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Review of Accounting Studies

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01.03.2012

The effect of stock price on discretionary disclosure

verfasst von: Ewa Sletten

Erschienen in: Review of Accounting Studies | Ausgabe 1/2012

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Abstract

I examine the impact of exogenous changes in stock prices on voluntary disclosure. Specifically, I investigate whether stock price declines prompt managers to voluntarily disclose firm-value-related information (management forecasts) that was withheld prior to the decline because it was unfavorable but became favorable at a lower stock price. Consistent with my predictions, I find that managers are more likely to release good-news forecasts following larger stock price declines but that there is no association between the likelihood of releasing good-news forecasts and the magnitude of stock price increases. Additional evidence indicates that the good-news forecasts eventually conveyed by withholding firms after negative price shocks would likely have resulted in negative market reactions had they been released before the shocks. More generally, I provide evidence that managers withhold bad news and that exogenous stock price declines can induce its disclosure.

Vorheriger Artikel Accounting complexity, misreporting, and the consequences of misreporting

Nächster Artikel Using residual income to refine the relationship between earnings growth and stock returns

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See, for example, Coughlan and Schmidt (1985), Lang and Lundholm (2000), Murphy and Zimmerman (1993), Noe (1999), Warner et al. (1988), Weisbach (1988).

In their models there are managers who either have no information (Dye 1985) or find it expensive to disclose (Verrecchia 1983). Because investors cannot distinguish between managers with poor information and managers with no new information (or high disclosure costs), firms with poor information will prefer the pooled price and will not disclose.

This can be illustrated with the following example. Suppose that the manager has private information that future earnings will be such that the firm should be valued at $27 per share but the current stock price is $30 per share. The manager would like to maintain a high stock price so she chooses not to release the news. However, if the stock price exogenously declines below $27 per share, the manager will release her information about future earnings because her disclosure will be now associated with a positive market reaction.

Moreover, Xu et al. (2006) also find that industry peers of firms whose restatement results in a negative (positive) market reaction incur negative (positive) contagion.

This group of firms includes firms with considerable negative contagion effects (needed for the manager’s private information to be more favorable than the firm’s stock price after the industry restatement) and firms that do not disclose regularly (since these firms are more likely not to follow a strategy of full disclosure). For further discussion, see Sect. 4.2 of the paper.

My primary specification controls for the standard deviation of market-adjusted returns. In additional, untabulated tests I check the robustness of my results to inclusion of the change in the standard deviation of market-adjusted returns around the industry restatement. The results remain qualitatively unchanged.

I also analyze bad news management forecasts issued after industry restatements. My results complement prior research suggesting that litigation risk gives rise to disclosure of bad news. Specifically, firms with larger stock price declines (and thus larger increase in litigation risk) are more likely to issue bad news forecasts.

See Beyer et al. (2010); Dye (2001); Healy and Palepu (2001); and Verrecchia (2001) for an extensive review of the disclosure literature.

Farrell (1986) comes to similar conclusions as Dye (1985), while Jung and Kwon (1988) extend the model developed by Dye (1985). Jovanovic (1982) develops a model based on Akerlof’s (1970) market for lemons that has the same implications as Verrecchia (1983).

Technically, this is only true in Dye (1985); in Verrecchia (1983) the threshold corresponds to stock price plus cost of disclosure. My predictions would be the same in either case.

I also check the sensitivity of my results to short windows (i.e., those not exceeding 1 week). The shorter the window, the less likely that new private information would confound observed disclosures. My results are robust to these alternative windows.

Gleason et al. (2008) report that 98.81% of the industry peer-firms do not restate following the first restatement in the industry. In their sample, peer-firms who do not subsequently restate have significantly negative abnormal returns of −0.24% during the three-day window centered on the industry restatement announcement.

A scenario that generates an empirical prediction distinct from mine is that at the time of the industry restatement managers have no previously withheld information (i.e. their private valuation equals the stock price before the industry restatement). In this case, negative contagion effect generates good news since the revised stock price always falls below the manager’s private valuation. As a result, managers disclose good news that simply increases the stock price to the level from before the industry restatement. The empirical prediction then is that simply experiencing a negative stock price contagion, rather than the magnitude of the negative contagion as in my hypothesis, is positively associated with the propensity to disclose good news. In Sect. 4.2 and Table 5, I provide empirical evidence suggesting that at least some of the disclosures result from withheld rather than newly received information.

Gleason et al. (2008) also provide similar evidence. I confirmed that the average one-quarter-ahead and one- and two-year-ahead analyst earnings forecasts revisions for the industry peers of the restating firms with negative market reactions are significantly negative in my sample as well (results not tabulated).

Cheng and Lo (2006) and Noe (1999), among others, use a similar approach to classifying forecasts as good news and bad news forecasts. Given that investors’ expectations change with the announcement of a peer restatement (as evidenced by the price change), using analysts’ expectations from before the peer restatement as a benchmark for classifying news as good or bad seems inappropriate in this study. Additionally, management forecasts are often released very soon after the restatement announcement, sooner than analysts revise their forecasts. Therefore, using analysts’ forecasts issued after the peer restatement as a benchmark for classifying management forecasts as good and bad news is not feasible.

In my final sample, approximately 85% of all forecasts are quarterly.

I verified the sensitivity of my results to this restriction. My main results are robust to 60 and 120 days as alternative cutoffs.

When earnings announcements dates are not available on COMPUSTAT I supplement them with First Call earnings announcement dates.

About 94% of forecasts in my final sample are forecasts of earnings.

This amounts to 5.75% of all observations. The fraction seems within the range documented by prior research. Anilowski et al. (2007) show that 11–25% of firms issue at least one forecast per year in my sample period 1997–2002. However, I measure disclosure over a much shorter horizon than a year (my measurement window starts on the day of the restatement announcement and ends one day before the quarterly earnings announcement—47 days on average).

In their study the mean and median contagion effect is −0.5%. However, Gleason et al. exclude from their sample peers of those restating firms for whom the three-day announcement period abnormal stock return is ≥ −1.0%.

Generally, when restatements are split into groups based on the accounting reason for the restatement (as defined in GAO 2002), the sign of the mean contagion effect is consistent with the sign of the restating firm’s returns. Based on my analysis (not tabulated), restatements due to improper accounting for acquisitions and mergers, securities, and in process research and development are notable exceptions. Since these restatements seem the most likely to result in a contagion effect measured with error, I check the sensitivity of my multivariate results to the exclusion of each one of these three groups of industry peers from my sample. My results remain qualitatively unchanged.

Note that my sample selection criteria exclude restatement announcements that are preceded by another industry restatement within 90 days before the announcement. However, once the restatement announcement satisfies the sample selection criteria, I incorporate in the sample all industry peers of the restating firm, including industry peers that restate their own financial statements subsequently. Importantly, none of those subsequently restating industry peers disclose good news management forecasts.

Prior literature provides plentiful evidence supporting the link between litigation risk and bad news disclosure but not litigation risk and good news disclosure (see Field et al. 2005; Kasznik and Lev 1995; Skinner 1994, 1997; Trueman 1997, among others). In fact, there is some evidence that firms subject to higher litigation are less likely to disclose good news (Frankel et al. 1995). Based on prior evidence, in this study I consider the impact of litigation risk on disclosure of bad news.

See for example Francis et al. (1994).

The results from a Wald test show that there is incremental explanatory power in using this model, relative to a simple model with no interaction terms.

My main results are not sensitive to replacing the change in litigation risk with the level of litigation risk measured either with the Rogers and Stocken (2005) measure or an industry membership as an alternative measure. Following Francis et al. (1994), I defined high litigation risk industries as biotechnology (SIC codes 2833–2836 and 8731–8734), computers (SIC codes 3570–3577), electronics (SIC codes 3600–3674), retail (SIC codes 5200–5961), and computer software (SIC codes 7371–7379).

See for example Heflin et al. (2003); Bushee et al. (2004).

Controlling for the firm-specific change in volatility around the industry restatement announcement leaves my results qualitatively unchanged.

In multivariate tests, I control for a number of factors that have been shown to affect disclosure and might be correlated with the contagion effect. Univariate tests likely suffer from the correlated omitted variable problem.

My results are qualitatively unchanged when I estimate the forecast error model using Ordinary Least Squares Regression.

See for example Baginski and Hassel (1997), Bamber and Cheon (1998), McNichols (1989), Rogers and Stocken (2005), and Ziebart and Guo (2000), .

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Titel: The effect of stock price on discretionary disclosure
verfasst von: Ewa Sletten
Publikationsdatum: 01.03.2012
Verlag: Springer US
Erschienen in: Review of Accounting Studies / Ausgabe 1/2012
Print ISSN: 1380-6653
Elektronische ISSN: 1573-7136
DOI: https://doi.org/10.1007/s11142-011-9165-4

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