandatory disclosure measures and various firm characteristics are sometimes linear (e.g., with firm size),

and other times non-linear (e.g., with firm performance). Ultimately, these relations vary based on the

disclosure measures and the firm characteristics considered.

In multivariate analysis, we show that the relation between 8K-based voluntary disclosure measures

and various firm-level characteristics vary with the disclosure measures as well. In addition, we find that

the time-series correlations of each of the voluntary disclosure measures are quite large. This highlights the

importance of considering the prior period’s disclosure as a determinant of current period disclosure.

Moreover, we find that higher levels of concurrent mandatory disclosure are associated with higher levels

of voluntary disclosure, although controlling for concurrent mandatory disclosure has a limited effect on

how voluntary disclosure enters into multivariate models. Finally, we document the persistence of the (1)

disclosure measures, (2) primary 8K items, (3) four disclosure channels commonly explored in the

literature, and (4) specific channels conditional on the 8K item it is disclosed within. These findings should

be of interest to regulators and to academics as they seek to select disclosure measures as part of their

research design.

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The second objective of this study—providing large-sample descriptive evidence about the content of

the information that firms voluntarily disclose and which voluntary 8K item it is reported within—is

motivated by two facets of the disclosure literature. First, some studies that examine the relation between

voluntary disclosure and various constructs rely on data from a single voluntary disclosure channel (e.g.,

management guidance or non-GAAP earnings). The overall frequency of disclosures via these channels,

the specific 8K item where firms elect to report these disclosures, and whether disclosures via these

channels are correlated with each other or across time is not known. Second, some studies look to

disclosures made within a particular voluntary 8K item to capture specific types of disclosure or specific

content (Gleason et al. 2019; Segal and Segal 2016), including strategic disclosures, although large-sample

evidence of the specific information firms provide within those 8K items is sparse.

Our analyses provide researchers and other interested parties with information related to both of these.

Using data collected via a keyword search of the three voluntary 8K items and the associated exhibits filed

during our sample period, we document the frequency with which firms report management guidance,

conference calls, non-GAAP measures, and investor day events, as well as the voluntary 8K item where

each of them is reported.8 We also provide detailed information about the content of the information (e.g.,

whether firms discuss business combinations or patents) reported in the two non-earnings-announcement

voluntary 8K items (7.01 and 8.01).

Thus, our study makes several contributions to the literature. First, we construct four voluntary

disclosure measures for a broad cross-section of firm-quarters and provide information about the basic

properties of these measures. The measures are based on 8K-reported information released by firms across

a broad range of channels, deemed voluntary by the firm, and available for all firms that report to the SEC.

Second, we construct concurrent mandatory disclosure measures useful in addressing concerns raised in the

8 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, attempt to deal with 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”. Our only data requirement is that a firm filed an 8K with the SEC during the sample period and that Compustat reported total assets and net income.

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literature (Beyer et al. 2010) about disentangling voluntary and mandatory disclosure. Third, we document

associations among these voluntary disclosure measures and with a series firm-specific characteristics that

the literature frequently links with disclosure. These findings should prove useful to researchers in

understanding the basic properties of 8K-based measures and provide a basis for selecting the most

appropriate measure for use in a specific research setting. Finally, we detail the frequency with which firms

employ four specific disclosure channels that have been used in numerous prior studies and provide

descriptive evidence about the content of disclosures reported within 8K Items 2.02, 7.01, and 8.01.

2 Literature and background

2.1 Literature – disclosure measures

Disclosure-related empirical studies rely on various proxies to capture variation in firm-level disclosure.

Frequently, researchers develop voluntary disclosure proxies using (1) the frequency of disclosures through

a single channel, including management guidance, conference calls, non-GAAP measures, and investor

days (e.g., Bergman and Roychowdhury 2008; Brown et al. 2012; Tasker 1998; Kirk and Markov 2016),

or (2) scores constructed from analysts’ or researchers’ assessments of firm-provided information (e.g.,

AIMR scores, used by Lang and Lundholm 1996, and researcher indices, used by Francis et al. 2008). As

noted by Beyer et al. (2010), Berger (2011), and others, however, there are potential disadvantages of using

these proxies when measuring voluntary disclosure. First, relying on a single disclosure channel fails to

consider the full menu of disclosure options available to managers. Prior studies find that there are

significant differences between the use of the various voluntary disclosure channels (Ajinkya, Bhojraj, and

Sengupta 2005; Black, Christensen, Joo, and Schmardebeck 2017), suggesting that a measure that relies on

a single channel will not fully reflect firm-level voluntary disclosure. Other concerns include whether

measures based on AIMR scores or researcher-constructed indices include a mandatory element, or if they

capture a broad range of disclosures as they are function of the scorers’ assessments of what matters.

Finally, these measures generally are available for a limited set of firms.

Recent studies have turned to firms’ 8K filings, one of the most common SEC filings accessed by

investors (Drake, Roulstone, and Thornock 2015), to capture voluntary disclosure. For example, Leuz and

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Schrand (2009), Balakrishnan et al. (2014), and Guay et al. (2016) use the number of 8Ks filed by a firm to

capture its voluntary disclosure. Bourveau et al. (2018), Bao et al. (2019), and Ellahie et al. (2019) use the

number of voluntary 8K items within the 8Ks to capture voluntary disclosure. Segal and Segal (2016) use

data from two 8K voluntary items (Items 7.01 and 8.01) to capture strategic disclosures and Cadman et al.

(2019) use one 8K voluntary item (Item 2.02) to capture a firm’s commitment to voluntary disclosure. The

appeal of 8K-based measures is the ability to construct them for a broad range of firms and the direct link

between the firm and the disclosure.

These issues – concerns with the efficacy of using a voluntary disclosure measure based on a single

channel, the limited availability of data to construct some disclosure proxies, and the increasing use of 8K

data to construct voluntary disclosure measures—motivate our study. To address these issues, we begin by

providing researchers with a series of voluntary disclosure measures that capture a broad set of firm-

provided disclosures and are available for a diverse set of firms. We document statistical properties of the

voluntary disclosure measures, and explore the cross-sectional and time-series correlations among them

and with concurrent mandatory disclosure measures. We also present univariate and multivariate analysis

between the voluntary disclosure measures and firm-level characteristics frequently linked with voluntary

disclosure, including firm size, performance, risk, and equity issuance. Finally, we document the persistence

of the various measures. Our analysis provides insights into firms’ disclosure activities reported within 8Ks

and an understanding of the basic properties of disclosure measures based on these activities as researchers

consider the most appropriate proxy to use in their research setting.

2.2 Disclosure and 8K filings

Our reliance on 8Ks to obtain data to construct disclosure measures is analogous to the approaches

employed by Kasznik and Lev (1995), Lang and Lundholm (2000), and Miller (2002). Each of those studies

uses disclosures issued by or directly attributed to a firm. The objective of each study is to enhance our

understanding of firms’ voluntary disclosure choices within specific settings; the studies highlight that this

focus is on disclosures made by firms. For example, Kasznik and Lev retrieve “all corporate announcements

made through the various news wire system,” while Miller notes that he includes “articles written by third

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parties only if they contain previously unreleased information quoted from management” (p. 183). 9

Likewise, the objective of our study is to capture firms’ voluntary disclosures.

The SEC requires firms to file an 8K whenever they (1) announce a major event that shareholders

should know about or (2) meet the requirements of RegFD, which requires firms to “disclose(s) material

nonpublic information to certain individuals or entities—generally, securities market professionals, such as

stock analysts, or holders of the issuer’s securities who may well trade on the basis of the information”

(SEC website). Consistent with 8Ks providing information to the market, Lerman and Livnat (2010) show

that all types of 8K items affect firm returns, price volatility, and trading volume; Drake et al. (2015) find

that 8Ks are one of the most requested SEC filings (in addition to 10Ks10, 10Qs, and Form 4s).

As noted by Carter and Soo (1999) and Lerman and Livnat (2010), 8Ks report information releases that

reflect (1) mandatory disclosures about events that the SEC requires a firm to report (events that happen to

a firm or events that it participates in) and (2) voluntary disclosures that reflect voluntarily supplied

statements or discussions that the SEC requires a firm to publicly report if the firm chooses to disclose

information.11 Generally, the SEC requirement is that firms file 8Ks with mandatory items within four

business days after the event, although 8Ks related to the announcement of new officers (Item 5.02) can be

delayed until another public announcement of the appointment (e.g., press release, trade conference, etc.)

and Item 4.02 (related to an issuer’s receipt of an auditor’s restatement letter) must be filed within two

business days. Filing deadlines around the three voluntary 8K items (2.02, 7.01, and 8.01) are as follows:

Item 2.02 (“results of operations”) must be completed before any associated analyst conference call. Item

7.01 (RegFD) filings must be (i) simultaneous with the release of the material that is the subject of the filing

9 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).” 10 Other studies use textual analysis to develop disclosure measures, frequently based on 10Ks (e.g., Brown and Tucker 2011; Li, Lundholm, and Minnis 2013). We do not include 10K-based measures, as they are mandatory filings required by the SEC on an annual basis. While 8Ks also are mandatory filings, 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 of this issue. 11 For example, as discussed earlier, the SEC requires a firm to file an 8K when it enters into a material definitive agreement (8K Item 1.01) or when a director departs (8K 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 8K 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 8K triggering event is a firm disclosure choice.

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(if such material is intentionally released to the public) or (ii) the next trading day (if the release was

unintentional). Item 8.01 disclosures (“other events”) have no filing deadline.

We rely on the SEC’s framework that requires firms to report material information via 8Ks to identify

when a firm discloses information and the reported item number to characterize the disclosure as voluntary

or mandatory. If firms fail to report items as required, inappropriately classify the reported items, or disclose

information but fail to disclose via 8Ks it will impact the disclosure measures.12

3. Constructing the disclosure measures

We begin by downloading all 8Ks and the attached exhibits available through the SEC EDGAR website.

Our sample period includes filings from January 2005 through December 2016.13 Within each 8K, we

identify and obtain the reportable items and attached exhibits. We then count the items and exhibits, count

the number of words in the items and exhibits, and perform a word search within the voluntary items and

exhibits. These data are used to construct our measures.

The SEC provides a list of 32 potential 8K item numbers (Table 1 Panel A). Item numbers 1.01 through

8.01 refer to specific topics and Item 9.01 is where firms attach financial statements and exhibits. As

discussed earlier, Item numbers 2.02, 7.01, and 8.01 and related financial statements and exhibits are

classified as voluntary. The remaining item numbers (except Item 9.01) and related financial statements

and exhibits are classified as mandatory.

We use the following process to classify information reported within 8Ks. First, for the 21.4 percent of

the 8Ks that report a single item number from 1.01 to 8.01; any financial statements or exhibits within these

12 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 8K 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 8K. 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 8Ks. He requires that the 8K 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 8K-based disclosure measures. 13 The sample begins in 2005, subsequent to when the SEC changed 8Ks 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 8K 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.

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8Ks are classified as voluntary or mandatory based on that item number. Some 8Ks are filed with just an

Item 9.01 (3,190 times or 0.4% of our 8Ks), however: we classify these Item 9.01s as mandatory. To classify

Item 9.01 exhibits that are included in 8Ks with one or more Item 1.01 through 8.01, we do the following.

When the 8K includes exactly two items and one of them is an Item 9.01 (53.5% of our 8Ks), the 9.01 is

classified as either voluntary or mandatory, based on the classification of the other item. To classify the

remaining Item 9.01 exhibits within the 8Ks—8Ks with three or more items including an Item 9.01 (24.7%

of our 8Ks)—we match the exhibits within the 9.01s to the Items 1.01 to 8.01 using the following steps.

First, we search the text of each non-9.01 item to identify any reference to specific exhibit numbers and

match the item and exhibit based on that reference and the SEC’s list of exhibit numbers and associated

item numbers (see Panel B of Table 1). Any unmatched exhibits then are sorted into two groups: exhibits

1–95 and exhibit 99s. Exhibits 1–95 are matched to 8K items, again based on the SEC’s list of exhibit

numbers and associated item numbers. Exhibit 99s are matched to 8K items using the following steps.14

First, if the 8K has an Item 2.02, the Exhibit 99 is matched with it. Second, if there is no Item 2.02 but there

is an Item 8.01, the Exhibit 99 is matched with the Item 8.01. Finally, if there is no Item 2.02 or 8.01, but

there is an Item 7.01, then the Exhibit 99 is matched with the 7.01.15 Using the steps described above, we

match all but 4.25 percent of the 8K exhibits with an item number.16 These unmatched exhibits are dropped

from our analysis.

Our final data collection is based on a keyword search of the voluntary 8K items and exhibits. The data

from this search are used to construct the fourth voluntary disclosure measure and to provide descriptive

evidence about the information firms report within the voluntary items. First, we use the keyword search to

identify whether a specific voluntary 8K item or its associated exhibits reports a disclosure related to the

14 When we match the remaining unmatched Exhibit 99s, we are matching 8Ks 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 8Ks with only mandatory items. 15 Our decision rule to match first with Item 2.02, then Item 8.01, and then Item 7.01 is based on reading the 8Ks filed by a random sample of 20 firms across the entire sample period and 300 additional 8Ks that include item numbers 2.02, 7.01, or 8.01. Within those 8Ks, 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 percent of this sample with two items, one of which is an Item 9.01, 32.7 percent of the non-9.01 items are Item 2.02, 25.0 percent of them are Item 8.01, and 14.6 percent of them are Item 7.01. 16 The main reasons for this are (1) the text does not mention an exhibit number; (2) the 8K 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 8K refers to a letter such as “exhibit (A).”

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voluntary disclosure channels discussed earlier: management guidance, non-GAAP measures, conference

calls, or investor day events). For each voluntary 8K item (and its related exhibits), we set MgmtGuide_Ct,

(QMgmtGuide_Ct, NonGAAP_Ct, ConfCall_Ct, or InvestDay_Ct) equal to one if the keyword search

identifies the disclosure of management guidance (quantitative management guidance, a non-GAAP

measure, a conference call, or an investor day event) and zero otherwise. The sum of these indicator

variables within a calendar quarter is used to construct our fourth voluntary disclosure measure. See

Appendix 1 for variable definitions and Appendix 2 for data processing procedures and the keyword search

strings for the disclosure channels.17

Appendix 3 provides details about the 8K elements (items and exhibits) used to construct the disclosure

measures. Panel A (B) includes variable definitions (descriptive statistics) for these elements. Panel B

shows there is meaningful cross-sectional variation in both the number and word count of the items and

exhibits. A few items of note. First, the mean values of the count and word count of the items and the

exhibits are significantly different from zero, suggesting that including both pieces of a firm’s disclosure

will impact the cross-sectional variation in the constructed measures. Second, the mean values of the items’

word count are consistently smaller than the mean values of the exhibits’ word count. For example, the

mean value of WC_VolItem is 374, while the mean value of WC_VolEX is 4,684. Third, the mean (median)

count of the voluntary items and exhibits is greater than the mean (median) count of the mandatory items

and exhibits: mean (median) Ct_VolItem is 2.03 (2.00) while mean (median) Ct_ManItem is 1.74 (1.00). In

contrast, the mean (median) word count for the voluntary items and exhibits is smaller than for the

mandatory items and exhibits: mean (median) WC_VolItem is 374 (144), while mean (median)

WC_ManItem is 610 (269). Fourth, for both voluntary and mandatory elements, the standard deviation of

items’ count (items’ word count) is smaller than the standard deviation of exhibits’ count (exhibits’ word

count). For example, the standard deviation of Ct_VolItem is 1.96, which is significantly smaller than the

standard deviation of Ct_VolEX, 2.35. Similarly, the standard deviation of WC_VolItem is 1,188, which is

17 We also perform a keyword search of the voluntary 8K 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.

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significantly smaller than that of WC_VolEX, 15,674. Finally, the standard deviations of the mandatory

items’ count and word count are greater than the standard deviations of the voluntary items’ count and

voluntary word count, respectively. The similar trend holds when we compare the standard deviations of

the mandatory exhibits’ count and word count with the standard deviations of the voluntary exhibits’ count

and word count. For example, the standard deviation of WC_ManEX is 30,973, which is significantly

greater than that of WC_VolEX which is 15,674. In short, (1) including items and exhibits, rather than items

alone, captures increased cross-sectional variance; (2) using word counts, rather than the count of

items/exhibits, captures even more variance; and (3) sorting disclosures into those that voluntary and

mandatory is meaningful.

4. Univariate statistics

This section of the paper presents a detailed description of the underlying 8K data used to construct the

disclosure measures and descriptive statistics for both the disclosure measures and the firm characteristics

for the firm-quarters that comprise our sample. The remainder of the study uses both univariate and

multivariate analysis to document some of the basic properties of the measures, to show how these measures

are related to each other, and to explore associations between the disclosure measures and firm

characteristics that the literature frequently views as being related to disclosure.

4.1 Descriptive statistics

4.1.1 8K items and exhibits

Table 1 Panel A lists the 32 SEC-mandated item numbers and presents (1) the number of times each item

number appears during the sample period (count), (2) the proportion of the total items this represents

(%Items), and (3) the proportion of the 8Ks associated with each item number (%8Ks). The most frequently

filed item is Item 9.01 (560,316 observations attached to other items and 3,190 stand-alone observations),

which is where firms report exhibits. As noted earlier, most 9.01s are filed in an 8K with one or more items.

We classify the Item 9.01 exhibits as voluntary or mandatory, based on the Item 1.01 – 8.01 it is related to.

Thus, item numbers 1.01–8.01 comprise the relevant item numbers in our analysis, while Item 9.01

attachments comprise the exhibits.

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During our 48-quarter sample period, firms reported a total of 984,789 8K items across a total of

724,862 8Ks (excluding 9.01s issued in conjunction with other 8K item numbers). Five 8K items (1.01,

2.02, 5.02, 7.01, and 8.01) constitute the majority of these observations (81.1 percent of Items 1.01–8.01

and stand-alone 9.01s). The three voluntary items comprise over half of the sample (53.8 percent). Item

2.02 (Results of Operations and Financial Condition) is the most frequently reported of these items (21.9

percent of the items). Item 7.01 (Regulation FD Disclosure) constitutes 13.8 percent of the items, and Item

8.01 disclosures (Other Events) constitutes 18.1 percent of the items. The most frequently reported

mandatory items are Item 1.01 (Entry into a Material Definitive Agreement—13.5 percent of the items) and

Item 5.02 (Departure of Directors or Principal Officer, Election of Directors, Appointment of Principal

Officers—13.8 percent of the items).

Table 1 Panel B presents a breakdown of the 29 exhibit numbers that appear in our sample. The most

frequently filed exhibits (#99—additional exhibits) often reference firms’ press releases that are furnished

as exhibits within the 8Ks. Panel C provides a detailed description of the Exhibit #99—additional exhibits,

listed by the item number to which the exhibits are associated. Across all three panels in Table 1, we

highlight the items, exhibits, and Exhibit #99s that are most frequently disclosed within 8Ks: Items 1.01,

2.02, 5.02, 7.01, and 8.01 and their associated exhibits. In untabulated analysis, we find that an average

firm files at least one 8K per calendar quarter. The five primary 8K items, Item 1.01 (2.02, 5.02, 7.01, and

8.01) are reported in 33.9 (73.9, 37.4, 28.8, and 38.4) percent of the calendar quarters in our sample period.

Thus, the unconditional expectation that a firm will issue an Item 2.02 (earnings announcement) during a

calendar quarter is 0.739.

4.1.2 8K-based disclosure measures

We aggregate the 8K data by calendar quarter to construct our firm-level disclosure measures. 8K_Ct, our

first voluntary disclosure measure, is the number of 8Ks a firm files, consistent with Leuz and Schrand

(2009), Balakrishnan et al. (2014), Guay et al. (2016), and others. To construct our second and third

voluntary disclosure measures and two concurrent mandatory disclosures measures, we use the reported

items and exhibits within the 8Ks. VDisc_Ct, our second voluntary disclosure measure, is the total number

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of voluntary 8K items and exhibits reported in the 8Ks filed during the calendar quarter; VDisc_WC, our

third voluntary disclosure measure, is the word count of those items and exhibits.18 Similarly, MDisc_Ct is

the number of mandatory 8K items and exhibits reported in the 8Ks filed during the calendar quarter, and

MDisc_WC is the word count of those 8K items and exhibits.

VDisc_Sum, our fourth voluntary disclosure measure, is based on the data from our keyword search of

the voluntary 8K items and exhibits. As discussed above, we search each of the voluntary 8K items and

exhibits to determine whether that item or exhibit reports the disclosure of management guidance, a

conference call, a non-GAAP financial measure, or an investor day event. If the search identifies the

presence of management guidance (a conference call, a non-GAAP measure, an investor day event) within

the 8K item or its exhibit, then MgmtGuide_Ct, (ConfCall_Ct, NonGAAP_Ct, InvestDay_Ct) equals 1, and

0 otherwise. Thus, for each voluntary 8K item, each of the four variables is either one or zero. VDisc_Sum

is the sum of these four variables, aggregated over a calendar quarter.19 Our keyword search also identifies

when management guidance is quantitative (a subset of the management guidance observations), which is

used to calculate QMGuide_Ct.20

4.1.3 Sample and descriptive statistics

We construct our disclosure measures for all firm-calendar quarters with data available to download from

the SEC website, starting with the first quarter of 2005 through the fourth quarter of 2016 (48 calendar

quarters). Our sample includes firm-calendar quarters for firms that report a minimum of one 8K during the

sample period and that we can match with Compustat using the SEC provided central index key (CIK).21

To be included in our analysis, we only require Compustat report a nonzero value for total assets and a non-

missing value for net income.

18 For example, if a firm files two 8Ks 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. 19 The maximum value of VDisc_Sum for any firm-quarter is the number of voluntary 8K items within the quarter times four, by

construction. Within our sample, the maximum value of VDisc_Sum is 52. 20 Miller (2002) finds that nearly 80 percent of the forward-looking statements in his sample are qualitative. We find that about 50 percent of our management guidance is quantitative, although this varies by the item number where the guidance is reported. 21 Some firms in our sample issue 8Ks 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 8Ks, although they issue 8Ks before and after

those firm quarters, we set VDisc_Ct and MDisc_Ct equal to zero as well.

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Table 2 Panel A reports summary statistics for our six disclosure measures. Relying on 8K data to build

our sample yields 260,880 firm-quarter observations over a twelve-year sample period; an advantage of our

voluntary disclosure measures is the large number of firm-quarters for which those measures can be

calculated. The mean (median) number of 8Ks issued within a calendar quarter (8K_Ct) is 2.78 (2.00),

consistent with earlier studies. In untabulated analysis, we find that the mean (median) total number of the

items and exhibits within 8Ks for a given quarter is over twice that of 8K_Ct. This difference reflects the

fact that some 8Ks include multiple items and others include exhibits along with the items. When we turn

to the voluntary and mandatory disclosure measures, we show that firms sometimes do not issue an 8K with

a mandatory item during a calendar quarter: MDisc_Ct is zero at the 25th percentile. The same is not true

for voluntary items: VDisc_Ct is 2.0 at the 25th percentile. We also find that the mean (median) value of

VDisc_Ct (3.78 (3.00)) is greater than the mean (median) value of MDisc_Ct (2.98 (2.00)). When disclosure

is measured using word counts, however, the mean (median) values of VDisc_WC (5,058 and 2,441) are

less than (greater than) the mean (median) values of MDisc_WC of 11,114 (432). These differences are

statistically significant and suggest that it is important to consider whether more refined measures, based

on word counts, provide a more appropriate measure of firm disclosure than a simple count of items and

exhibits. Finally, we document that the mean (median) value of VDisc_Sum is 1.91 (1.00) and zero at the

25th percentile.22

We include a broad set of firm-specific characteristics in our study, drawing from the literature to

identify variables frequently viewed as related to disclosure. We loosely classify the firm characteristics

into three categories: structural, performance-related, and environmental. The structural variables are

relatively stable across time while the performance-related and environmental variables tend to be more

time specific. We include five structural variables (TAsst, MVE, #Anl, Segm, FAge). TAsst is total assets at

the end of quarter t. MVE is the market value of equity at the end of quarter t. #Anl is the number of analyst

that follow the firm during quarter t using I/B/E/S data. Segm is the number of business plus geographic

22 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 8Ks.

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segments in Compustat during quarter t, and FAge is the number of years a firm appears in Compustat. We

also include six performance-related variables (two profitability measures—ROA and Loss—and BTM, RD,

Comp, and RetVol). ROA is return on assets (current net income divided by total assets). Loss in an indicator

variable that equals one if a firm reported a loss in any of the four preceding quarters and zero otherwise.

BTM is book value of equity divided by the market value of equity, using Compustat data. RD is Compustat-

reported research and development expense during quarter t, scaled by TAsst. Comp, a competition measure

based on the Herfindal index, is the sum of squares of the market shares of the firm within a four-digit SIC

industry. RetVol is the standard deviation of a firm’s monthly returns over the last 12 months. We include

two environmental firm characteristics: Issue and PLit. Issue is an indicator variable that equals one if the

number of shares outstanding increases by more than 10 percent from quarter t+1 to quarter t+2. PLit is the

ex-ante probability of litigation, based on Model 3 in Table 7 from Kim and Skinner (2012).

Panel B reports summary statistics about the sample firm characteristics. The number of observations

for in this panel, based on data limitations. Ultimately, consistent with our ability to construct disclosure

measures for a broad range of firms and our minimal Compustat data requirements, our sample includes

smaller and less profitable firms than found in many disclosure studies. For example, Bergman and

Roychowdhury (2008) report mean (median) MVE of 3,694 (695), compared to 2,518 (250) in our sample.

They also report a mean (median) ROA of 0.01 (0.01), while the mean (median) ROA in our sample is -0.12

(0.00). Even so, our minimal data restrictions yield a sample that includes a larger number of firms (Guay

et al. include an average of about 4,200 firms per year versus an average of about 5,400 firms per quarter

in our sample), poorer performing firms, and firms that are not followed by analysts. We include these firm

characteristics in our examination of the association between the disclosure measures and firm

characteristics presented in Tables 4, 5, and 8.

Panel C of Table 2 reports summary statistics for the four disclosure channel variables and the

quantitative version of management guidance: MgmtGuide_Ct, ConfCall_Ct, NonGAAP_Ct, InvestDay_Ct,

and QMGuide_Ct. The median value of each variable is zero. This means that fewer than 50% of firm

quarters include a disclosure of the relevant disclosure channel. Further, as the median value of VDisc_Ct

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is three, it suggests that limiting voluntary disclosure to disclosure via one of these four disclosure channels

would result in a number of firm quarters with voluntary 8K disclosures being classified as having no

voluntary disclosure.

Panel D of Table 2 documents the voluntary 8K item where firms disclose each of the four disclosure

channels. We report values and include percentages based on two scalars. The first scalar is the total number

of the specific disclosure channel observations and is used to calculate %Variable, which reports the

proportion of each disclosure channel reported in each voluntary 8K item. The second scalar is the total

number of the 8K item 2.02s (7.01s, 8.01s) filed within the sample period, and is used to calculate %2.02

(%7.01, %8.01), which reports the proportion of the 2.02s (7.01s, 8.01s) that include the disclosure

channel.23 We include No_ALT in the table, which is an indicator that equals one if none of the four

disclosure channels is identified in a given 8K item.

We document that, across the 48 sample quarters with a total of 529,710 voluntary 8K items (215,616

Item 2.02s, 135,626 Item 7.01s, and 178,468 Item 8.01s), firms reported management guidance 162,894

times (86,001 are quantitative), conference calls 162,380 times, non-GAAP measures 148,216 times, and

investor day events 24,687 times. Even so, in 187,254 (35.3 percent) of the voluntary 8K items, No_ALT

equals one. This means that in over one third of all the voluntary 8K items our keyword search fails to

identify any of the four disclosure channels. We do find that each of the four disclosure channels is much

more frequently reported in Item 2.02 than in either Item 7.01 or 8.01. Consistent with Rogers and Van

Buskirk (2013), we find that 68.7 (73.2) percent of management guidance (quantitative management

guidance) is reported within Item 2.02. Moreover, 51.9 percent of Item 2.02s include management

guidance; over half of that guidance (29.2 percent) is quantitative. Firms frequently report management

guidance in Items 7.01 and 8.01 as well: 19.0 and 12.3 percent of the time, respectively. This guidance is

quantitative about half the time—18.3 percent of observations—when it is reported in Item 7.01, and about

23 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 Items 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 8K item.

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a third of the time—8.5 percent of observations—when it is reported in Item 8.01. We also show that the

majority of three of the disclosure channels (management guidance, conference calls, non-GAAP measures)

are reported within Item 2.02 and that the majority of Item 2.02s report one or more of these channels. Only

14.3 percent of Item 2.02s do not include at least one of these disclosure channels. We also document,

however, that disclosures via these four channels are frequently reported in Items 7.01 and 8.01: only 37.0

percent of 7.01s and 59.5% of 8.01s do not report any one of these disclosure channels.

4.1.4 Industry analysis

The link between disclosure and industry is often explored or suggested in the literature (e.g., Lang and

Lundholm 1993; Ali, Klasa, and Yeung 2014). Consistent with that, Table 3 Panel A documents significant

differences in the average magnitudes of the disclosure measures across the Fama-French 12 industries.

The specific disclosure measure used, however, affects those differences. For example, the industry with

the lowest average level of voluntary disclosure is Business Equipment, based on three of the four voluntary

disclosure measures (mean values of 8K_Ct = 2.70, VDisc_Ct = 3.17, VDisc_WC= 3,581) but is Health,

medical equipment, and drugs, based on VDisc_Sum (mean value of 1.68). The industry with the highest

average level of voluntary disclosure is Oil, gas, & coal extraction and products, based on 8K_Ct (mean of

3.7), and is Utilities, based on the other three measures (mean values of VDisc_Ct = 5.69, VDisc_WC=

12,213, VDisc_Sum = 3.12). We also document the level of 8K-based mandatory disclosure across

industries. Based on both mandatory disclosure measures, Oil, gas, & coal extraction and products has the

highest level of average disclosure. Finance (Business equipment) has the lowest average level of

concurrent mandatory disclosure based on the count (word count) of the mandatory 8K items.

Panel B presents additional evidence of the relative importance of industry in explaining variation in

disclosure. It presents the results of regressing the voluntary and concurrent mandatory disclosure measures

on indicator variables for the Fama-French 12 industry classifications.

Disclosure Measure = β0 + Σ βi × INDi + ε

All the regression coefficients are significant at the 0.001 level. The explanatory power of industry is

higher when disclosure is based on word count rather than on the simple count of the items, and is generally

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higher for the voluntary disclosure measures (VDisc_Ct and LVDisc_WC) than for the mandatory disclosure

measures (MDisc_Ct and LMDisc_WC). Industry provides the least explanatory power in terms of

voluntary disclosure when it is measured using VDisc_Sum.

4.2 Correlations

Table 4 presents a series of correlations. Panel A includes correlations among the 8K-based disclosure

measures. Panel B includes correlations between those measures and the four disclosure channels that

comprise VDisc_Sum. Panel C (D) includes correlations between the 8K-based disclosure measures

(disclosure channels) and firm characteristics. Almost all the correlations across the panels are statistically

significant at less than the 0.05 level; insignificant correlations are italicized and indicated by a #.

The correlations in panel A are generally large. 8K_Ct, a proxy used in prior work (e.g., Guay et al.

2016), is highly correlated with VDisc_Ct, VDisc_WC, and VDisc_Sum, and (ρ = 0.732, 0.555, and 0.418,

respectively). 8K_Ct’s correlations with the mandatory disclosure measures are also quite high (ρ = 0.678

with MDisc_Ct and ρ = 0.626 with MDisc_WC). In untabulated analysis, we find 8K_Ct is most highly

correlated with the sum of the voluntary and mandatory disclosure measures: the correlations between

8K_Ct and total disclosure based on the count (word count) is 0.890 (0.658). Not surprisingly, the

correlations between “paired” 8K-based measures (e.g., disclosure measures based on count and on word

count) are high: the correlation between VDisc_Ct and VDisc_WC is 0.802 and between MDisc_Ct and

MDisc_WC is 0.937. In contrast, the correlations between the voluntary and mandatory disclosure measures

are the lowest in this panel: the correlation between VDisc_Ct and MDisc_Ct is 0.271 and between

VDisc_WC and MDisc_WC is 0.269. Finally, we find that VDisc_Sum is more highly correlated with the

voluntary disclosure measures (VDisc_Ct, ρ = 0.629; VDisc_WC, ρ = 0.810) than with the mandatory

disclosure measures (MDisc_Ct, ρ = 0.187; MDisc_WC, ρ = 0.230). These correlations show that each of

the disclosure measures convey similar information, although there is significant variation unique to each.

Panel B reports correlations between the disclosure measures and the four disclosure channel measures

used individually to capture voluntary disclosure in prior studies: MgmtGuide_Ct, ConfCall_Ct,

NonGAAP_Ct, and InvestDay_Ct. We include QMGuide_Ct, which is limited to on quantitative guidance

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and more similar to prior work. These correlations highlight common variation between measures based on

the four disclosure channels and the broader measures. Not surprisingly, each of the individual disclosure

channels is most highly correlated with VDisc_Sum, which is the sum of the disclosure channels. In

addition, each of the individual disclosure channels is more highly correlated with the voluntary disclosure

measures (VDisc_Ct and VDisc_WC) than the mandatory disclosure measures (MDisc_Ct and MDisc_WC).

Finally, we find that correlations with MgmtGuide_Ct are greater than with QMGuide_Ct.

Panel C reports correlations between the disclosure measures and firm characteristics. The number of

observations that the correlations are based on is a function of the data needed to form the proxies for firm

characteristics. Generally, the correlations between the four voluntary disclosure measures and firm

characteristics are stronger than between the mandatory disclosure measures and firm characteristics. All

the disclosure measures are positively (negatively) associated with TAsst, MVE, #Anl, Segm, and PLit (RD

and Comp) consistent with voluntary and mandatory disclosure generally increasing with size, complexity,

and the probability of litigation (decreasing in research and development and competition). In contrast,

FAge and ROA (Loss) are positively (negatively) associated with the voluntary disclosure measures and

negatively (positively) associated with the mandatory disclosure measures. This suggests that firms increase

voluntary disclosure as they become older and more profitable, although concurrent reportable events

become less frequent. They decrease voluntary disclosure and experience more reportable events when they

report losses. The associations between RetVol and Issue are similar to Loss, although 8K_Ct (which is

labeled a voluntary disclosure measure in many studies, although it is highly correlated with total

disclosure) is positively associated with RetVol and Issue. The correlations with BTM are generally small.

The signs of the correlations in Panel D between the disclosure channels and firm characteristics are

generally consistent across the channels and with the voluntary disclosure measures in Panel C. This

suggests similarity among the voluntary disclosure channels. The magnitudes of the correlations vary

substantially, however. For example, the correlation between NonGAAP_Ct and TAsst is 0.455, while the

correlation between QMGuide_Ct and TAsst is 0.296 and between InvestDay_Ct and TAsst is 0.167.

Overall, the findings highlight the usefulness of separating disclosure into its voluntary and mandatory

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aspects, as doing so obtains measures that differ in terms of cross-sectional variation and magnitude.

Furthermore, we document how measures used in prior work (e.g., QMGuide_Ct and NonGAAP_Ct) vary

with each other, with broader voluntary and mandatory disclosure measures, and with firm characteristics.

4.3 Univariate sorts

To further explore the association between firms’ 8K-based disclosures and firm characteristics, we conduct

two related subsample analysis. First, we split the sample into two groups based on data availability issues

that frequently arise in disclosure studies: (1) the availability of management earnings forecast data from

I/B/E/S (8K&MEF = 1 if a firm would be included in a sample based on I/B/E/S management forecast data,

0 otherwise); (2) the availability of I/B/E/S data to calculate #Anl (Ind_#Anl = 1 if #Anl is available, 0

otherwise); (3) whether Compustat reports a value to calculate RD (Ind_RD = 1 if RD is available, 0

otherwise); and (4) whether returns-related inputs to the Kim and Skinner litigation prediction model are

available (Ind_PLit = 1 if all inputs are available, 0 if return-related inputs are missing). Data availability

frequently constrains samples in accounting studies; our analysis provides researchers with a better

understanding of how these constraints are systematically related to our disclosure measures. We also split

the sample based on two firm-specific characteristics—whether a firm reports a loss or it issues equity.

Across these six different subsamples, we report differences in our 8K-based disclosures measures and in

the frequency of the three voluntary 8K items. 2.02_Ct is the count of Item 2.02s and the associated exhibits

within the 8Ks that a firm issues during a calendar quarter. 7.01_Ct and 8.01_Ct are defined similarly.

Panel A of Table 5 presents the results of this subsample analysis. We find that the mean values of the

voluntary and mandatory disclosure measures and of 2.02_Ct, 7.01_Ct, and 8.01_Ct are significantly

different from each other across the subsamples in all but two cases. Within our sample, fewer than a fifth

of the firm quarters have both 8K-based data and I/B/E/S management forecast data (8K&MEF equals 1

for 42,614 out of 239,066 observations). Importantly, the subsample where MEF data is available also is

the set of firm-quarter where all the disclosure measures are higher. The same is true for two of the three

additional subsamples based on data availability: firm-quarters where Ind_#Anl equals 1 and firm-quarters

23

where Ind_PLit equals 1. When we partition the sample based on R&D data (Ind_RD equals 1), however,

some of the disclosure measures are larger in the subsample when R&D data is missing (e.g., average

VDisc_Ct is 3.93 when Ind_RD equals 0 and 3.58 when Ind_RD equals 1), while the opposite is true for

others (MDisc_Ct is 2.86 when Ind_RD equals 0 and 3.13 when Ind_RD equals 1). These findings support

systematic differences in 8K-based disclosures based on data availability, which may result in biased or

even spurious conclusions from studies that are subject to data limitations.

The other two binary variables we include in Panel A are related to whether a firm reports a loss (Loss)

or whether it issues equity (Issue). We find that, for a firm that has reported loss within a year, all four

voluntary disclosure measures (8K_Ct, VDisc_Ct, VDisc_WC, and VDisc_Sum) are smaller than other

firms, while MDisc_Ct and MDisc_WC are statistically larger. Loss firms also provide less disclosure

within each of the voluntary items than other firms. In contrast, for a firm that is going to issue equity (Issue

equals 1), three of the voluntary disclosure measures (VDisc_Ct, VDisc_WC, and VDisc_Sum) are

statistically greater than other firms. The measures of concurrent mandatory disclosure (MDisc_Ct and

MDisc_WC) are statistically smaller. Further, we document that issuing firms provide less (more) disclosure

via Item 2.02 (7.01 and 8.01) than other firms. These are univariate statistics, however, that do not take into

account other firm characteristics that could also affect a firm’s disclosures practices.

Our second subsample analysis explores differences in disclosure measures after independently sorting

the full sample into quintiles based on 11 key firm characteristics: TAsst, MVE, ROA, BTM, #Anl, Segm,

PLit, RD, Comp, FAge, and RetVol. This analysis informs academics, regulators, and users of the 8K

disclosures in terms of how firm characteristics and economic settings are systematically associated with

firm-level disclosure. To perform this analysis, we do the following. First, within each calendar quarter, we

sort observations into quintiles, based on the value of the firm characteristic. Next, across all firm quarters,

we calculate the mean value of each disclosure measure and each voluntary 8K item within each quintile

rank. Panel B of Table 5 presents the values generated by this analysis. Our objective is to examine (1)

whether firms’ 8K-based disclosures are systematically associated with the magnitudes of the firm

24

characteristics, (2) the signs of those associations, and (3) differences in both (1) and (2) across the

alternative disclosure measures. We present the raw values of our sorts in Table 5 Panel B and, in Figures

1- 3, provide a visual representation of that analysis. Our discussion focuses on the figures.

We include three figures, each that includes 11 plots. Figure 1 includes plots of the mean values of

8K_Ct, VDisc_Ct, and MDisc_Ct across the quintile ranks of the 11 firm characteristics, where the

horizontal axis is the rank of the firm attribute (from lowest to highest) and the vertical axis ranges from

zero to six. Figure 2 includes similar lots of the 11 firm characteristics, but reports the values of VDisc_WC

and MDisc_WC. The vertical axis ranges from zero to 20,000 across these 11 plots. Finally, Figure 3

includes similar plots of the 11 firm characteristics, but reports the values of 2.02_Ct, 7.01_Ct, 8.01_Ct,

and VDisc_Sum. For this set of plots, the vertical axis ranges from zero to 3.5. Across each figure, we

discuss two general aspects of the plots. First, is there a discernable linear or non-linear association between

the magnitudes of the firm attribute and of the disclosure measure? Second, is the linear association

increasing or decreasing or is the non-linear association concave or convex?

Across the plots in Figure 1 that document the associations between the magnitudes of the firm

characteristics and the count-based disclosure measures, about half the time the magnitude of the disclosure

measures and the rank of the firm characteristic exhibit a linear relation (TAsst, MVE, #Anl, Segm, FAge,

RetVol). The linear associations between the rank of the firm characteristic and the three included disclosure

measures included are not always consistent, however. For example, the linear relations between TAsst,

MVE, and #Anl and VDisc_Ct (the red dashed lines) are positive, while the linear relations between these

same three firm characteristics and 8K_Ct and MDisc_Ct (the solid blue line and the black dotted lines) are

relatively flat. The linear relations between the rank of Segm and FAge and the three disclosure measures

are relatively flat across all three measures. Finally, the linear relation between RetVol and VDisc_Ct

suggests that voluntary disclosure is decreasing in the quintile rank of RetVol, although the linear relations

with 8K_Ct and MDisc_Ct is again relatively flat.

The remaining five plots in Figure 1 suggest non-linear associations, at least in terms of the relation

25

with VDisc_Ct. The level of VDisc_Ct is initially increasing with the quintile rank of ROA, BTM, and PLit,

peaks, and then decreases. The opposite is true with Comp. Across these four firm characteristics, however,

the levels of 8K_Ct and MDisc_Ct exhibit a more linear relation. Finally, the relation between the rank of

RD and VDisc_Ct is decreasing. Overall, these plots suggest that (1) VDisc_Ct varies more with the rank

of firm characteristics than either 8K_Ct or MDisc_Ct, which are relatively flat across many of the firm

characteristics, and (2) the relation between the rank of the firm characteristics and 8K_Ct and MDisc_Ct

frequently track one another. Therefore, the use of 8K_Ct as a disclosure measure likely captures mandatory

aspects of firms’ 8K disclosures.

Figure 2 presents a set of plots where word count instead of count is used to measure disclosure. The

overall linearity and non-linearity of the relation between the rank of the firm characteristics and VDisc_WC

are similar to the VDisc_Ct plots in Figure 1. In contrast with Figure 1, however, we find that the relation

between the quintile rank of the firm characteristics and VDisc_WC and MDisc_WC is more similar across

the two disclosure measures when word count is used. Further, across all 11 plots, which are based on the

mean values of the word counts by the by the firm characteristics, we see that the word count of mandatory

disclosures exceeds that of voluntary disclosures.

Figure 3 reports the mean values of the count of items and exhibits for each voluntary item (2.02_Ct,

7.01_Ct, and 8.01_Ct) and for VDisc_Sum, calculated within each quintile rank of the firm characteristics.

There are two main takeaways from this set of plots. First, for the three voluntary items and for VDisc_Sum,

the overall increasing or decreasing relations and the linear or nonlinear shape of the plots generally are

consistent with the VDisc_Ct graphs in Figure 1. Second, among the three voluntary items, more Item 2.02s

and exhibits are filed while firms file the fewest Item 7.01s and exhibits. It is worth noting that, for some

firm characteristics, the mean value for 2.02_Ct in the lowest quintile is less than one. As shown in Table

5 Panel B, when we sort 2.02_Ct by the quintile rank of TAsst, we find the mean value of 2.02_Ct is 0.70

in the lowest TAsst quintile (52,158 firm-quarter observations). Similarly, in the lowest MVE quintile

(49,333 firm-quarter observations), the mean value of 2.02_Ct is 0.80. This suggests that smaller firms do

26

not always issue an Item 2.02, consistent with the voluntary nature of this item.

5. Associations and disclosure measure determinants

5.1 Associations

In this section of the study, we provide additional analysis of the properties of the four voluntary disclosure

measures in a setting where voluntary disclosure has been viewed as an important independent variable.

Specifically, we examine the associations between the voluntary disclosure measures and information

asymmetry and the cost of equity capital. We include two common proxies for information asymmetry (bid-

ask spread and the Amihud illiquidity measure) and cost of equity based on a quarterly implied rate of

return. The results of the information asymmetry analysis are presented in Table 6 and of the cost of capital

analysis in Table 7. Since these analyses have differing data requirements, the sample size varies across the

tests. The data requirements, sample size, and descriptions of the various variables used in those analyses

are included in the respective tables.

5.1.1 Disclosure and information asymmetry

We begin by examining the association between the voluntary disclosure measures and two proxies for

information asymmetry: bid-ask spread (Model 1) and Amihud illiquidity (Model 2). Specifically, we

estimate the following models (e.g., Coller and Yohn 1997; Chen, Miao, and Shevlin 2015).

AvgBASi, t+1 = β1 + β2VolMeasurei,t + β3LVolumei,t + β4LPricei,t + β5BTMi,t + β6LTAssti,t + IndFE + YrFE + μi, (1) AmihudIlli, t+1 = β1 + β2VolMeasurei,t + β3LPricei,t + β4BTMi,t + β5LTAssti,t + IndFE + YrFE + μi, (2) where: AvgBAS = the average daily effective bid-ask spread, measured over quarter t+1;

AmihudIll = the Amihud illiquidity measure, measured as the average value of daily returns/daily volume during quarter t+1 (Amihud 2002);

VolMeasure = One of four voluntary disclosure measures—8K_Ct, VDisc_Ct, VDisc_Sum, LVDisc_WC;

LVolume = The log of the average of the daily firm trading volume during quarter t;

LPrice = The log of the average of the daily firm (split adjusted) price during quarter t;

BTM = Book to market ratio—book value of equity divided by market value of equity—Compustat item CEQQ / (PRCCQ x CSHOQ);

LTAsst = The log of total assets at the end of quarter t – Compustat item ATQ.

27

Our first dependent measure is AvgBAS, and the explanatory variable of interest VolMeasure is one of

the four voluntary disclosure measures. We estimate the model with each of the measures separately and

then re-estimate the VDisc_Ct and VDisc_WC models with the related concurrent mandatory disclosure

measure. We include standard control variables drawn from prior studies in the literature: LVolume, LPrice,

BTM, and LTAsst. LVolume is the log of trading volume and controls for the liquidity of firms’ shares,

which can affect inventory-holding costs (Demsetz 1968). LPrice is the log of stock price and controls for

market makers’ processing costs (Stoll 1978). BTM is the firm’s book value of equity scaled by its market

value of equity, and LTAsst is the log of the firm’s total assets. These variables control for firm-specific

characteristics that studies suggest are associated with bid-ask spread. We also include industry fixed effects

based on two-digit SIC codes and year fixed effects to control for unobserved industry and year effects. We

cluster standard errors by firm. Our second measure of information asymmetry is AmihudIll—the Amihud

illiquidity measure, calculated as average daily absolute value of daily return/daily volume over the quarter

(Amihud 2002), where a lower value is considered more liquid. Again, we consider the voluntary disclosure

measures individually and after controlling for mandatory disclosure and include standard control variables

suggested by the literature.24

Table 6 Panel A reports mean correlations across the 48 calendar quarters between the disclosure

measures and bid-ask spread, the Amihud measure, and the control variables. The number in parentheses

is the number of calendar quarters that the correlation is statistically positive/negative. Panel B (C) reports

the results of estimating the AvgBAS (AmihudIll) models. The bid-ask spread (Amihud illiquidity) sample

includes 185,983 (172,588) firm-quarter observations over the sample period.

We document consistently negative correlations between both measures of information asymmetry

and the disclosure measures: firms with higher levels of disclosure have lower bid-ask spreads and greater

24 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.

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liquidity. The average magnitudes of the correlations between the voluntary disclosure measures and

AvgBAS and AmihudIll are greater than with the mandatory disclosure measures. The highest correlations

are with VDisc_Sum (-0.426 and -0.452, respectively). We continue to report positive correlations between

firm size and each of the disclosure measures (as in the Table 4). The signs of the correlations between

BTM and the disclosure measures vary from what was reported in Table 4, although they generally are low.

Panel B presents the results of estimating Model (1). Column (1) reports results when VolMeasure is

8K_Ct. Columns (2) - (4) report results when VDisc_Ct, LVDisc_WC, and VDisc_Sum are included in the

model individually. Finally, columns (5) and (6) report results when VDisc_Ct and LVDisc_WC along with

concurrent mandatory disclosure measures MDisc_Ct and LMDisc_WC are included in the models.25

The results in Table 6 Panel B show that three of the four voluntary disclosure proxies (VDisc_Ct,

LVDisc_WC, and VDisc_Sum) are negatively associated with bid-ask spread, even when we control for

concurrent mandatory disclosure. In contrast, 8K_Ct, a measure earlier studies have used to proxy for

voluntary disclosure, is not statistically significant. While our primary interest is in the voluntary disclosure

proxies, it is interesting to note that higher levels of concurrent mandatory disclosure are associated with

increased bid-ask spreads. Panel C presents the results from estimating the second model, where AmihudIll

proxies for information asymmetry. VolMeasure in columns (1) - (6) in Panel C are consistent with columns

(1) - (6) in Panel B. In this panel, however, we find significantly negative coefficients on all of the disclosure

measures: the four voluntary disclosure measures and the measures of concurrent mandatory disclosure.26

5.1.2 Disclosure and cost of equity

There is a broad literature that explores the link between disclosure and the cost of equity capital, with

much of the focus on the role of voluntary disclosure. Where theoretical and empirical studies conclude

25 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. 26 In untabulated analyses, we also employed 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.

29

that the cost of capital is increasing/decreasing in voluntary disclosure, there continues to be disagreement

in the literature on whether information quality should impact the cost of capital. We remain agnostic, as

our interest is in documenting how our various voluntary disclosure measures (with and without controls

for concurrent mandatory disclosure) are associated with the cost of capital in a multivariate model, rather

than providing empirical evidence in support of a specific relation. Thus, we estimate a model implemented

in prior studies (e.g., Chen et al. 2015), detailed below:

COECi, t+1 = β1 + β2VolMeasurei,t + β3MBetai,t + β4BTMi,t + β5LogMVEi,t + YrFE + μi,t, (3)

where:

COEC = Cost of equity capital estimated quarterly using the price-earnings-to-growth method; VolMeasure = One of four voluntary disclosure measures—8K_Ct, VDisc_Ct, LVDisc_WC, VDisc_Sum;

MBeta = Firm-specific beta, estimated from a rolling regression of firm returns on the value-weighted market index returns over the prior 36 (minimum of 24) months;

BTM = Book-to-market ratio—book value of equity divided by market value of equity—Compustat items CEQQ / (PRCCQ x CSHOQ);

LMVE = Log of the market value of equity at the end of quarter t—Compustat item PRCCQ x CSHOQ.

Following prior research, we include several controls in the analysis: MBeta, the beta coefficient from

a rolling regression of firm returns on market returns over the prior 36 months; BTM, the book-to-market

ratio, computed as book value of common equity scaled by market value of equity; and LMVE, the log of

the market value of equity. Similar to Table 6, we estimate model (3) with each of the voluntary disclosure

measures individually and two of the measures with controls for concurrent mandatory disclosure.

Table 7 Panel A reports mean correlations between the disclosure measures, the cost of equity, and

control variables across the 48 calendar quarters. The values in parentheses are the number of quarters the

correlation is statistically positive/negative. This sample includes 45,996 observations over the 48 quarters.

The cost of equity is consistently negatively correlated with LVDisc_WC (ρ = -0.085, negative in 21 of 48

quarters). All of the disclosure measures are positively correlated with firm size (LMVE). The correlations

between 8K_Ct, LVDisc_WC, and VDisc_Ct and BTM are positive and relatively consistent across quarters

(positive in 16 or 21 of 48 quarters). The correlations between the disclosure measures and MBeta are

generally low and inconsistent.

30

Table 7 Panel B reports results from estimating Model 3. Column (1) presents results when VolMeasure

is 8K_Ct. Columns (2) - (4) report results when VolMeasure is VDisc_Ct, LVDisc_WC, and VDisc_Sum,

respectively. Columns (5) and (6) reports results when VolMeasure is VDisc_Ct and LVDisc_WC and the

controls for concurrent mandatory disclosure (MDisc_Ct and LMDisc_WC) are included. LVDisc_WC is

significantly negative; the coefficients on 8K_Ct and VDisc_Ct are both negative, but insignificant. When

we include concurrent mandatory disclosure, it is positively associated with the cost of capital, although it

is statistically insignificant. In both columns, however, the magnitudes of the negative coefficients on the

voluntary disclosure measures is larger when concurrent mandatory disclosure is included. VDisc_Sum is

positive and statistically insignificant.27

5.2 Disclosure determinants

A number of studies in the disclosure literature explore firm-specific characteristics that predict a firm’s

voluntary disclosures (e.g., Lang and Lundholm 1996; Miller 2002). To enhance our understanding of the

role that firm characteristics play in firm’s 8K-based voluntary disclosure decisions, we follow this prior

literature and estimate a multivariate model that includes a series of firm-specific characteristics and our

voluntary disclosure measures.

5.2.1 Independent variables

We estimate two models: the first is limited to three firm-specific variables beyond the firm characteristics

discussed earlier—a lagged voluntary disclosure measure, a control for mandatory disclosure, and a

quarterly trend variable. The inclusion of a lagged value of the disclosure measure is suggested by the

findings of Graham, Harvey, and Rajgopal (2005). The authors survey CEOs and document that companies

voluntarily disclose to build a reputation for providing timely and reliable information to investors.

Providing stable voluntary disclosures is also consistent with Gibbins, Richardson, and Waterhouse’s

27 In untabulated analysis, we estimate models (1) – (3) when MgmtGuide_Ct, ConfCall_Ct, NonGAAP_Ct, InvestDay_Ct, and QMGuide_Ct were 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.

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(1990) “disclosure position” and “ritualism” constructs. We include a trend variable to control for increases

in disclosure across time (e.g., Guay et al. 2016), as well as year and industry fixed effects.

We also include lagged values of firm-specific characteristics included in our univariate analysis in our

multivariate model. We estimate the following model where each of our voluntary disclosure measures is

included as VolMeasure.

VolMeasurei,t+1 = α +γ1LagVolMeasurei,t +γ2MDisci,t+1 +γ3LTAssti,t +γ4#Anli,t +γ5Ind_#Anli,t +γ6Segmi,t

+γ7FAgei,t +γ8ROAi,t +γ9Lossi,t +γ10BTMi,t +γ11RDi,t +γ12Ind_RDi,t + γ13Compi,t +γ14RetVoli,t +γ15Issuei,t+2 + γ16PLiti,t +γ17Ind_PLiti,t + Trend+IndFE+YrFE+ε (4)

where: VolMeasure = One of the voluntary disclosure measures discussed above;

LagVolMeasure = The lagged value of each voluntary disclosure measures (VolMeasure);

MDisc = Concurrent mandatory disclosure, based on count or word count;

LTAsst = Log of total assets at the end of quarter t—Compustat item ATQ;

#Anl = The number of financial analysts that follow the firm during quarter t; if these data are unavailable through I/B/E/S, we set #Anl equal to zero. 28

Ind_#Anl = One if I/B/E/S data is available and zero otherwise;

Segm = The number of business plus geographic segments during quarter t;

FAge =The number of years that a firm appears on Compustat;

ROA = Return on assets for quarter t—Net income divided by total assets—Compustat item NIQ/ATQ;

Loss = An indicator variable equal to one if a firm reported a loss in any of the four quarters prior to quarter t+1 and zero otherwise;

BTM = Book to market ratio—book value of equity divided by market value of equity at the end of quarter t (Compustat item CEQQ/(PRCCQ x CSHOQ);

RD = Research and development expense at quarter t (Compustat item XRDQ), scaled by TAsst. If XRDQ is missing in Compustat, we set RD equal to zero;

Ind_RD = One if Compustat data item XRDQ is available and zero otherwise;

Comp = Competition is measured using the Herfindahl index, which is calculated as the sum of the squares of the market shares of the firms with an industry. An industry is defined as all firms reported on Compustat sharing the same 4-digit SIC code;

RetVol = Standard deviation of a firm’s monthly returns over the past 12 months;

Issue = An indicator variable equal to one if the number of shares outstanding, adjusted for stock dividends/splits, increases by more than 10 percent from quarter t+1 to quarter t+2;

PLit = The ex-ante probability of litigation, based on Table 7, model 3, Kim and Skinner (2012);

Ind_PLit = One if PLit is calculated using the full Kim and Skinner (2012) model (above), zero if data to form the returns-based independent variables for the Kim and Skinner model are unavailable, so PLit is based on Compustat data only;

Trend = A time-trend variable that equals the number of quarters elapsed since the beginning of the sample period.

28 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 in Khanna, Kim, and Lu (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.

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5.2.2 Results

We present the results of this analysis in Table 8. Panel A includes the results from estimating the model

where we limit the independent variables to LagVolMeasure, MDisc, and Trend. Panels B present results

based on the full model. When the dependent measure is one of three voluntary disclosure measures based

on detailed data from the voluntary 8K items, we present results with and without controlling for concurrent

mandatory disclosure.

Panel A reports significant and economically meaningful positive coefficients on the lagged values of

each of the disclosure measures. This suggests that a firm’s 8K-based voluntary disclosures are sticky across

time and that predicting future such voluntary disclosures starts with its historical decisions. We also

document significant coefficients on the trend variable, although the sign of that coefficient in the 8K_Ct

model is negative, while it is positive in the other models. This suggests that the number of 8K filings are

decreasing across time, while there is a general increase in detailed voluntary disclosures via those 8Ks.

We also document a positive association between concurrent mandatory disclosure and voluntary

disclosure, although including it in the models has a limited impact on the explanatory power and does not

change the tenor of the other associations.

Table 8 Panel B reports the results of estimating the full model; the expanded model includes lagged

values of firm characteristics drawn from the disclosure literature. A couple of general comments. First, the

addition of the firm characteristics increases the explanatory power of the models, although the increases

are modest. For example, the adjusted R2 of the LVDisc_WC model that excludes MDisc in Panel A is

0.489. Including the additional variables increases the adjusted R2 to 0.519, a change of about 6 percent.

Second, we continue to document the important role prior voluntary disclosure, concurrent mandatory

disclosure, industry, and time trends play in the level of future voluntary disclosure.

When we examine the link between the “structural” firm characteristics (LTAsst, #Anl, Ind_#Anl, Segm,

FAge) and voluntary disclosure, we find the following. First, each of the voluntary disclosure measures is

increasing with firm size measured as LTAsst. In contrast, #Anl has a significantly negative coefficient,

33

suggesting higher analysts’ following leads to lower voluntary disclosure. The indicator variable for when

we have I/B/E/S data to calculate #Anl (Ind_#Anl) is significantly positive when voluntary disclosure is

measured using word count or the number of disclosure channels. Even after controlling for size (which is

positively correlated with whether a firm is followed or not), we find that being followed by analysts is

associated with higher levels of the word count of voluntary disclosures and the use of voluntary disclosure

channels in the future period. Finally, we find no evidence that complexity (Segm) is related to voluntary

disclosures, although older firms provide significantly less voluntary disclosure across our models.

When we look to the link between performance-related firm characteristics and the voluntary disclosure

measures, we find the following. First, the firms’ prior quarter profitability (ROA) is negatively (positively)

associated with future voluntary disclosure measured with 8K_Ct and VDisc_Ct (VDisc_Sum), although the

coefficient on ROA is not significant in the VDisc_Ct model when concurrent mandatory disclosure is

included and is only significant in the VDisc_Sum model when concurrent mandatory disclosure is included.

Second, firms that report losses provide higher levels of voluntary disclosure, except when voluntary

disclosure is measured using VDisc_Ct and we control for concurrent mandatory disclosure. In that case,

losses are associated with lower future disclosure. We document significant negative coefficients across all

models on BTM and Comp, consistent with firms with lower growth potential and that face more

competition reducing their levels of voluntary disclosure. In most models, voluntary disclosure is increasing

in the level of research and development expenditures (the coefficient on RD is positive in all the models,

but insignificant when word count is used to measure disclosure and when the sum of the disclosure

channels is used and we control for concurrent mandatory disclosure).

We also find that, in the period prior to when a firm issues equity, the level of voluntary disclosure

generally is higher (Issue is positive in all models, but insignificant when LVDisc_WC or VDisc_Sum is the

dependent measure and concurrent mandatory disclosure is included.) Finally, firm quarters with a higher

probability of litigation generally lead to lower levels of voluntary disclosure. The opposite is true, when

8K_Ct is the dependent measure.

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In sum, our voluntary disclosure measures are sticky across time and are increasing in the level of

concurrent mandatory disclosure. Larger firms and firms with fewer analysts provide more voluntary

disclosure. Firms that that report losses in the past or issue equity in the future tend to provide more

voluntary disclosure; the general level of voluntary disclosure is increasing across time. These findings

support the link between voluntary disclosure and a number of firm characteristics, although how that

disclosure is measured and whether concurrent mandatory disclosure is included in the model affects the

associations. Finally, it is important to recall that some of the disclosure measures and the firm

characteristics exhibit non-linear univariate relations, which could affect the results of our linear model.

6. Additional analyses

Our final analysis seeks to increase our understanding of the information reported within the five most

frequently reported 8K items (the three voluntary 8K items—Items 2.02, 7.01, and 8.01 and two mandatory

8K items—Items 1.01 and 5.02). We begin by documenting the persistence of voluntary and mandatory

disclosure measures and the specific 8K items that are used to generate those measures. We also explore

the persistence of the four voluntary disclosure channels and of the disclosure channels reported within a

specific voluntary 8K item number. This analysis is motivated in part by the findings from Table 8 of the

significant role that lagged voluntary disclosure plays in predicting future disclosure. We also present

preliminary evidence of specific topics reported within the voluntary 8K items, especially information

reported within 8K Items 7.01 and 8.01. Our earlier analysis documents the presence of the four disclosure

channels in each of voluntary 8K items. We supplement these findings by documenting the content of the

voluntary 8K items beyond the four disclosure channels.

6.1 Persistence

Table 9 reports the persistence of the voluntary and mandatory disclosure measures, the primary 8K items,

and the four disclosure channels. Studies in the voluntary disclosure literature frequently refer to two types

of voluntary disclosures (e.g., Lang and Lundholm 2000; Leuz and Verrecchia 2000; Cadman et al. 2019;

Ellahie et al. 2019): disclosures that signal a commitment to disclosure and disclosures that are made

35

conditional on the firm’s operating environment or strategic voluntary disclosures. Understanding the

relative persistence of disclosures adds to our understanding of how various proxies for voluntary disclosure

align with the commitment versus strategic sorting.

Panel A presents the persistence of the voluntary and mandatory 8K disclosure measures examined in

the study, the three voluntary 8K items, and the two primary mandatory 8K items used to construct those

measures. Panel B presents persistence of the disclosure channels used to construct VDisc_Sum and Panel

C presents the persistence of the voluntary disclosure channels, conditional on the voluntary 8K items

within which they are reported.

In general, the results in Panel A show that the disclosure measures that are based on the count of items

and exhibits are more persistent than the disclosure measures based on a word count. Further, q-1

disclosures are more persistent than q-4 disclosures and voluntary disclosures are more persistent than

mandatory disclosures.29 Since mandatory disclosures are based on events over which firms have limited

control, while voluntary disclosures are based a firms’ decisions, this is not surprising. When we compare

the persistence of the disclosure measures based on counts, we find that the persistence of 8K_Ct, the

measure drawn from the literature, is more persistent than MDisc_Ct but less so than VDisc_Ct. The

persistence of the three voluntary 8K items that are combined to construct VDisc_Ct and VDisc_WC are

significantly different from each other. Specifically, the count and word count of 2.02s are more persistent

than the count or word count of either 7.01s or 8.01s. When we look to the word counts, this is particularly

evident. We also note that the q-1 persistence of the count of items and exhibits for 2.02s is not statistically

different than the q-4 persistence. These findings are consistent with earnings announcements reflecting a

firm’s commitment to disclosure (e.g., Cadman et al. 2019), relative to other voluntary items. In contrast,

we find that the persistence of 7.01s and 8.01s suggest that firms do not consistently provide voluntary

disclosures via these 8K items.

29 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_WC is 0.133 (0.134).

36

Panel B presents the persistence of the disclosures via the four disclosure channels that are summed to

construct VDisc_Sum and VDisc_Sum, the sum of the four channels. VDisc_Sum is highly persistent (0.712

and 0.697 for q-1 and q-4), as is each of the four channels. Reports of non-GAAP measures and conference

calls are the most persistent. The persistence of quantitative management guidance (QMGuide_Ct) appears

lower than the persistence of total management guidance (MgmtGuide_Ct).

In Panel C, we report the persistence of each of the four disclosure channels, within a given voluntary

8K item. These findings show that the persistence of the four disclosure channels varies with the voluntary

8K item where it is reported. For example, the persistence (q-1) of the voluntary channels within item 2.02

varies from a low of 0.581 (QMGuide_Ct) to a high of 0.809 (NonGAAP_Ct). When those same disclosure

channels are reported via item 7.01, they are significantly less persistent (0.470 for QMGuide_Ct and 0548

for NonGAAP_Ct). Within item 8.01 the persistence of QMGuide_Ct is 0.125 and of NonGAAP_Ct is 0.192.

We document that the persistence of each of the disclosure channels is highest when reported within Item

2.02 and lowest when reported in Item 8.01. This holds for the all the measures examined in this panel and

for both q-1 results and q-4 results.

The findings support the view that there is considerable variance in voluntary disclosure and voluntary

8K items. Item 2.02s are more persistent than 7.01s or 8.01s, which would support the use of 2.02s to

identify commitment to voluntary disclosure and 7.01s or 8.01s to identify strategic disclosure. An

important takeaway is that relying on the four voluntary disclosure channels commonly employed in the

literature to capture either commitment to disclosure or strategic disclosures would be enriched by including

the 8K item where the disclosure is reported.

6.2 Content in voluntary 8K items

We performed a keyword search of the three voluntary 8K items and associated exhibits and collected the

frequency with which firms reported nine additional special topics of interest to researchers, academics,

and researchers. To identify and select these topics, we read all the 8Ks for a random sample of (1) 20 firms

across the entire sample period and (2) 300 additional 8Ks that included Item 7.01 or 8.01. From this, we

37

identified the five most frequently discussed topics: business combinations, dividend announcements,

litigation, restructuring, and security offerings. We also included topics drawn from the literature (i.e.,

conference presentations (Gleason et al. 2019), patents (Plumlee, Xie, Yan, and Yu 2015), shareholder

repurchases (Brochet, Ferri, and Miller 2018), and shareholder agreements (Schoenfeld 2019)). The results

of the keyword search are used to provide evidence of the content of 8K-based voluntary disclosures.

Appendix 4 provides the results of the keyword search. Panel A details the search terms used to identify

the nine additional topics and Panel B provides descriptive analysis of the results of the searches. We report

two proportions in Panel B. The first proportion is relative to the total number of observations by the item

numbers (%All, %2.02, %7.01, %8.01) and the second proportion is relative to the variable (%Var). We

detail the frequency with which specific topics are reported in all three voluntary 8K items, with an

additional focus on the topics reported in Items 7.01 and 8.01. The two topics most frequently reported in

Items 7.01 and 8.01 are business combinations (BusCom is identified in 34.0 (27.6) percent of 7.01s (8.01s))

and litigation (Lit is identified in 29.8 (27.2) percent of 7.01s (8.01s)). Information about dividends (Div),

restructurings (Res), and security offerings (SecOff) is frequently identified in Item 7.01—17.2, 16.3, and

15.1 percent of the time. Information about dividends and security offerings also is frequently identified in

Item 8.01—17.1 and 21.0 percent of 8.01s. No_ST (which is one if none of the nine topics are identified,

zero otherwise) is one in 18.2 percent of 7.01s and 19.8 percent of 8.01s. No_ALL (which is one if none of

the nine topics or the four disclosure channels are identified, zero otherwise) is one for 3.3 percent of 2.02s,

13.3 percent of 7.01s, and 17.4 percent of 8.01s.

7. Conclusion

There is a broad literature that seeks to understand the role of firm-level disclosures in a variety of academic

settings. Providing empirical evidence about these issues requires researchers to obtain a measure of firm-

level voluntary disclosure to use in the analysis. We construct six measures of disclosure—four voluntary

and two concurrent mandatory—based on firms’ 8K filings and document some basic properties of these

disclosure measures. We also assess links between the disclosure measures and various firm characteristics

38

common to the disclosure literature. Our findings should prove useful to researchers and others as they

explore options for measuring disclosure in their research setting.

This study also provides information around two other issues that arise in constructing firm-specific

voluntary disclosure measures. First, we construct measures of concurrent mandatory disclosure, a potential

correlated omitted variable in many settings. Using our measures, we document a positive association

between voluntary and concurrent mandatory disclosure, although controlling for mandatory disclosure has

limited effect on our results. Second, our method of calculating voluntary disclosure incorporates a broad

range of information and can be employed for the population of firms are required to file with the SEC.

This process can be replicated, which means the voluntary and concurrent mandatory disclosure measures

can be extended across time.

In addition, this study provides empirical evidence of the persistence of the primary 8K items filed by

firms, of the voluntary disclosure channels, and of the voluntary disclosure channels conditional on the

voluntary 8K item they are reported in. This increases our understanding of firm voluntary disclosures in

general, as well as providing support for the use of specific 8K voluntary items to capture commitment to

disclosure while using others to capture strategic disclosure. We also provide preliminary evidence of the

content of the information reported within the voluntary 8K items, both in terms of the voluntary disclosure

channels and in terms of specific topics.

While admittedly exploratory, our results are likely to be of interest to researchers. There is clearly

room for additional research, however, focusing on specific aspects of the 8K filings and developing more

refined measures. Our conclusions are also subject to important caveats. The construction of our measures

is limited to self-reported information within 8Ks. If firms strategically determine what information to

include in the filings or which 8K item number to use in reporting that information, this could affect the

link between our measures and a firm’s “true” voluntary and mandatory disclosures.

39

Appendix 1 Variable definitions

Variable Brief definition

Disclosure measures

8K_Ct The number of 8Ks a firm files during a calendar quarter.

VDisc_Ct The count of the voluntary items (#s 2.02, 7.01, and 8.01) and associated exhibits reported

within the 8Ks a firm files during a calendar quarter.

VDisc_WC The word count of the voluntary items (#s 2.02, 7.01, and 8.01) and associated exhibits

reported within the 8Ks a firm files during a calendar quarter. LVDisc_WC is the natural

log of this value.

VDisc_Sum The sum of MgmtGuide_Ct, ConfCall_Ct, NonGAAP_Ct, and InvestDay_Ct for a firm

within a calendar quarter.

MDisc_Ct The count of the mandatory items (all item #s other than 2.02, 7.01, and 8.01) and

associated exhibits reported within the 8Ks a firm files during a calendar quarter.

MDisc_WC The word count of mandatory 8K items (all item #s other than 2.02, 7.01, and 8.01) and

associated exhibits reported within the 8Ks a firm files during a calendar quarter.

LMDisc_WC is the natural log of this value.

MgmtGuide_Ct An indicator variable that equals one if a keyword search identifies a minimum of one

management guidance search term within an item or its related exhibits, zero otherwise.

This analysis is performed for voluntary item numbers only.

ConfCall_Ct An indicator variable that equals one if a keyword search identifies a minimum of one

conference call search term within an item or its related exhibits, zero otherwise. This

analysis is performed for voluntary item numbers only.

NonGAAP_Ct An indicator variable that equals one if a keyword search identifies a minimum of one Non-

GAAP search term within an item or its related exhibits, zero otherwise. This analysis is

performed for voluntary item numbers only.

InvestDay_Ct An indicator variable that equals one if a keyword search identifies a minimum of one

Investor Day search term within an item or its related exhibits, zero otherwise. This

analysis is performed for voluntary item numbers only.

QMGuide_Ct An indicator variable that equals one if a keyword search identifies a minimum of one

quantitative management guide search term within an item or its related exhibits, zero

otherwise. This analysis is performed for voluntary item numbers only.

Firm characteristics and other variables

TAsst Total assets at the end of quarter t (Compustat item ATQ). LTAsst is the natural log of this

value.

MVE The market value of equity at the end of the quarter t (Compustat item PRCCQ x CSHOQ).

LMVE is the natural log of this value.

#Anl The number of analysts that follow the firm during quarter t from I/B/E/S. If the data is

missing from I/B/E/S, #Anl is set to zero.

Ind_#Anl An indicator variable that equals one if I/B/E/S data to calculate #Anl is available, and zero

otherwise.

Segm The number of business segments plus geographic segments during quarter t. FAge The number of years that a firm appears on Compustat.

ROA Return on assets for quarter t – Net income divided by total assets (Compustat item

NIQ/ATQ).

Loss An indicator variable that equals one if a firm reported a loss in any of the four quarters

prior to quarter t+1, and zero otherwise.

BTM Book to market ratio – book value of equity divided by market value of equity (Compustat

item CEQQ / (PRCCQ x CSHOQ)).

40

RD Research and development expense at quarter t (Compustat item XRDQ), scaled by total

assets. If the variable is missing from Compustat, RD is set to zero.

Ind_RD An indicator variable that equals one when Compustat data item XRDQ is available, and

zero if the item is missing.

Comp Competition, measured using the Herfindahl index. Calculated as the sum of the squares

of the market shares of the firms within an industry. An industry is defined as all firms

reported on Compustat sharing the same 4-digit SIC code.

RetVol Standard deviation of a firm’s monthly returns over the past 12 months.

Issue An indicator variable that equals one if the number of shares outstanding, adjusted for stock

dividends/splits, increases by more than 10 percent from quarter t+1 to quarter t+2, and

zero otherwise

PLit The ex-ante probability of litigation, based on model 3 in Table 7 from Kim and Skinner

(2012).

Ind_PLit An indicator variable that equals one if we have non-missing data for all inputs in the Kim

and Skinner model and zero if we are limited to Compustat data, but are missing returns-

related data.

Trend A time-trend variable that is equal to the number of quarters elapsed since the beginning

of the sample period (e.g., it equals one for the first quarter of 2005 and two for the second

quarter of 2005, etc.).

AvgBAS The average daily quoted bid-ask spread over quarter t+1. Daily quoted bid-ask spread is

calculated as the average of all bid-ask spreads, 0.5 × (Ask-Bid) / (Ask+bid). The quote data

are from TAQ.

AmihudIll The average of the daily Amihud measure, calculated as the absolute value of daily returns

scaled by the daily trading volume, over a quarter t+1. A lower value of this measure

indicates greater liquidity.

LPrice The natural log of the average of the daily firm, split-adjusted price over quarter t.

LVolume The natural log of the average of the daily firm trading volume over quarter t.

COEC Cost of equity capital is estimated using the Price-Earnings-to-Growth method following

Easton (2004) and Ellahie et al. (2019). Et(F12i) is the 12-month-ahead I/B/E/S analyst

earnings forecast for firm i at quarter t, calculated by time-weighting the one-year-ahead

and two-year-ahead consensus annual earnings forecasts. The weights are based on the

number of days between the earnings forecast date and the fiscal period end data for the

firm’s one-year-ahead forecast, divided by 365 days. Et(LTFi) is the long-term earnings

forecast estimated from the median long-term growth forecast from I/B/E/S.

MBeta Firm-specific beta, estimated from a rolling regression of firm returns on the value-

weighted market index returns over the prior 36 months (minimum 24 months).

41

Appendix 2 Data processing procedures and keyword search strings

Panel A: Steps to process data and construct disclosure measures

Item numbers classified as voluntary (Items 2.02, 7.01, 8.01)

and exhibits traced to voluntary items.

Sum the number or word count of items from 8Ks filed within the

period (e.g. quarterly) to create Ct_ManItem or WC_ManItem. (To

calculate word count, we eliminate HTML tags, space, comma,

periods, etc. and count only the number of words. Numbers and

words/numbers within tables are also included in our count.) Sum

the number or word count of exhibits from 8Ks filed within the

period (e.g. quarterly) to create Ct_ManEX or WC_ManEX. These

values are used as inputs to construct measures of mandatory

disclosure. *

Two Measures of Concurrent Mandatory Disclosure:

MDisc_Ct = Ct_ManItem + Ct_ManEX

MDisc_WC = WC_ManItem +WC_ManEX

Sum the number or word count of items from 8Ks filed within

the period (e.g. quarterly) to create Ct_VolItem or WC_VolItem.

(To calculate word count, we eliminate HTML tags, space,

comma, periods, etc. and count only the number of words.

Numbers and words/numbers within tables are also included in

our count.) Sum the number or word count of exhibits from 8Ks

filed within the period (e.g. quarterly) to create Ct_VolEX or

WC_VolEX. These values are used as inputs to construct

measures of voluntary disclosure.

Two Measures of Voluntary Disclosure:

VDisc_Ct = Ct_VolItem + Ct_VolEX

VDisc_WC = WC_VolItem +WC_VolEX

Download 8K filings from EDGAR, including attached exhibits.

Eliminate JPG, GIF, and other image files.

Identify all item and exhibits.

Collect:

1. The item numbers and the word count for each item.

2. The exhibit numbers and the word count for each exhibit.

Match:

The exhibits (exhibit numbers) to the associated item (item numbers).

Item numbers classified as mandatory (other than Items 2.02,

7.01, and 8.01) and exhibits traced to mandatory items.

42

Panel B: Voluntary disclosure channels--Keyword search strings

Measure

Acronym

Keyword search string

Management

guidance

MgmtGuide_Ct

Forecast, guidance, outlook, expectation, expectations, expect, project, estimate, guide, anticipate, expected, anticipated,

projected, projects, forecasts, expects, anticipates, estimates, forecasting, anticipating, projecting, expecting, forecasted,

projected) within ten words of (earnings, profit, profitability, loss, income, sales, EBITDA, revenue, revenues, cash flow,

EPS, earnings per share, margin, SG&A, capital expenditures, cost, costs, price, prices). We also require the two-word

groups appear in the same sentence.30

Quantitative guidance

QMGuide _Ct

Management guidance with a $ or % or “percent” within the sentence

Conference calls

ConfCall_Ct

Conference call or earnings call

Non-GAAP measures

NonGAAP_Ct

Pro forma, pro-forma, proforma, earnings excluding, net income excluding, cash earnings, free cash flow, normalized EPS,

normalized earnings, recurring earnings, distributable cash flow, GAAP one-time adjusted, GAAP adjusted, cash loss,

earnings (loss) excluding, earnings per share excluding, operating margin excluding, non-GAAP earnings, non-GAAP net

income, non-GAAP revenue, non-GAAP gross margin, non-GAAP operating margin, Non-U.S. GAAP measures, non-

GAAP financial, non-GAAP reconciliation, non-GAAP reconciliations, non-GAAP measures, non-GAAP measurement,

or non-GAAP measurements

Investor day

InvestDay_Ct

Investor day, investor conference*, investor conferences, investor presentation, analyst conference*, meetings with

analysts, meetings with investors, investor meeting, analyst meeting, presentations to institutional investors, or presentations

to investors

This table presents the steps to process data and construct disclosure measures (Panel A) and details of the keyword search strings for voluntary disclosure channels (Panels B). The keyword search is performed on voluntary 8K items (items 2.02, 7.01, and 8.01) and the matched exhibits. *To ensure what we capture is “investor day” rather than “conference call”, we add additional constraint in this search process to exclude “investor conference” and “analyst conference” with “call (s)” immediately afterwards.

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

43

Appendix 3 Variable names and descriptive statistics for disclosure measure components

Panel A: Variable names

Ct_VolItem The number of voluntary items within the 8Ks a firm files during a calendar quarter. Items 2.02 (Results of Operations and Financial

Condition), 7.01 (Regulation FD Disclosure), and 8.01 (Other Events) are classified as voluntary (Lerman and Livnat 2010).

Ct_VolEX The number of exhibits matched with voluntary items within the 8Ks a firm files during a calendar quarter.

WC_VolItem The word count of voluntary items within the 8Ks a firm files during a calendar quarter.

WC_VolEX The word count of exhibits matched with voluntary items within the 8Ks a firm files during a calendar quarter.

Ct_ManItem The number of mandatory items within the 8Ks a firm files during a calendar quarter.

Ct_ManEX The number of exhibits matched with mandatory items within the 8Ks a firm files during a calendar quarter.

WC_ManItem The word count of mandatory items within the 8Ks a firm files during a calendar quarter.

WC_ManEX The word count of exhibits matched with mandatory items within the 8Ks a firm files during calendar quarter.

Panel B: Descriptive statistics

Variable Mean Std. Dev. 25th Median 75th

Ct_VolItem 2.03 1.96 1.00 2.00 3.00

Ct_VolEX 1.75 2.35 0.00 1.00 2.00

Ct_ManItem 1.74 2.27 0.00 1.00 3.00

Ct_ManEX 1.23 2.66 0.00 0.00 2.00

WC_VolItem 374 1,188 46 144 367

WC_VolEX 4,684 15,674 0.00 2,194 4,386

WC_ManItem 610 1,319 0.00 269 763

WC_ManEX 10,504 30,973 0.00 0.00 4,985

This table details variable names (Panel A) and reports summary statistics (Panel B) for the elements used to construct the 8K-based disclosure measures. The sample includes 260,880 firm-quarters—the intersection of the 8K data and Compustat.

44

Appendix 4 Specific topics disclosed in voluntary 8K items and exhibits

Panel A: Specific topics keyword search strings

Topic Keyword search string Acronym

Business combinations Merger, acquisition, joint venture BusCom

Conference presentations Presentation materials, participated and presentation or transcript within 5 words of

each other ConfP

Dividend announcements Dividend or stock split Div

Litigation Litigation, lawsuit, subpoena, patent infringement, or filed and suit within 5 words of

each other Lit

Patents Patent Patent

Restructuring Restructuring, divestiture, impairment, spinoff Res

Security offerings Registered public offering, registration statement, debt offering, private placement,

secondary offering, underwriting, or underwritten SecOff

Share repurchases Share repurchase, stock repurchase, share buyback, stock buyback, share buy-back, or

stock buy-back ShRep

Shareholder agreements Investor agreement, investment agreement, cooperation agreement, investor rights,

exchange agreement, support agreement, stockholder agreement, shareholder

agreement, or settlement agreement

ShAgree

45

Panel B: Distribution of specific topics identified in Items 2.02, 7.01, and 8.01 and related exhibits

All voluntary items Within Item 2.02 Within Item 7.01 Within Item 8.01

Variable N. Obs. %All N. Obs. %Variable %2.02 N. Obs. %Variable %7.01 N. Obs. %Variable %8.01

(1) BusCom 219,386 41.4 123,960 56.5 57.5 46,142 21.0 34.0 49,284 22.5 27.6

(2) ConfP 8,810 1.7 2,829 32.1 1.3 5,396 61.2 4.0 585 6.6 0.3

(3) Div 143,004 27.0 89,177 62.4 41.4 23,386 16.4 17.2 30,441 21.3 17.1

(4) Lit 216,118 40.8 127,079 58.8 58.9 40,430 18.7 29.8 48,609 22.5 27.2

(5) Patent 35,432 6.7 17,055 48.1 7.9 6,825 19.3 5.0 11,552 32.6 6.5

(6) Res 135,565 25.6 98,050 72.4 45.5 22,055 16.3 16.3 15,260 11.3 8.6

(7) SecOff 93,626 17.7 35,671 38.1 16.5 20,447 21.8 15.1 37,508 40.1 21.0

(8) ShRep 45,775 8.6 30,430 66.5 14.1 6,926 15.1 5.1 8,419 18.4 4.7

(9) ShAgree 10,968 2.1 4,467 40.7 2.1 2,329 21.2 1.7 4,172 38.0 2.3

(10) No_ST 76,531 14.4 16,558 21.6 7.7 24,646 32.2 18.2 35,327 46.2 19.8

No_All 56,264 10.6 7,199 12.8 3.3 18,002 32.0 13.3 31,063 55.2 17.4

TVDisc Items 529,710 215,616 135,626 178,468 This table presents the keyword search strings and descriptive statistics of indicator variables related to nine additional specific topics. The keyword search is performed on the three

voluntary 8K items (items 2.02, 7.01, and 8.01) and the matched exhibits filed by firms from 2005 through 2016. Panel A presents the details of the keyword search strings of the

nine additional specific topics. If the keyword search string identifies the specific topic, the relevant acronym is coded one for that item number. If not, it is coded zero. Panel B

presents descriptive statistics related to the nine additional specific topics where No_ST is defined as one if none of the nine topics are identified, zero otherwise. No_ALL is defined

as one if none of the nine topics or four disclosure channels are identified, zero otherwise. %Variable is the number of observations scaled by the total number of observations of

each variable. % All (% 2.02, %7.01, % 8.01) is the number of observations scaled by the total number of voluntary 8K items (2.02s, 7.01s, 8.01s) filed during the sample period.

46

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50

Table 1 Descriptive statistics - Detailed 8K items and exhibits

Panel A: Distribution of 8K items

Item # Description Count % Items % 8Ks1 1.01 Entry into a Material Definitive Agreement 132,594 13.5 18.3

1.02 Termination of a Material Definitive Agreement 11,847 1.2 1.6

1.03 Bankruptcy or Receivership 584 0.1 0.1

1.04 Mine Safety – Reporting of Shutdowns and Patterns of Violations 161 0.0 0.0

2.01 Completion of Acquisition or Disposition of Assets 15,035 1.5 2.1

2.02 Results of Operations and Financial Condition 215,616 21.9 29.7

2.03 Creation of a Direct Financial Obligation or an Obligation under an Off-Balance Sheet Arrangement of a Registrant 35,590 3.6 4.9

2.04 Triggering Events That Accelerate or Increase a Direct Financial Obligation under Off-Balance Sheet Arrangement 1,900 0.2 0.3

2.05 Cost Associated with Exit or Disposal Activities 4,544 0.5 0.6

2.06 Material Impairments 2,435 0.2 0.3

3.01 Notice of Delisting or Failure to Satisfy a Continued Listing Rule or Standard; Transfer of Listing 9,067 0.9 1.2

3.02 Unregistered Sales of Equity Securities 24,164 2.4 3.3

3.03 Material Modifications to Rights of Security Holders 7,254 0.7 1.0

4.01 Changes in Registrant’s Certifying Accountant 7,245 0.7 1.0

4.02 Non-reliance on Previously Issued Financial Statements or a related audit report or completed interim review 3,594 0.4 0.5

5.01 Changes in Control of Registrant 2,343 0.2 0.3

5.02 Departure of Directors or Principal Officer; Election of Directors; Appointment of Principal Officers 135,790 13.8 18.7

5.03 Amendments to Articles of Incorporation or Bylaws; Change in Fiscal Year 24,070 2.4 3.3

5.04 Temporary Suspension of Trading Under Registrant’s Employee Benefit Plans 965 0.1 0.1

5.05 Amendments to the Registrant’s Code of Ethics, or Waiver of a Provision of the Code of Ethics 1,597 0.2 0.2

5.06 Change in Shell Company Status 553 0.1 0.1

5.07 Submission of Matters to a Vote of Security Holders 30,019 3.0 4.1

5.08 Shareholder Director Nominations 275 0.0 0.0

6.01 ABS Informational and Computational Material 51 0.0 0.0

6.02 Changes of Servicer or Trustee 54 0.0 0.0

6.03 Change in Credit Enhancement or Other External Support 55 0.0 0.0

6.04 Failure to Make a Required Distribution 52 0.0 0.0

6.05 Securities Act Updating Disclosure 51 0.0 0.0

7.01 Regulation FD Disclosure 135,626 13.8 18.7

8.01 Other Events 178,468 18.1 24.6

9.01 Financial Statements and Exhibits (stand-alone) 3,190 0.3 0.4

Total Items – 1.01 through 8.01, and stand-alone 9.01s 984,789 100.0

9.01 Financial Statements and Exhibits (filed within an 8K with an additional item) 560,316

51

Panel B: Distribution of 8K financial statements and exhibits filed within an item 9.01

EX # Description of Exhibit Assoc. Item #s Count % EX

1. Underwriting agreement 1.01 13,186 1.7

2. Plan of acquisition, reorganization, arrangement, liquidation, or succession 1.01; 2.01 12,473 1.6

3. Articles of incorporation; Bylaws 5.03; 5.07 23,681 3.1

4. Instruments defining the rights of security holders, including indentures 1.01; 3.03 31,679 4.1

5. Opinion re: legality 9.01 11,043 1.4

7. Correspondence from an independent accountant regarding non-reliance on a previously issued

audit report or completed interim review

4.02 88 0.0

8. Opinion re tax matters 9.01 2,883 0.4

9. Voting trust agreement 266 0.0

10. Material contracts 1.01; 2.03; 3.02; 5.02; 5.07 169,183 22.2

11. Statement re computation of per share earnings 9 0.0

12. Statement re computation of ratios 9.01 1,127 0.1

13. Annual report to security holders, Form 10-Q or quarterly report to security holders 9 0.0

14. Code of ethics 5.05 838 0.1

15. Letter re unaudited interim financial information 32 0.0

16. Letter re: change in certifying accountant 4.01 5,002 0.7

17. Correspondence on departure of director 5.02 703 0.1

19. Report furnished to security holders 2 0.0

20. Other documents or statements to security holders 7.01; 8.01 184 0.0

21. Subsidiaries of the registrant 9.01 29 0.0

22. Published report regarding matters submitted to vote of security holders 9.01 9 0.0

23. Consents of experts and counsel 3,304 0.4

24. Power of attorney 8.01 12 0.0

25. Statement of eligibility of trustee 9.01 104 0.0

31. Rule 13a-14(a)/15d-14(a) Certifications 109 0.0

32. Section 1350 Certifications 41 0.0

33. Report on assessment of compliance with servicing criteria for asset-backed issuers 4 0.0

35. Servicer compliance statement 11 0.0

95. Mine safety disclosure exhibit 3 0.0

99. Additional exhibits 486,960 63.8

Total 762,974 100.0

52

Panel C: Distribution of exhibit # 99 across item numbers

Item # Description of items associated with exhibit #99 Count % EX. 99

1.01 Entry into a material definitive agreement 19,381 4.0

1.02 Termination of a Material Definitive Agreement 644 0.1

1.03 Bankruptcy or Receivership 168 0.0

2.01 Completion of Acquisition or Disposition of Assets 3,790 0.8

2.02 Results of Operations and Financial Condition 204,843 42.1

2.03 Creation of a Direct Financial Obligation/Obligation under an Off-Balance Sheet Arrangement of a Registrant 1,027 0.2

2.04 Triggering Events That Accelerate or Increase a Direct Financial Obligation under Off-Balance Sheet Arrangement 210 0.0

2.05 Cost Associated with Exit or Disposal Activities 934 0.2

2.06 Material Impairments 191 0.0

3.01 Notice of Delisting or Failure to Satisfy a Continued Listing Rule or Standard; Transfer of Listing 3,832 0.8

3.02 Unregistered Sales of Equity Securities 884 0.2

3.03 Material Modifications to Rights of Security Holders 226 0.0

4.01 Changes in Registrant’s Certifying Accountant 357 0.1

4.02 Non-reliance on Previously Issued Financial Statements or a related audit report or completed interim review 461 0.1

5.01 Changes in Control of Registrant 98 0.0

5.02 Departure of Directors or Principal Officer; Election of Directors; Appointment of Principal Officers 32,036 6.6

5.03 Amendments to Articles of Incorporation or Bylaws; Change in Fiscal Year 1,098 0.2

5.04 Temporary Suspension of Trading Under Registrant’s Employee Benefit Plans 608 0.1

5.05 Amendments to the Registrant’s Code of Ethics, or Waiver of a Provision of the Code of Ethics 77 0.0

5.06 Change in Shell Company Status 8 0.0

5.07 Submission of Matters to a Vote of Security Holders 587 0.1

5.08 Shareholder Director Nominations 14 0.0

6.03 Change in Credit Enhancement or Other External Support 4 0.0

7.01 Regulation FD Disclosure 100.896 20.7

8.01 Other Events 113,549 23.3

Total 486,960 100 This table reports the distribution of 8K items and exhibits during firm quarters Q1/2005 through Q4/2016. Panel A presents details related to all 8K-item numbers. Panel B presents details related to exhibits reported within item 9.01s that are not stand-alone. Panel C presents details related to exhibit number 99. Shaded items are the most frequently reported items (greater than or equal to. 4%) across the entire sample period. 1The total is not equal to 100% because some 8K filings include multiple items. A single 8K might include one or multiple items, and a single item might include no or multiple exhibits.

53

Table 2 Summary statistics

Panel A: Summary statistics for the disclosure measures

Variable N. Obs. Mean Std. Dev. 25th Median 75th

8K_Ct 260,880 2.78 2.12 1.00 2.00 4.00

VDisc_Ct 260,880 3.78 4.04 2.00 3.00 5.00

VDisc_WC 260,880 5,058 15,939 324 2,441 4,812

VDisc_Sum 260,880 1.91 2.37 0.00 1.00 3.00

MDisc_Ct 260,880 2.98 4.39 0.00 2.00 4.00

MDisc_WC 260,880 11,114 31,569 0.00 432 5,865

Panel B: Summary statistics for firm characteristics

Variable N. Obs. Mean Std. Dev. 25th Median 75th

TAsst 260,880 4,211 13,618 52 429 2,093

MVE 246,760 2,518 7,681 44 250 1,330

#Anl 149,190 7.69 6.96 3.00 5.00 11.00

Segm 219,371 3.90 2.98 2.00 3.00 5.00

FAge 252,697 18.53 15.26 7.00 14.00 25.00

ROA 260,880 -0.12 0.63 -0.02 0.00 0.02

Loss 260,880 0.55 0.50 0.00 1.00 1.00

BTM 217,970 0.69 0.68 0.28 0.52 0.87

RD 112,169 0.03 0.20 0.00 0.00 0.001

Comp 254,265 0.35 0.31 0.13 0.23 0.49

RetVol 194,894 0.12 0.08 0.07 0.10 0.15

Issue 255,096 0.15 0.36 0.00 0.00 0.00

PLit 167,307 -1.65 2.26 -3.09 -2.02 -0.70

Panel C: Summary statistics for voluntary disclosure channels

Variable Mean Std. Dev. 25th Median 75th Max

MgmtGuide_Ct 0.62 0.95 0.00 0.00 1.00 28.00

ConfCall_Ct 0.62 0.76 0.00 0.00 1.00 13.00

NonGAAP_Ct 0.57 0.91 0.00 0.00 1.00 20.00

InvestDay_Ct 0.09 0.41 0.00 0.00 0.00 12.00

QMGuide_Ct 0.33 0.65 0.00 0.00 1.00 14.00

54

Panel D: Distribution of voluntary disclosure channels identified in Items 2.02, 7.01, and 8.01 and related exhibits All voluntary items Within Item 2.02 Within Item 7.01 Within Item 8.01

Variable N. Obs. %All N. Obs. %Variable %2.02 N. Obs. %Variable %7.01 N. Obs. %Variable %8.01 MgmtGuide_Ct 162,894 30.7 111,985 68.7 51.9 30,951 19.0 22.8 20,048 12.3 11.2 ConfCall_Ct 162,380 30.6 137,052 84.4 63.6 16,306 10.0 12.0 9,022 5.6 5.1 NonGAAP_Ct 148,216 28.0 111,160 75.0 51.6 24,689 16.7 18.2 12,367 8.3 6.9 InvestDay_Ct 24,687 4.7 6,067 24.6 2.8 14,978 60.7 11.0 3,642 14.8 2.0 QMGuide_Ct 86,001 16.2 62,940 73.2 29.2 15,750 18.3 11.6 7,311 8.5 4.1 No_ALT 187,254 35.3 30,877 16.5 14.3 50,127 26.8 37.0 106,250 56.7 59.5 TVDisc Items 529,710 215,616 135,626 178,468 This table presents descriptive statistics for the sample. Panel A reports summary statistics for the disclosure measures using the count of items and exhibits, the word count from

the items and exhibits, and the count of specific disclosures based on keyword searches. Panel B reports summary statistics for firm characteristics. The summary statistics for

#Anl, RD, and PLit are based on observations without missing values. Panel C presents details related to disclosure of the four disclosure channels in 8K Items 2.02, 7.01, or 8.01

and any associated exhibits. It includes No_ALT, an indicator defined as one if none of the four disclosure channels are identified, zero otherwise. %Variable is the number of

observations scaled by the total number of observations of each variable. %All (%2.02, %7.01, %8.01) is the number of observations scaled by the total number voluntary 8K

items (2.02s, 7.01s, 8.01s) filed during the sample period. Appendix 1 includes variable definitions.

55

Table 3 Industry analysis

Panel A: Mean values of disclosure by industry

Industry 8K_Ct VDisc_Ct VDisc_WC VDisc_Sum MDisc_Ct MDisc_WC

Consumer nondurables 2.83 3.70 4,882 1.99 3.13 11,961

Consumer durables 2.96 3.99 5,007 2.19 3.27 11,757

Manufacturing 2.79 3.74 4,532 2.22 2.97 11,352

Oil, gas, & coal extraction and products 3.67 5.52 6,711 2.47 4.32 21,027

Chemicals and allied products 3.09 4.11 5,316 2.16 3.58 15,257

Business equipment 2.70 3.17 3,581 2.16 3.13 9,485

Telephone & TV transmission 3.32 4.47 7,115 2.38 3.88 17,200

Utilities 3.45 5.69 12,213 3.12 3.06 16,810

Whole, retail, & some services 2.99 4.12 4,230 2.22 3.15 11,701

Health, medical equipment, & drugs 3.17 4.04 4,051 1.68 3.55 10,818

Finance 3.09 4.66 7,618 1.88 2.85 11,062

Other 2.97 3.82 4,840 2.10 3.61 13,492

Panel B: Regression coefficients from industry analysis

Industry 8K_Ct VDisc_Ct VDisc_WC VDisc_Sum MDisc_Ct MDisc_WC

Consumer nondurables 1.135 1.408 2.381 0.651 1.114 1.918

Consumer durables 1.826 2.582 4.679 1.535 2.154 3.773

Manufacturing 1.652 2.336 4.775 1.574 1.859 3.604

Oil, gas, & coal extraction and products 2.535 4.112 4.824 1.822 3.206 4.707

Chemicals and allied products 1.953 2.702 4.575 1.508 2.461 4.164

Business equipment 1.565 1.759 4.558 1.508 2.011 3.723

Telephone & TV transmission 2.182 3.066 4.935 1.730 2.763 4.338

Utilities 2.314 4.279 5.467 2.474 1.946 3.655

Whole, retail, & some services 1.856 2.714 4.732 1.570 2.035 3.732

Health, medical equipment, & drugs 2.040 2.636 4.553 1.025 2.434 4.200

Finance 1.958 3.248 5.150 1.232 1.739 3.192

Other 1.833 2.412 4.435 1.447 2.495 4.077

Adjusted R2 0.103 0.076 0.261 0.057 0.034 0.106 Panel A reports the mean values of each disclosure measure within the Fama-French 12 industry classifications for the full sample of 260,880 observations from 2005Q1 to 2016Q4. Panel B reports coefficient estimates from regressions of the disclosure measures on industry indicator variables based on Fama-French 12 Industry classification. All the parameter estimates in Panel B are statistically significant at < 0.001 level (two-tailed). See Appendix 1 for variable definitions.

56

Table 4 Correlations

Panel A: Correlations among disclosure measures – 260,880 obs.

8K_Ct VDisc_Ct VDisc_WC VDisc_Sum MDisc_Ct

VDisc_Ct 0.732 ---

VDisc_WC 0.555 0.802 ---

VDisc_Sum 0.418 0.629 0.810 ---

MDisc_Ct 0.678 0.271 0.227 0.187 ---

MDisc_WC 0.626 0.290 0.269 0.230 0.937

Panel B: Correlations between disclosure measures and voluntary disclosure channels – 260,880 obs.

8K_Ct VDisc_Ct VDisc_WC VDisc_Sum MDisc_Ct MDisc_WC

MgmtGuide_Ct 0.340 0.507 0.645 0.827 0.155 0.186

QMGuide_Ct 0.238 0.356 0.464 0.608 0.109 0.136

ConfCall_Ct 0.329 0.497 0.645 0.833 0.153 0.190

NonGAAP_Ct 0.303 0.462 0.669 0.802 0.147 0.185

InvestDay_Ct 0.219 0.296 0.304 0.353 0.071 0.088

Panel C: Correlations between disclosure measures and firm characteristics

N. Obs. 8K_Ct VDisc_Ct VDisc_WC VDisc_Sum MDisc_Ct MDisc_WC

TAsst 260,880 0.304 0.436 0.571 0.479 0.080 0.125

MVE 246,760 0.320 0.437 0.574 0.556 0.112 0.158

#Anl 149,190 0.110 0.140 0.056 0.290 0.276 0.075

Segm 219,371 0.140 0.197 0.273 0.302 0.047 0.063

FAge 252,697 0.059 0.125 0.168 0.155 -0.032 -0.017

ROA 260,880 0.048 0.158 0.186 0.220 -0.080 -0.050

Loss 260,880 -0.042 -0.161 -0.177 -0.150 0.101 0.071

BTM 217,970 -0.020 0.012 0.009 -0.054 -0.043 -0.043

RD 112,169 -0.113 -0.224 -0.312 -0.300 -0.004# -0.035

Comp 254,265 -0.073 -0.071 -0.109 -0.120 -0.065 -0.073

RetVol 194,894 0.011 -0.063 -0.102 -0.045 0.080 0.060

Issue 255,096 0.034 -0.061 -0.110 -0.129 0.123 0.097

PLit 167,307 0.280 0.338 0.414 0.384 0.129 0.149

Panel D: Correlations between voluntary disclosure channels and firm characteristics

N. Obs. MgmtGuide_Ct QMGuide_Ct ConfCall_Ct NonGAAP_Ct InvestDay_Ct

TAsst 260,880 0.387 0.296 0.350 0.455 0.167

MVE 246,760 0.444 0.364 0.463 0.487 0.159

#Anl 149,190 0.231 0.199 0.210 0.261 0.063

Segm 219,371 0.272 0.219 0.238 0.271 0.044

FAge 252,697 0.168 0.140 0.101 0.122 0.037

ROA 260,880 0.198 0.177 0.181 0.181 0.037

Loss 260,880 -0.143 -0.126 -0.126 -0.126 -0.059

BTM 217,970 -0.046 -0.081 -0.074 -0.027 0.009

RD 112,169 -0.261 -0.210 -0.196 -0.309 -0.075

Comp 254,265 -0.080 -0.069 -0.119 -0.097 -0.036

RetVol 194,894 -0.057 -0.066 0.038 -0.087 -0.057

Issue 255,096 -0.111 -0.098 -0.121 -0.121 -0.013

PLit 167,307 0.300 0.218 0.343 0.308 0.087 This table reports Spearman correlations among the 8K-based disclosure measures (Panel A), between the 8K-based disclosure measures and

the disclosure channel variables (Panel B), between the 8K-based disclosure measures and firm characteristics (Panel C), between the keyword

search indicator variables and firm characteristics (Panel D). All correlations are statistically significant at < 0.05 level (two-tailed) other than

those indicated by #. See Appendix 1 for variable definitions.

57

In this panel we split the full sample by the availability of I/B/E/S earnings guidance data, of I/B/E/S analyst following data, of Compustat data to calculate RD, and CRSP return

data to calculate PLit. We also split the sample based on two firm-specific factors. We present the mean values of disclosure variables in each subsample. The 8K & MEF sample

period includes 2005-2015, and all others have a sample period of 2005-2016. For the three indicator variables (“Ind”), when the variable equals 0 (e.g., Ind_#Anl=0), this indicates

that data necessary to form the underlying primary variable (e.g. #Anl ) is missing and set to a value instead of dropping the observation. All the values across the two corresponding

subgroups are statistically different from each other at <0.05 level, other than those indicated by #.

Table 5 Subsample descriptive statistics

Panel A: Binary subsamples

N. Obs. 8K_Ct VDisc_Ct VDisc_WC VDisc_Sum MDisc_Ct MDisc_WC 2.02_Ct 7.01_Ct 8.01_Ct

8K&MEF=1 42,614 3.16 4.60 6,994 3.21 3.03 12,920 2.21 1.10 1.29

8K&MEF=0 196,452 2.74 3.69 4,743 1.68 2.97 10,824 1.54 0.90 1.25

Ind_#Anl=1 149,190 3.24 4.72 6,734 2.72 3.15 12,946 2.10 1.15 1.47

Ind_#Anl=0 111,690 2.16 2.52 2,819 0.83 2.74 8,667 0.98 0.61 0.93

Ind_RD=1 112,169 2.78# 3.58 4,529 1.98 3.13 10,780 1.67 0.76 1.15

Ind_RD=0 148,711 2.77 3.93 5,457 1.86 2.86 11,366 1.58 1.04 1.30

Ind_PLit=1 167,307 3.09 4.35 5,894 2.49 3.12 12,504 1.99 1.03 1.33

Ind_PLit=0 46,674 1.93 2.20 3,294 0.83 2.66 9,432 0.73 0.62 0.85

Loss=1 144,173 2.74 3.43 4,427 1.64 3.37 11,834 1.40 0.85 1.19

Loss=0 116,707 2.83 4.21 5,843 2.24 2.49 10,225 1.90 1.01 1.30

Issue =1 38,381 3.05# 3.74 4,569 1.39 4.37 15,301 1.18 0.95 1.62

Issue =0 216,715 2.75 3.81 5,127 2.02 2.71 10,199 1.72 0.92 1.17

58

Panel B: Quintile analysis by firm characteristics

Low TAsst High TAsst Low MVE High MVE

8K_Ct 1.95 2.56 2.76 3.05 3.58 1.93 2.55 2.89 3.18 3.53

VDisc_Ct 1.89 3.10 3.70 4.50 5.71 1.90 3.13 3.90 4.66 5.51

VDisc_WC 1,232 2,584 3,744 5,812 11,918 1,549 2,681 3,976 6,165 10,571

VDisc_Sum 0.49 1.40 1.92 2.45 3.27 0.51 1.16 1.90 2.73 3.39

MDisc_Ct 2.82 2.93 2.72 2.98 3.42 2.67 2.91 2.98 3.13 3.43

MDisc_WC 5,997 8,026 9,668 14,058 17,821 5,858 8,107 10,247 14,004 17,171

2.02_Ct 0.70 1.47 1.83 1.99 2.12 0.80 1.39 1.76 2.08 2.24

7.01_Ct 0.46 0.64 0.78 1.18 1.54 0.40 0.70 0.93 1.20 1.40

8.01_Ct 0.74 0.99 1.09 1.32 2.05 0.70 1.04 1.21 1.38 1.87

N. Obs. 52,158 52,184 52,188 52,184 52,166 49,333 49,359 49,366 49,359 49,343

Low #Anl High #Anl Low Segm High Segm

8K_Ct 2.95 3.15 3.20 3.32 3.65 2.71 2.49 2.63 2.85 3.04

VDisc_Ct 4.03 4.45 4.68 4.95 5.61 3.44 3.17 3.54 3.87 4.32

VDisc_WC 4,394 5,565 6,416 7,409 10,274 3,645 3,710 4,563 5,344 6,733

VDisc_Sum 1.80 2.50 2.89 3.15 3.45 1.31 1.43 1.81 2.21 2.65

MDisc_Ct 2.96 3.07 3.07 3.22 3.49 3.18 2.96 2.90 3.04 3.11

MDisc_WC 9,961 11,785 12,809 14,754 15,912 10,060 10,165 10,728 12,036 13,238

2.02_Ct 1.85 2.04 2.15 2.21 2.32 1.24 1.27 1.53 1.78 1.97

7.01_Ct 0.89 1.07 1.16 1.27 1.41 0.90 0.82 0.90 0.94 1.01

8.01_Ct 1.29 1.34 1.37 1.47 1.88 1.30 1.09 1.11 1.15 1.34

N. Obs. 35,443 28,017 25,914 30,658 29,158 24,070 44,848 44,911 50,603 54,939

Low FAge High FAge Low ROA High ROA

8K_Ct 2.58 2.81 2.83 2.76 2.90 2.58 2.87 2.93 2.83 2.67

VDisc_Ct 3.23 3.69 3.79 3.87 4.32 2.81 3.81 4.36 4.17 3.74

VDisc_WC 3,608 4,415 4,758 5,175 7,284 2,685 5,352 6,752 6,222 4,277

VDisc_Sum 1.40 1.88 1.93 1.99 2.37 1.02 1.92 2.09 2.49 2.03

MDisc_Ct 3.41 3.06 2.90 2.75 2.71 3.70 3.31 2.65 2.66 2.55

MDisc_WC 12,351 11,125 10,168 10,646 10,978 10,266 13,481 10,981 11,609 9,234

2.02_Ct 1.19 1.61 1.74 1.74 1.83 1.00 1.61 1.84 1.89 1.76

7.01_Ct 0.89 0.91 0.86 0.89 1.08 0.69 0.94 1.06 1.02 0.89

8.01_Ct 1.15 1.17 1.19 1.24 1.41 1.12 1.26 1.46 1.26 1.09

N. Obs. 45,855 52,187 49,500 53,079 52,076 52,158 52,184 52,188 52,184 52,166

59

Low BTM High BTM Low RD High RD

8K_Ct 2.82 2.99 3.01 2.95 2.71 2.92 3.14 2.73 2.72 2.48

VDisc_Ct 3.72 4.15 4.29 4.22 3.76 4.21 4.41 3.45 3.23 2.66

VDisc_WC 4,339 5,331 5,984 5,739 4,849 6,899 6,986 3,831 2,960 1,995

VDisc_Sum 1.90 2.34 2.32 2.19 1.68 2.22 3.04 2.41 1.67 0.77

MDisc_Ct 3.09 3.04 3.00 2.92 2.74 3.13 3.33 2.87 3.02 3.36

MDisc_WC 11,027 11,987 12,051 11,278 9,246 13,521 16,020 9,326 7,735 7,976

2.02_Ct 1.58 1.87 1.90 1.88 1.68 1.80 2.05 1.93 1.67 0.97

7.01_Ct 0.90 0.99 1.02 1.01 0.89 1.08 0.94 0.58 0.55 0.61

8.01_Ct 1.25 1.29 1.36 1.33 1.19 1.33 1.41 0.95 1.01 1.08

N. Obs. 43,571 43,602 43,610 43,602 43,585 28,493 16,366 22,441 22,447 22,422

Low Comp High Comp Low RetVol High RetVol

8K_Ct 3.09 2.88 2.72 2.59 2.65 3.12 3.06 3.02 3.05 3.20

VDisc_Ct 4.56 3.85 3.52 3.33 3.67 4.75 4.50 4.24 4.15 4.25

VDisc_WC 7,803 4,889 4,185 4,053 4,627 7,669 6,351 5,301 4,873 5,022

VDisc_Sum 2.46 1.88 1.91 1.88 1.57 2.41 2.54 2.46 2.32 2.00

MDisc_Ct 3.28 3.14 3.10 2.96 2.55 2.75 2.81 2.91 3.12 3.59

MDisc_WC 14,662 11,868 11,178 10,582 8,098 11,588 11,969 11,532 11,517 12,394

2.02_Ct 1.73 1.60 1.58 1.58 1.63 1.99 2.03 2.01 1.97 1.81

7.01_Ct 1.28 0.98 0.81 0.74 0.82 1.17 1.08 1.01 0.96 0.99

8.01_Ct 1.56 1.27 1.13 1.01 1.22 1.60 1.39 1.22 1.23 1.45

N. Obs. 50,798 50,863 50,891 50,871 50,842 38,960 38,989 38,986 38,989 38,970

Low PLit High PLit

8K_Ct 1.98 2.63 2.97 3.24 3.37

VDisc_Ct 2.10 3.52 4.30 4.71 4.77

VDisc_WC 1,641 4,301 6,351 7,244 7,095

VDisc_Sum 0.75 1.86 2.52 2.84 2.66

MDisc_Ct 2.64 2.79 2.92 3.17 3.57

MDisc_WC 7,125 10,551 12,817 13,959 14,715

2.02_Ct 0.89 1.62 1.93 2.08 2.05

7.01_Ct 0.50 0.84 1.06 1.17 1.14

8.01_Ct 0.72 1.05 1.31 1.47 1.57

N. Obs. 42,778 42,806 42,806 42,806 42,806 This panel reports the mean values of disclosure variables within each quintile rank of each of the 11 firm characteristics. Within each calendar quarter, we sort observations into

quintiles based on the value of a firm characteristic. We then calculate the mean value of each disclosure variable within each quintile rank of the firm characteristic across all

firm-quarters. See Appendix 1 for variable definitions.

60

Table 6 Disclosure and liquidity

Panel A: Correlations

AvgBAS AmihudIll LVolume LPrice BTM LTAsst

8K_Ct -0.164 -0.242 0.256 0.043 -0.020 0.206

(0/47) (0/47) (47/0) (25/0) (0 /11) (47/0)

VDisc_Ct -0.229 -0.268 0.262 0.136 -0.016 0.286

(0/47) (0/47) (47/0) (47/0) (1/10) (47/0)

LVDisc_WC -0.406 -0.445 0.429 0.234 -0.035 0.474

(0/47) (0/47) (47/0) (47/0) (0 /23) (47/0)

VDisc_Sum -0.426 -0.452 0.428 0.221 -0.110 0.348

(0/47) (0/47) (47/0) (47/0) (0/47) (47/0)

MDisc_Ct -0.074 -0.150 0.181 -0.043 -0.024 0.079

(0/31) (0/47) (47/0) (0/25) (1/11) (39/0)

LMDisc_WC -0.107 -0.173 0.197 -0.007 -0.035 0.108

(0/44) (0/47) (47/0) (2/5) (1/18) (45/0)

Panel B: Regression results when the dependent variable is average bid-ask spread

Variables (1) (2) (3) (4) (5) (6)

8K_Ct 0.007

(0.23)

VDisc_Ct -0.039 -0.054***

(-2.42)** (-3.11)

LVDisc_WC -0.536*** -0.541***

(-11.62) (-11.68)

VDisc_Sum -0.187***

(-6.95)

MDisc_Ct 0.062***

(5.74)

LMDisc_WC 0.024***

(2.44)

LVolume -4.296*** -4.282*** -4.185*** -4.249*** -4.292*** -4.190***

(-43.98) (-43.81) (-43.53) (-43.44) (-43.96) (-43.65)

LPrice -5.207*** -5.217*** -5.209*** -5.219*** -5.188*** -5.197***

(-38.72) (-38.82) (-39.27) (-38.90) (-38.56) (-39.14)

BTM 1.784*** 0.178*** 1.753*** 1.768*** 1.779*** 1.754***

(6.98) (6.96) (6.97) (6.93) (6.97) (6.98)

LTAsst 1.228*** 1.240*** 1.356*** 1.274*** 1.232*** 1.352***

(12.50) (12.64) (13.88) (12.98) (12.54) (13.80)

Intercept 41.121*** 41.101*** 41.528*** 40.933*** 41.089*** 41.513***

(51.40) (51.46) (52.72) (51.19) (51.46) (52.72)

N. Obs. 185,983 185,983 185,983 185,983 185,983 185,983

Adj. R2 0.528 0.528 0.532 0.529 0.528 0.532

61

Panel C: Regression results when the dependent variable is the Amihud illiquidity measure

Variable (1) (2) (3) (4) (5) (6)

8K_Ct -0.090***

(-8.36)

VDisc_Ct -0.043*** -0.039***

(-6.37) (-5.80)

LVDisc_WC -0.190*** -0.184***

(-10.17) (-9.87)

VDisc_Sum -0.126***

(-13.22)

MDisc_Ct -0.016***

(-4.55)

LMDisc_WC -0.032***

(-7.33)

LPrice 0.433*** 0.446*** 0.439*** 0.437*** 0.437*** 0.421***

(9.55) (9.81) (9.77) (9.69) (9.62) (9.47)

BTM 1.226*** 1.229*** 1.197*** 1.208*** 1.226*** 1.189***

(15.87) (15.92) (15.63) (15.74) (15.89) (15.55)

LTAsst -0.677*** -0.681*** -0.625*** -0.646*** -0.676*** -0.614***

(-20.13) (-20.19) (-19.28) (-19.78) (-20.18) (-19.27)

Intercept 4.231*** 4.184*** 4.344*** 4.127*** 4.192*** 4.375***

(15.09) (14.97) (15.39) (14.87) (15.00) (15.48)

N. Obs. 172,588 172,588 172,588 172,588 172,588 172,588

Adj. R2 0.132 0.132 0.136 0.133 0.132 0.136 This table reports correlations between the disclosure measures, bid-ask spread, the Amihud illiquidity measure, and control variables for the sample period (Panel A), coefficient estimates from regressions of the average bid-ask spreads on the disclosure measures and control variables (Panel B), and coefficient estimates from regressions of the Amihud illiquidity measure on the disclosure measures and control variables (Panel C). All regressions include industry and year fixed effects and standard errors are clustered at the firm level. All coefficient values in Panel B (C) are multiplied (divided) by 1000 for ease of exposition. *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels (two-tailed), respectively. See Appendix 1 for variable definitions.

62

Table 7 Disclosure and cost of equity capital

Panel A: Correlations

COEC MBeta BTM LogMVE

8K_Ct -0.029 -0.024 0.072 0.141

(0/5) (0/0) (16/0) (30/0)

VDisc_Ct -0.049 -0.039 0.091 0.130

(0/5) (0/9) (21/0) (30/0)

LVDisc_WC -0.085 -0.002 0.100 0.253

(0/21) (2/7) (21/0) (34/0)

VDisc_Sum 0.024 0.052 -0.007 0.173

(2/0) (9/0) (1/2) (32/0)

MDisc_Ct 0.007 0.028 0.038 0.116

(1/2) (6/0) (3/0) (28/0)

LMDisc_WC 0.007 0.024 0.034 0.126

(1/2) (4/0) (3/0) (30/0)

Panel B: Regression results when the dependent variable is the COEC

Variable (1) (2) (3) (4) (5) (6)

8K_Ct -0.039

(-0.29)

VDisc_Ct -0.088 -0.101

(-1.40) (-1.57)

LVDisc_WC -0.443** -0.474***

(-2.58) (-2.77)

VDisc_Sum 0.013

(1.11)

MDisc_Ct 0.057

(1.24)

LMDisc_WC 0.073

(1.44)

MBeta 7.887*** 7.880*** 7.901*** 7.869*** 7.866*** 7.885***

(15.51) (15.50) (15.55) (15.44) (15.49) (15.51)

BTM -3.605*** -3.436*** -3.347*** -3.708*** -3.462*** -3.380***

(-2.89) (-2.75) (-2.69) (-2.98) (-2.77) (-2.71)

LogMVE -1.279*** -1.228*** -1.162*** -1.339*** -1.240*** -1.180***

(-4.25) (-4.08) (-3.88) (-4.44) (-4.11) (-3.93)

Intercept 99.801*** 99.689*** 102.279*** 99.792*** 99.672*** 102.240***

(36.80) (36.79) (35.07) (36.86) (36.79) (35.04)

N. Obs. 45,996 45,996 45,996 45,996 45,996 45,996

Adjusted R2 0.348 0.348 0.349 0.348 0.348 0.349 This table reports correlations between the disclosure measures, the cost of equity, and the control variables (Panel A) and the

coefficient estimates from regressions of the cost of equity capital on the disclosure measures and control variables (Panel B). All

regressions include year fixed effects and standard errors are clustered at the firm level. *, **, and *** indicate statistical

significance at the 10%, 5%, and 1% (two-tailed) levels, respectively. See Appendix 1 for variable definitions.

63

Table 8 Disclosure determinants

Panel A: Lagged disclosure model

Variable 8K_Ct VDisc_Ct LVDisc_WC VDisc_Sum

LagVolMeasure 0.444*** 0.551*** 0.527*** 0.502*** 0.495*** 0.621*** 0.608***

(19.73) (18.32) (16.54) (63.05) (63.18) (87.38) (83.58)

MDisc 0.201*** 0.042*** 0.060***

(25.73) (22.65) (21.44)

Trend -0.017*** 0.025*** 0.035*** 0.058*** 0.059*** 0.053*** 0.057***

(-8.40) (5.70) (7.82) (27.36) (27.59) (24.40) (26.28)

Intercept 0.784*** 0.277*** -0.001 -0.0521 -0.109 -0.277*** -0.374***

(10.41) (2.84) (-0.01) (-0.41) (-0.89) (-7.17) (-10.33) N. Obs. 147,852 147,852 147,852 147,852 147,852 147,852 147,852

Adjusted R2 0.252 0.346 0.381 0.489 0.494 0.442 0.452

Panel B: Full model

Variable 8K_Ct VDisc_Ct LVDisc_WC VDisc_Sum

LagVolMeasure 0.413*** 0.530*** 0.510*** 0.421*** 0.418*** 0.570*** 0.561***

(17.12) (16.49) (15.16) (51.87) (51.89) (70.31) (67.80)

MDisc 0.198*** 0.033*** 0.058***

(25.55) (18.70) (21.13)

LTAsst 0.136*** 0.235*** 0.192*** 0.228*** 0.218*** 0.178*** 0.166***

(16.71) (13.94) (11.41) (24.43) (23.60) (22.46) (21.32)

#Anl -0.0004 -0.010** -0.009** -0.012*** -0.012*** -0.009*** -0.009***

(-0.21) (-2.43) (-2.21) (-6.32) (-6.35) (-3.99) (-3.90)

Ind_#Anl 0.015 0.012 0.006 0.299*** 0.293*** 0.207*** 0.209***

(0.61) (0.29) (0.14) (11.02) (10.90) (10.54) (10.84)

Segm -0.002 -0.003 -0.005 -0.006 -0.006 0.006 0.005

(-0.40) (-0.33) (-0.72) (-1.26) (-1.33) (1.56) (1.42)

FAge -0.003*** -0.005*** -0.003** -0.009*** -0.008*** -0.006*** -0.005***

(-5.08) (-3.64) (-1.99) (-11.63) (-11.24) (-7.56) (-6.91)

ROA -0.794*** -0.533*** 0.0709 -0.156 -0.056 0.063 0.244***

(-7.44) (-3.62) (0.51) (-1.53) (-0.54) (1.03) (3.94)

Loss 0.149*** 0.068*** -0.050* 0.082*** 0.061*** 0.089*** 0.055***

(9.65) (2.60) (-1.90) (4.98) (3.74) (5.95) (3.72)

BTM -0.045*** -0.128*** -0.137*** -0.097*** -0.098*** -0.111*** -0.114***

(-3.42) (-5.49) (-5.93) (-5.25) (-5.35) (-8.72) (-9.08)

RD 5.291*** 10.18*** 8.141*** 2.433 2.143 1.476* 0.850

(2.63) (2.99) (2.66) (0.97) (0.86) (1.77) (0.95)

Ind_RD -0.032 -0.095** -0.086** -0.015 -0.015 0.059** 0.064***

(-1.39) (-2.38) (-2.18) (-0.55) (-0.55) (2.57) (2.78)

Comp -0.097*** -0.161*** -0.141** -0.224*** -0.219*** -0.082** -0.076*

(-2.89) (-2.65) (-2.32) (-4.74) (-4.67) (-2.02) (-1.89)

RetVol 0.605*** 0.499** 0.040 -0.209* -0.283** 0.235*** 0.094

(5.46) (2.54) (0.20) (-1.68) (-2.28) (2.60) (1.04)

Issue 0.230*** 0.250*** 0.109** 0.050* 0.028 0.064*** 0.021

(8.75) (5.54) (2.44) (1.69) (0.96) (2.91) (0.96)

PLit 0.005* -0.006 -0.012** -0.007** -0.008*** -0.009*** -0.010***

(1.84) (-1.14) (-2.19) (-2.51) (-2.83) (-3.48) (-4.19)

Ind_PLit 0.107 0.169 0.177 -0.036 -0.036 -0.106* -0.099

(1.54) (1.38) (1.47) (-0.50) (-0.49) (-1.74) (-1.61)

Trend -0.026*** 0.015*** 0.027*** 0.059*** 0.059*** 0.053*** 0.058***

(-12.02) (3.30) (6.00) (25.92) (26.28) (23.43) (25.47)

Intercept 0.062 -0.857*** -0.848*** -0.645*** -0.637*** -1.048*** -1.065***

(0.59) (-5.46) (-5.52) (-4.39) (-4.41) (-12.64) (-12.89) N. Obs. 147,852 147,852 147,852 147,852 147,852 147,852 147,852

Adjusted R2 0.266 0.354 0.387 0.519 0.522 0.459 0.467

64

This table reports the coefficient estimates from regressions of the voluntary disclosure measures on lagged voluntary disclosure, concurrent

mandatory disclosure, a time trend, and firm characteristics. All regressions include industry and year fixed effects and standard errors are

clustered at the firm level. *, **, and *** indicate statistical significance at the 10%, 5%, and1% levels (two-tailed), respectively. See

Appendix 1 for variable descriptions.

65

Table 9 Disclosure persistence

Panel A: Persistence of primary items and exhibits

Count of Items and Exhibits Word Count of Items and Exhibits

q-1 q-4 q-1 q-4

8K_Ct 0.531 0.489 NA NA

VDisc_Ct/WC 0.601 0.541 0.242 0.227

Item 2.02 + Exhibit 0.711 0.720 0.766 0.742

Item 7.01 + Exhibit 0.635 0.606 0.336 0.357

Item 8.01 + Exhibit 0.466 0.356 0.104 0.095

MDisc_Ct/WC 0.319 0.263 0.133 0.134

Item 1.01+ Exhibit 0.214 0.181 0.119 0.121

Item 5.02 + Exhibit 0.163 0.189 0.064 0.096

Panel B: Persistence of disclosure channels

q-1 q-4

VDisc_Sum 0.712 0.697

MgmtGuide_Ct 0.607 0.565

NonGAAP_Ct 0.714 0.678

ConfCall_Ct 0.721 0.698

InvestDay_Ct 0.454 0.477

QMGuide_Ct 0.565 0.520

Panel C: Persistence of disclosure channels, conditional on voluntary item numbers.

Count of Items and Exhibits

q-1 q-4

Within Item 2.02

MgmtGuide_Ct 0.662 0.614

NonGAAP_Ct 0.809 0.756

ConfCall_Ct 0.792 0.763

InvestDay_Ct 0.612 0.596

QMGuide_Ct 0.581 0.526

VDisc_Sum 0.791 0.767

Within Item 7.01

MgmtGuide_Ct 0.529 0.504

NonGAAP_Ct 0.548 0.526

ConfCall_Ct 0.519 0.473

InvestDay_Ct 0.425 0.449

QMGuide_Ct 0.470 0.435

VDisc_Sum 0.574 0.572

Within Item 8.01

MgmtGuide_Ct 0.197 0.141

NonGAAP_Ct 0.192 0.158

ConfCall_Ct 0.280 0.265

InvestDay_Ct 0.151 0.138

QMGuide_Ct 0.125 0.097

VDisc_Sum 0.233 0.188 This table reports the persistence of the disclosure measures and the primary items used to construct those measures (Panel A), of the disclosure channels (Panel B), and of the disclosure channels conditional on the 8K item they are reported in (Panel C). Cell values are coefficient estimates where current quarter disclosures are regressed on lagged quarter disclosures (lagged 1 or 4 quarters). Standard errors are clustered at the firm level. All coefficient estimates are statistically significant at the 1% level (two-tailed). See Appendix 1 for variable definitions.

66

Figure 1:

Plots of 8K-based count disclosure measures, sorted by quintile rank of firm attributes

8K_Ct/VDisc_Ct/MDisc_Ct

0

1

2

3

4

5

6

Low

TAsst

2 3 4 High

TAsst

0

1

2

3

4

5

6

Low

MVE

2 3 4 High

MVE

0

1

2

3

4

5

6

Low

#Anl

2 3 4 High

#Anl

0

1

2

3

4

5

6

Low

Segm

2 3 4 High

Segm

0

1

2

3

4

5

6

Low

FAge

2 3 4 High

FAge

0

1

2

3

4

5

6

Low

ROA

2 3 4 High

ROA

0

1

2

3

4

5

6

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BTM

2 3 4 High

BTM

0

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2

3

4

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6

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RD

2 3 4 High

RD

0

1

2

3

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6

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Comp

2 3 4 High

Comp

0

1

2

3

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6

Low

RetVol

2 3 4 High

RetVol

0

1

2

3

4

5

6

Low

PLit

2 3 4 High

PLit

67

Figure 2:

Plots of 8K-based word count disclosure measures, sorted by quintile rank of firm attributes

VDisc_WC/MDisc_WC

0

5000

10000

15000

20000

Low

TAsst

2 3 4 High

TAsst

0

5000

10000

15000

20000

Low

MVE

2 3 4 High

MVE

0

5000

10000

15000

20000

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#Anl

2 3 4 High

#Anl

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5000

10000

15000

20000

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Segm

2 3 4 High

Segm

0

5000

10000

15000

20000

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FAge

2 3 4 High

FAge

0

5000

10000

15000

20000

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ROA

2 3 4 High

ROA

0

5000

10000

15000

20000

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BTM

2 3 4 High

BTM

0

5000

10000

15000

20000

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RD

2 3 4 High

RD

0

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10000

15000

20000

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Comp

2 3 4 High

Comp

0

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10000

15000

20000

0

5000

10000

15000

20000

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PLit

2 3 4 High

PLit

68

Figure 3:

Plots of voluntary 8K items (and associated exhibits) and of VDisc_Sum, sorted by quintile rank of firm attributes

2.02_Ct/7.01_Ct/8.01_Ct/VDisc_Sum

0

0.5

1

1.5

2

2.5

3

3.5

Low

TAsst

2 3 4 High

TAsst

0

0.5

1

1.5

2

2.5

3

3.5

Low

MVE

2 3 4 High

MVE

0

0.5

1

1.5

2

2.5

3

3.5

Low

#Anl

2 3 4 High

#Anl

0

0.5

1

1.5

2

2.5

3

3.5

Low

Segm

2 3 4 High

Segm

0

0.5

1

1.5

2

2.5

3

3.5

Low

FAge

2 3 4 High

FAge

0

0.5

1

1.5

2

2.5

3

3.5

Low

ROA

2 3 4 High

ROA

0

0.5

1

1.5

2

2.5

3

3.5

Low

BTM

2 3 4 High

BTM

0

0.5

1

1.5

2

2.5

3

3.5

Low

RD

2 3 4 High

RD

0

0.5

1

1.5

2

2.5

3

3.5

Low

Comp

2 3 4 High

Comp

0

0.5

1

1.5

2

2.5

3

3.5

Low

RetVol

2 3 4 High

RetVol

0

0.5

1

1.5

2

2.5

3

3.5

Low

PLit

2 3 4 High

PLit