Abstract
Regulators claim that increased mandated disclosure frequency should lead to more efficient price formation. However, analytical models suggest that mandating disclosure may actually impede the price formation process, and prior empirical studies have been unable to document a relation between mandatory disclosure and improved price formation. We re-examine this relationship using a recent SEC regulation that increased the frequency of mandated event disclosures in form 8-K. We show that price formation improves after the mandate, where firms with the largest increases in mandatory disclosure experience the greatest improvements in price formation. Our evidence is consistent with the idea that mandating an increase in the frequency that material events must be disclosed is associated with improved price formation.
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Notes
We define price formation as the speed with which information is incorporated into a firm’s stock price. Following prior research (e.g., Butler et al. 2007; Bushman et al. 2010), we measure price formation using intraperiod timeliness (IPT). We provide a detailed description of how this measure is calculated along with illustrative examples in the internet appendix.
There is also a large literature that uses 8-K filings to examine market reactions to specific events. Examples include (1) Schwartz and Soo (1996), Ettredge et al. (2001), and Whisenant et al. (2003) for auditor change announcements; (2) Chambers and Penman (1984), Easton and Zmijewski (1989), and Collins and Hribar (2000) for earnings; and (3) Feldman et al. (2008) for nonreliance on previously issued financial statements. The focus of these studies is primarily the short-term reactions to the disclosed events.
As discussed in Section 4 of the internet appendix, we provide evidence consistent with the notion that the firms most impacted by the regulation (i.e., those that had the largest increase in disclosure) had the highest pre-regulation levels of proprietary costs.
Consistent with the limited investor response to 10-Q/K filings, in untabulated tests we fail to find evidence of a significant impact of the regulation on IPT in the 14-day window after the EAD and leading up to the 10-K/Q. This lack of evidence in this short window is consistent with Lerman and Livnat’s (2010) analysis, which finds no reduction in periodic filings’ information content after the regulation and provides support for our use of the earnings announcement as the end point of our price formation window.
This is also consistent with firms perceiving these newly mandated disclosures as providing minimal benefits. Specifically, a firm’s decision not to voluntarily disclose these items in the pre-regulation period may be driven by the belief that the disclosures provide insufficient benefits, relative to the costs associated with making those disclosures (Leuz and Wysocki 2016).
Gigler and Hemmer (1998) model a periodic disclosure framework, where they predict that mandating more frequent interim reports may lead to reductions in voluntary disclosures, due to an overall increase in the cost of disclosure (e.g., production costs). They suggest that, because voluntary disclosures are often more precise indicators of firm value, mandating disclosure could actually lead to a reduction in price-informativeness. Consistent with this crowding out notion, a concurrent study by Noh et al. (2017) provides evidence that the 2004 8-K mandate results in a significant decrease in voluntary disclosure.
To properly interpret the IPT measure, it is important to use an endpoint culminating with the release of the summary information for the quarter. Following Bushman et al. (2010), we use the earnings announcement as our endpoint, because it provides a common and meaningful date across all firms where a significant amount of information becomes public. In addition, we select the earnings announcement, rather than the 10-Q/K, as research has shown that there is little to no average market reaction to these periodic filings (Li and Ramesh 2009). To reduce the likelihood that prior-period earnings information is affecting the measure, we eliminate any firm-quarters from our sample where a prior-period earnings announcement is made during the 63-trading-day window.
More detail on the calculation of IPT along with illustrative examples can be found in the internet appendix.
As evidence of this large increase, we find that, for our sample firms, the total number of 8-K items issued per year nearly doubled from 121,314 before the regulation to 223,878 after the regulation (untabulated).
We use the highest and lowest terciles to ensure that the regulation had distinct impacts on the high and low impact firms. In addition, as noted, our tests focus on the four quarters on either side of the regulation. Bertrand et al. (2004) raise a potential concern that serial correlation may affect the standard errors when using multiple observations in the pre and post period. To address this concern we perform a robustness test (untabulated), where, for each firm, we average together the four quarters of data before and the four quarters after the regulation to create a single variable for each of the pre and post periods. We then re-run our primary analyses using this substantially reduced sample and find that the significance and economic magnitude of the coefficients are unaffected.
In addition to these primary controls, the internet appendix provides results showing that our findings are robust to controlling for potential changes in the timeliness or textual and numeric content of 8-K disclosures.
In untabulated tests, we cluster standard errors by year-quarter and find this does not affect our results.
Although there is potential for noise in the IPT measure, there is no reason to expect this noise to introduce any type of bias into our inferences. In Section 5.4, we provide evidence that our results are robust to alternative methods of addressing outliers, including retaining the extreme observations with studentized residuals greater than two or using a decile-ranked version of IPT.
This estimate is derived by combining the coefficient estimate on Post with the intercept value of 36.912 (untabulated). Results are nearly identical if industry fixed effects are omitted.
In the internet appendix, we provide a series of tests (i.e., placebo tests and quarter-by-quarter tests) that show our results are unique to the period surrounding the passage of the regulation.
Results are robust to using the full, nonweighted sample of high and low impact firms (untabulated).
These effects are derived by combining the applicable coefficient estimates with the intercept value of 29.877 (untabulated). Results are nearly identical if industry fixed effects are omitted.
In Section 5.5, we perform additional cross-sectional analyses to better understand whether the regulation differentially impacted firms with high and low institutional ownership.
Appendix A provides a summary of item descriptions. As previously discussed, the numbering scheme changed with the regulation. The excluded 8-K filing numbers are based on the new numbering system, while 8-K filed during the pre-regulation period were adjusted to match the corresponding post-regulation classifications.
Specifically, during the 63-trading day-window with which we measure IPT, a lack of any price response until the end of earnings announcement window would result in an IPT value of 0, while an immediate and complete price response on the first day of the quarter, with no subsequent change in price, would result in an IPT value of 62.5.
The results reported in Panel B of Table 6 demonstrate that our results are not driven by the inclusion/exclusion of potential extreme observations. Not surprisingly, when extreme observations are included, the coefficient on the interaction term in the first column of Table 6 Panel B is larger than the coefficient reported in Panel B of Table 3, where these extreme observations are excluded. We also note that the difference in the coefficient magnitudes across the columns of Table 6 Panel B is largely attributable to the difference in dependent variables (continuous measure of IPT versus decile-ranked measure).
Negative IPT values correctly capture the underlying economics of slower price formation, where returns at the beginning of the period are negative (positive) and then toward the end of the period flip, to result in an overall positive (negative) quarterly return. In contrast, the economic interpretation of IPT values above 62.5 is less clear. As such, we also re-run (untabulated) our analysis after removing only those observations with IPT values above 62.5 and find that the coefficient on Post*High_Impact is positive and significant (t-statistic of 2.251).
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Acknowledgements
We are grateful for helpful comments from workshop participants at Duke University, Texas A&M University, the 2016 FARS Conference, the 2016 AAA Conference, the 2015 BYU Accounting Research Symposium, the 2017 Midwest Finance Association Annual Meeting, and the 2017 EAA Annual Congress, as well as Dirk Black (AAA discussant), John Campbell (FARS discussant), Kimball Chapman, Ed deHaan, Paul Fischer, Cristi Gleason, Brad Hepfer, Eric Holzman, Bret Johnson, Pepa Kraft (MFA discussant), Joshua Madsen, Richard Sloan (editor), and two anonymous referees. We also express gratitude to Adam Hadley for research assistance. Brian Miller gratefully acknowledges financial support from the PwC Faculty Fellowship.
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Appendices
Appendix 1
1.1 Form 8-K item descriptions
Item | Description | Introduced By Regulation? |
|---|---|---|
1.01 | Entry into a Material Definitive Agreement | Yes |
1.02 | Termination of a Material Definitive Agreement | Yes |
1.03 | Bankruptcy or Receivership | No |
2.01 | Completion of Acquisition or Disposition of Assets | No |
2.02 | Results of Operations and Financial Condition | No |
2.03 | Creation of a Direct Financial Obligation or an Obligation under an Off-Balance Sheet Arrangement of a Registrant | Yes |
2.04 | Triggering Events That Accelerate or Increase a Direct Financial Obligation or an Obligation under an Off-Balance Sheet Arrangement | Yes |
2.05 | Costs Associated with Exit or Disposal Activities | Yes |
2.06 | Material Impairments | Yes |
3.01 | Notice of Delisting or Failure to Satisfy a Continued Listing Rule or Standard; Transfer of Listing | Yes |
3.02 | Unregistered Sales of Equity Securities | Yes |
3.03 | Material Modifications to Rights of Security Holders | Yes |
4.01 | Changes in Registrant’s Certifying Accountant | No |
4.02 | Non-Reliance on Previously Issued Financial Statements or a Related Audit Report or Completed Interim Review | Yes |
5.01 | Changes in Control of Registrant | No |
5.02 | Departure of Directors or Principal Officers; Election of Directors; Appointment of Principal Officers | Expanded |
5.03 | Amendments to Articles of Incorporation or Bylaws | Expanded |
5.04 | Temporary Suspension of Trading Under Registrant’s Employee | No |
5.05 | Amendments to the Registrant’s Code of Ethics, or Waiver of a Provision of the Code of Ethics | No |
7.01 | Regulation FD Disclosure | No |
8.01 | Other Events | No |
9.01 | Financial Statements and Exhibits | No |
Appendix 2
1.1 Variable definitions
8K_Prop_Ret | = the signed size, BTM, and momentum (5 × 5 × 5) adjusted buy-and-hold return over the two-day period beginning on the 8-K filing date, summed across all 8-Ks filed during the quarter, and scaled by the signed quarterly size, BTM, and momentum adjusted buy-and-hold return. |
Abs_EA_Ret | = the absolute size, BTM, and momentum (5 × 5 × 5) adjusted buy-and-hold return over the two-day period beginning on the earnings announcement date. |
AggRetVol | = the standard deviation of daily market (value-weighted) returns over the 63-day trading day window beginning 60 trading days prior to the earnings announcement and ending two trading days after it. |
Avg_Num_Numbers | = the average number of numbers in all 8-Ks filed by the firm during the quarter. |
Avg_Num_Words | = the average number of words in all 8-Ks filed by the firm during the quarter. |
Avg_Timeliness | = the average number of days between the event date and the filing date of all 8-K disclosures made by the firm during the quarter. |
BTM | = the book-to-market ratio as of the end of the quarter. |
Capx | = capital expenditures during the quarter scaled by total assets. |
FirmRetVol | = the standard deviation of daily raw returns over the 63-day trading day window beginning 60 trading days prior to the earnings announcement and ending two trading days after it. |
High_Impact | = an indicator variable equal to one if the firm is in the sample of firms most impacted by the regulation, zero if the firm is in the sample of firms least impacted by the regulation, and missing otherwise. Firms in the highest (lowest) tercile of Item_Change are defined as most (least) impacted. |
High_Impact_Adj | = an indicator variable equal to one if the firm is in the sample of firms most impacted by the regulation, zero if the firm is in the sample of firms least impacted by the regulation, and missing otherwise, using the alternative measures of regulation impact as defined in Section 5.1.2. |
High_Impact_Ex_Ante | = an indicator variable equal to one if the firm is in the sample of firms most impacted by the regulation, zero if the firm is in the sample of firms least impacted by the regulation, and missing otherwise, using the ex-ante measure of regulation impact based on the existence of, and voluntary disclosure of, impairments and disposals in the pre-regulation period, as defined in Section 5.1.1. |
InstOwn | = the number of shares held by institutional investors, scaled by total shares outstanding as of the end of the quarter. |
IPT | = the intraperiod timeliness measure, calculated over the 63-day trading day window beginning 60 trading days prior to the earnings announcement and ending two trading days after it. See the internet appendix for more details. |
Item_Change | = the percentage change in the number of 8-K items the company filed with the SEC from the pre-regulation period to the post-regulation period. |
Leverage | = long-term debt scaled by total assets as of the end of the quarter. |
ln(B_Segs) | = the natural logarithm of the number of the compan’s unique business segments as of the end of the quarter. |
ln(Follow) | = the natural logarithm of the number of analysts following the firm as of the end of the quarter. |
ln(G_Segs) | = the natural logarithm of the number of the company’s unique geographic segments as of the end of the quarter. |
ln(MVE) | = the natural logarithm of market value of equity as of the end of the quarter. |
ln(News) | = the natural logarithm of one plus the number of articles written about the firm in the Dow Jones News Archives during the quarter, provided by RavenPack. |
Loss | = an indicator variable equal to one if net income for the quarter was less than zero and zero otherwise. |
Num_Item | = the number of 8-K items the company filed with the SEC during the quarter. |
Post | = an indicator variable equal to one if the quarter occurred after the passage of the SEC’s new Form 8-K disclosure requirements on August 23, 2004, and zero otherwise. |
Prop_Bad_News | = the proportion of 8-Ks issued during the quarter that contain bad news, where bad news is determined based on a negative two day size, BTM, and momentum (5 × 5 × 5) adjusted buy-and-hold return to the filing. |
ROA | = return on assets for the quarter, calculated as net income before extraordinary items divided by total assets. |
Time | = a count variable that begins at 0.01 and increases by 0.01 for each month of the sample period. |
Time 2 | = the squared value of Time. |
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McMullin, J.L., Miller, B.P. & Twedt, B.J. Increased mandated disclosure frequency and price formation: evidence from the 8-K expansion regulation. Rev Account Stud 24, 1–33 (2019). https://doi.org/10.1007/s11142-018-9462-2
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DOI: https://doi.org/10.1007/s11142-018-9462-2