The Timeliness of Bad Earnings News and Litigation Risk

The following post comes to us from Dain Donelson of the Department of Business, Government, and Society at the University of Texas at Austin, John McInnis of the Department of Accounting at the University of Texas at Austin, Richard Mergenthaler of the Department of Accounting at the University of Iowa, and Yong Yu of the Department of Accounting at the University of Texas at Austin.

In our paper, The Timeliness of Bad Earnings News and Litigation Risk, which was recently made publicly available on SSRN, we examine the relation between the timeliness of bad earnings news and the incidence of securities litigation. Skinner (1994) proposes that the earlier revelation of bad news reduces the expected costs of litigation because earlier revelation diminishes the perception that management “hid the truth” and reduces damages by shortening the class period. This litigation reduction hypothesis predicts that timelier revelation of bad earnings news should reduce the likelihood of being sued and/or the costs of resolving lawsuits that do occur.

Prior work investigates the litigation reduction hypothesis using measures based on management earnings “warnings” or “pre-announcements” via a press release to measure early disclosure. Our innovation is a new measure of the timeliness of total earnings news, which captures how quickly earnings news is revealed to the market using the evolution of analysts’ consensus earnings forecasts. This new measure allows for a stronger test of the litigation reduction hypothesis for two reasons. First, our measure captures all bad earnings news revealed to the market, including instances where there are multiple news events. Earnings warnings delivered in companies’ press releases are only one way in which earnings news can be revealed to the market. Alternative methods include analyst conference calls, presentations, webcasts, private communications (at least before Regulation FD), and analyst research. Second, our measure is constructed using machine-readable data sources, allowing for larger sample tests. Hand-collection of disclosure data (e.g., press release warnings) is costly and time consuming. Analysts’ consensus forecasts are arguably the best available proxy for the market earnings expectation. We measure earnings news timeliness for the quarter triggering lawsuits by computing the proportion of total earnings news revealed up to each day in the quarter and then taking the average of the daily proportions. Thus, our timeliness measure captures the average daily proportion of total earnings news revealed to the market during the quarter triggering litigation.

Our sued sample consists of 423 securities class action lawsuits from 1996-2005. Consistent with prior research, we use a matched sample research design. Our first matched sample contains non-sued firms matched with sued firms based on total earnings news and disclosure window. This ensures that sued and non-sued firms have similar total earnings news over the same time period, which helps control for the endogeneity noted by Skinner (1997). Specifically, for each sued firm-quarter (i.e., the quarter triggering the lawsuit), we select a non-sued firm from the same quarter with the closest total earnings news (i.e., the ultimate earnings revelation less the beginning-of-quarter consensus forecast, scaled by beginning-of-quarter stock price). Our second matched sample utilizes the predicted probability of litigation. Specifically, we estimate a litigation prediction model that expresses the probability of being sued as a function of economic determinants using all bad news firm-quarters. Then, for each sued firm-quarter, we select the non-sued firm from the same quarter the closest predicted litigation probability.

Using each of the two matched samples, we find that timelier revelation of bad earnings news is associated with a lower threat of litigation. This negative relation applies to both settled and dismissed suits and is robust to controlling for numerous determinants of litigation risk, such as firm size, stock returns over the litigation quarter, the largest negative one-day return during the litigation quarter, and insider selling. Furthermore, our results are similar if we use alternative matching methods, such as matching on market capitalization and stock returns over the litigation quarter or matching on industry and the largest negative one-day stock return over the litigation quarter. These alternative matching methods provide evidence that our results are not driven by sued firms having larger stock price drops over the litigation quarter or over a short window. In addition, our results are not driven by innate differences between sued and non-sued firms. We find similar patterns when we benchmark sued firms against themselves by examining the speed of news revelation in non-litigation quarters.

We perform two analyses to reconcile our findings with those of prior studies. First, we repeat our test with a timeliness measure used by prior studies. We hand-collect data on management earnings warnings via press releases from Factiva and Lexis-Nexis for a random sub-sample of firms with large negative total earnings news. Following Field et al. (2005), we measure disclosure timeliness using an indicator variable for the presence of an earnings warning prior to the earnings announcement. Consistent with prior studies, we find that sued firms are more likely to issue earnings warnings than non-sued firms. However, once we replace this earnings warning measure with our new measure of the timeliness of total earnings news, we find that bad earnings news is revealed timelier for non-sued firms than for sued firms. This result suggests that the difference between our findings and those of prior studies is driven by our new timeliness measure, which captures news revelation beyond management press releases.

Second, we examine the underlying sources of analysts’ forecast revisions in our sample. We hand-collect analyst research reports for the random sub-sample of firms described above. These reports contain analysts’ explanations for their forecast revisions. We then classify each revision into three categories based on the source of the information that triggered the revision: a) traditional managerial warnings through press releases (i.e., those studied by prior research), b) non-traditional managerial disclosures (e.g., conference calls, webcasts, presentations), and c) non-management news (e.g., analysts’ research with respect to industry news or polling of customers or suppliers).

This analysis yields three main results. First, the overwhelming majority of analyst revisions (roughly 90%) are driven by managerial disclosures, traditional or non-traditional. Second, although sued firms are more likely to issue traditional earnings warnings, we find that when non-sued firms do issue traditional earnings warnings, these warnings are timelier. Third, non-sued firms are more likely than sued firms to issue non-traditional managerial disclosures, and these disclosures are also timelier. Overall, our analysis of analyst research reports helps validate our new measure as a way to capture all forms of managerial disclosure. Further, the fact that non-sued firms release bad news in a timelier fashion via non-traditional channels explains why the use of our measure provides robust support for the litigation reduction hypothesis.

This study makes three primary contributions. First, we construct a new measure of timeliness that captures how quickly total bad earnings news is revealed to the market. This measure is based on machine-readable data and can be used in future research to investigate the impact of timely earnings news revelations. Second, we provide additional evidence on Skinner’s (1994) litigation reduction hypothesis. Our findings complement and extend those of Field et al. (2005) by providing evidence that timelier revelation of bad earnings news deters all types of litigation. Third, our results demonstrate the importance of considering multiple revelation channels when studying managerial disclosure. Our findings suggest that managers frequently utilize channels other than press releases to reveal earnings information. Thus, examining only press releases yields an incomplete picture of managerial disclosure and can lead to erroneous inferences.

The full paper is available for download here.

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