Managerial Incentives and the Informativeness of ...

Managerial Incentives and the Informativeness of Earnings Announcements*

Sugata Roychowdhurya

Ewa Slettenb

MIT Sloan School of Management Current Draft: December, 2009

Abstract If managers have incentives to voluntarily disclose good news early and delay bad news disclosure, and quarterly earnings announcements (QEAs) can at least partially counter these incentives, then QEAs should play a greater role in the disclosure of bad news than good news. Using returns to measure news, we find that the proportion of news concentrated around QEAs relative to non-QEA periods is significantly greater during bad-news periods than during goodnews periods. The differential informativeness of QEAs is concentrated among firms that do not provide short-horizon forecasts of current-period’s earnings, consistent with managers’ asymmetric incentives dominating concerns about litigation risk in this sample. In cross-sectional tests, we find that earnings announcements’ differential informativeness in bad-news periods is more pronounced among firms characterized by greater information asymmetry between managers and investors, and by insider sales of firm stock. Time-series analysis reveals that there is a significant increase in the proportion of bad news that is concentrated at QEAs with the passage of Regulation Fair Disclosure, and an increase in the proportion of good news concentrated around QEAs with the passage of the Sarbanes Oxley Act.

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This paper was previously circulated as “The Disciplinary Role of Earnings Information”. We thank our editor Jerry Zimmerman and an anonymous referee for their suggestions and comments. The paper has also benefited from comments given by Derek Johnson, Mozaffar Khan, S.P. Kothari, Dawn Matsumoto, Bill Mayew, Shiva Rajgopal, Konstantin Rozanov, Terry Shevlin, Thor Sletten, Rodrigo Verdi, Ross L. Watts, Joe Weber, the participants at the HBS-MIT, and the University of Toronto Conferences, and seminar participants at Boston College, George Mason University, University of Chicago, University of Minnesota, University of Washington, Washington University at St. Louis, University of Southern California, and Ohio State University. a E52-343B, [email protected] b E52-325C, [email protected]

1. Introduction In this paper, we are interested in the information conveyed by earnings incremental to that conveyed by alternate sources, and how earnings’ incremental information content varies across bad-news periods relative to good-news periods. We define earnings’ incremental information as the news reaching the market during the earnings announcement, relative to that reaching the market during the non-announcement period. We hypothesize that earnings counter managers’ asymmetric incentives to voluntarily disclose good news early and delay bad news disclosure by conveying greater incremental information in bad-news periods than in good-news periods. Managers’ asymmetric voluntary disclosure incentives are widely discussed in the literature (Miller 2002, Kothari, Shu and Wysocki 2008, Sletten 2009). As firm insiders, managers are often in the possession of information unavailable to external stakeholders such as investors. When the information privately observed by managers is good, they have incentives to release the good news voluntarily to the market either through earnings forecasts or nonearnings-related disclosures (such as those about favorable business conditions, new contracts acquired, etc.). Favorable stock price responses to good news disclosures benefit managers both directly (via their compensation packages) and indirectly (via reputation effects). When the information privately observed by managers is bad, they are more likely to consider delaying its disclosure. Delayed disclosure allows managers time to take corrective action, if possible, to reverse the effect of the bad news, and avoid compensation and reputation costs. It also allows for the possibility that subsequently received good news offsets the bad news. We propose that the earnings reporting process is an important factor countering managers’ asymmetric disclosure incentives. Specifically, we expect that an important

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consequence of the earnings reporting process is that earnings play a greater role in the release of bad news to the market relative to good news. Earnings represent a summary performance measure that is the product of financial statement information prepared according to generally accepted accounting principles (GAAP). GAAP earnings are expected to provide a “true and fair” description of the firm’s performance in a given period subject to materiality and verifiability. They are scrutinized by external fiduciary agents such as outside directors and auditors. These external agents’ reputational capital is tied to their ability to understand managers’ asymmetric incentives and identify possibly adverse circumstances affecting the firm. Further, listed firms’ financial reporting is regulated, with significant costs for firms and managers via regulatory investigations, restatements and personal penalties if accounting practices deviate significantly from acceptable norms.1 In general, the preparation of financial statements at the end of every fiscal period is likely to result in the identification and release of negative information that managers have been less forthcoming about. The primary example of earnings announcements conveying negative information is when realized earnings fall short of prevailing expectations, and investors revise their opinion of current and future firm performance. Further, even when earnings meet/beat expectations, capital markets’ scrutiny of current earnings and other operational information concurrently released by managers, for example via conference calls, can generate negative information. Collectively, (a) managers’ asymmetric disclosure incentives, (b) GAAP measurement principles underlying the earnings reporting process and (c) capital markets scrutiny of earnings releases generate our primary hypothesis: earnings’ incremental information content is higher in bad-news periods relative to good-news periods.

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See Dechow et al. (1996) and Feroz et al. (1991) for consequences of SEC investigations and Desai et al. (2006) and Palmrose et al. (2004) for those of earnings restatements.

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Empirically, earnings’ greater informativeness in bad news periods is not necessarily a foregone conclusion, for a number of reasons. First, managers can use their discretion over accruals and real activities to prevent earnings from releasing adverse information (Dechow et al. 2009, Fields et al. 2001, Roychowdury 2006). Second, not all bad news necessarily affects current-period earnings, for example, the negative outcome of a product trial.

Third, the

literature discusses alternate mechanisms that counter managers’ asymmetric disclosure incentives. For example, Skinner (1994) and Anilowski et al. (2007), among others, discuss managers’ incentives to pre-empt negative surprises at impending quarterly earnings announcements (QEAs) via short-horizon earnings forecasts, to avoid litigation risk. Thus, whether there is an incremental role for earnings in conveying bad news relative to good news is an empirical question. Existing empirical evidence on the greater informativeness of earnings during bad-news periods relative to good-news periods is lacking. There is substantial discussion and evidence in the literature on earnings’ greater timeliness in recognizing bad news than in recognizing good news (see Basu 1997), a phenomenon commonly referred to as asymmetric timeliness of earnings, or conditional conservatism (Beaver and Ryan 2005). The Basu asymmetric timeliness measure, used in a large number of studies such as Leone, Wu, and Zimmerman (2006), LaFond and Roychowdhury (2008), and Lafond and Watts (2008), does not capture the timing of the news release, in particular, does the bad news release happen at the time of the earnings announcement? In fact, Basu (1997) uses returns as a measure of news and empirically specifies earnings as a function of returns, under the assumption that returns lead earnings. Thus, the notion in Basu (1997) is that earnings, for purposes of contractual efficiency, is more timely in recognizing bad news that is possibly already available to the market.

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Our tests explicitly involve the timing of the news release. We test whether, when the overall news is negative, a greater proportion of it is released at the time of the earnings announcements than when the news is positive. Empirical support for this hypothesis would suggest that earnings directly addresses the information asymmetry between managers and investors by releasing information that was not available prior to the earnings announcements, particularly the negative information that managers have incentives to withhold. The underlying hypothesis generates the cross-sectional prediction that earnings’ greater role in conveying bad news relative to good news should be more pronounced when the information asymmetry between managers and investors is more severe. Further, we predict that earnings’ differential informativeness is more pronounced in periods in which managers have greater incentives to delay bad news disclosures because they are net sellers of stock. The research design in this paper allows for earnings’ informativeness to vary with the issuance of voluntary pre-announcements of bad news via short-horizon forecasts. Among firms without short-horizon forecasts, litigation risk is either not high enough to induce early disclosure, or is outweighed by other concerns; we expect earnings to play a greater role in conveying bad news during QEAs among such firms. Finally, we identify firms whose earnings miss expectations as instances when managers either do not have enough accounting flexibility to manage earnings up to meet/beat expectations, or are unwilling to exploit that flexibility. We predict that earnings’ differential informativeness during bad news periods is more pronounced for such firms. In the empirical tests, we condition on the sign of news reaching the market in a given fiscal quarter. Using returns to measure news, we identify negative-return (positive-return) quarters as periods when bad news (good news) reaches the market. We use returns in the three

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days around earnings announcements to capture the incremental information released by earnings. Using a sample of 150,618 firm-quarters over the period 1987-2006, we find results consistent with our primary prediction: the proportion of news released during quarterly earnings announcements (QEAs) relative to that released during the non-QEA period, is greater in badnews quarters than in good-news quarters.2 Our cross-sectional results indicate that the differential informativeness of QEAs in badnews periods is greater among firms with higher information asymmetry, in periods with net insider sales, and among firms that miss earnings expectations. Additionally, to examine the role of litigation risk, we compare firms that issue short-horizon forecasts to firms that do not. We find that, as expected, the incremental informativeness of QEAs in bad-news periods is particularly pronounced in firm-quarters without short-horizon forecasts. In contrast, there is no evidence of QEAs’ increased informativeness during bad-news periods among firm-quarters with short-horizon forecasts. Interestingly, quarterly returns for firms that issue short-horizon forecasts are significantly more negative than for firms that do not.3 Collectively, the evidence suggests that managers tend to pre-empt bad news only when the news is particularly negative and litigation risk is high. In a majority of cases, when the magnitude of bad news is relatively low, QEAs serve the role of countering the asymmetric disclosure incentives of managers.4

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For the overall sample, the ratio of news released around QEAs to that in non-QEA periods is around 30% for good-news periods; the corresponding news ratio is around 34.5% for bad-news periods. For a more recent subsample in the post-SOX period, the news ratios are higher, at 38% for good-news periods and 43% for bad-news periods. 3 Focusing on firms experiencing bad news, mean (median) returns for bad-news firm-quarters with short-horizon forecasts are around -20.75% (-17.52%), while mean (median) quarterly returns for bad-news firm-quarters without short-horizon forecasts are around -15.93% (-12.50%). 4 A priori evidence suggests that pre-emption of bad news via short-horizon forecasts is not pervasive. The proportion of firm-quarters with short-horizon forecasts in our sample is relatively low even in the post-REG FD period, at 11% (20% value-weighted). This is lower than the proportion of firm-quarters in our sample that report negative quarterly returns (47%, 48% value-weighted) or even negative earnings-announcement returns (49%, 47% value-weighted), indicating that a relatively large proportion of firms do not pre-empt bad news. Kasznik and Lev (1995) also point to the high percentage of firms with negative earnings surprises that do not issue any earnings warnings.

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In time-series analysis, we examine shifts in the informativeness of earnings announcements with the passage of Regulation Fair Disclosure (or REG FD) and the Sarbanes Oxley Act (SOX). We find that there is a significant increase in the proportion of bad news that is concentrated at QEAs with the passage of REG FD, suggesting that the relative importance of QEAs in conveying bad news increased post REG FD. In the post-SOX period, there is an increase in the proportion of good news concentrated around QEAs, suggesting that SOX restrained managers from providing early voluntary disclosures of good news. In supplementary tests, we provide evidence that our measure of differential informativeness of QEAs across bad-news and good-news periods is distinct from the commonly-used Basu (1997) measure of conservatism, asymmetric timeliness of earnings. In particular, it is well-documented that large negative special items of firms are associated with greater asymmetric timeliness of earnings (see for example Frankel and Roychowdhury 2009). We document that QEAs’ differential infomativeness in bad-news periods is not higher when firms report negative special items, unless their incidence coincides with an earnings miss. Intuitively, negative special items convey negative information only to the extent that they are unanticipated. On the other hand, the Basu asymmetric timeliness measure is high for all negative special items, and not incrementally so for those associated with earnings misses. The tests confirm that the Basu measure and QEAs’ differential informativeness capture different aspects of earnings timeliness. Finally, we examine the informativeness of 10-Q and 10-K filing dates, since the full set of financial statements become available to the market on these dates. The results indicate that filing dates are, in general, less informative than QEAs; however, they also exhibit differential informativeness across bad-news and good-new periods.

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Our paper contributes to the existing literature by highlighting earnings’ informational role in mitigating the adverse selection problem in disclosure that arises in high-information asymmetry environments. Kothari, Shu and Wysocki (2008) and Sletten (2009) document empirical evidence consistent with asymmetric incentives to expedite good news releases and delay bad news releases in managers’ voluntary disclosures. A number of academics (Watts and Zimmerman 1976, Watts 2003, Beyer et al. 2009, Armstrong et al. 2009) have pointed to the possibility that GAAP measurement rules and the auditing process underlying financial reporting have evolved over time to provide numbers that counter managers’ asymmetric incentives to be more forthcoming with good news than bad news. Beyer et al. (2009) refer to this as earnings’ “disciplinary” role in providing verifiable information, and point out the general lack of empirical evidence on this disciplinary role. Direct evidence on the informational role of earnings is particularly critical at this point in time, as the FASB considers changing the measurement rules for earnings to more neutral, fair-value based standards (see Kothari et al. 2009), presumably for the purpose of making earnings more informative. This is based on the view that current GAAP earnings are untimely, and hence not valuable as a source of information.5 Our findings indicate that the current measurement rules and practices serve an important purpose: they increase the informational efficiency of the capital markets by countering the asymmetric disclosure incentives of managers, particularly when litigation risk is not high enough to induce voluntary bad-news disclosure. The rest of the paper is organized as follows. In Section 2, we develop our hypotheses. Section 3 describes the data, descriptive statistics and empirical design. Results are presented in Section 4, and Section 5 concludes. 5

This view is reflected in some academic literature as well (see for example, Ball and Shivakumar 2008).

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2. Hypothesis Development 2.1 Earnings Differential Disclosure Role The hypotheses in this paper are developed under the maintained assumption that managers have incentives to disclose privately received good news in a timely manner, and to delay disclosure of privately received bad news to the extent possible. This assumption is widely discussed in the literature in the context of disclosures about firm performance over both long and short horizons (see Lang and Lundholm 2000, Miller 2002, Kothari et al. 2008, Sletten 2009).6 The literature also discusses some mechanisms that can offset managers’ asymmetric disclosure incentives (Skinner 1994, Soffer et al. 2000, Matsumoto 2002, and Richardson et al. 2004). These studies argue that managers have incentives to pre-empt impending negative earnings surprises by disclosing bad news early, to avoid litigation risk or to enjoy reputation benefits. However, the incentives to disclose bad news early are not similar across all firms or managers; our study simply suggests that they can, in certain cases, be dominated by the incentives to delay bad news disclosure. To understand managers’ incentives to delay bad news disclosures relative to good news disclosures, we discuss two explicit scenarios. First, consider the case when managers possess privately-observed good news. Immediate disclosure generates favorable stock price response, which benefits managers directly via compensation packages and indirectly via reputation effects. This makes managers more likely to release good news early, via earnings forecasts and/or non-earnings-related disclosures such as press releases about favorable business conditions, new contracts acquired, etc. In the second case, on privately observing bad news,

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In some limited instances, such as when managers receive option grants, they can have incentives to delay good news disclosures and release bad news early (Yermack 1997, Aboody and Kasznik 2000).

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managers have incentives to first take corrective action, since immediate disclosure can lead market participants to attribute the bad news to lack of managerial skill and effort. Managers can also have incentives to wait for future offsetting good news, generating delays in bad-news disclosure. One impediment to this delay is the earnings information released at quarterly earnings announcements (QEAs). It is likely that managers are unable to reverse or offset all the bad news they privately observe by the time of the QEA. To the extent that the bad news observed by managers has consequences for current-period earnings, it is disclosed when current-period earnings are released at the time of the QEAs, via negative earnings surprises. Disclosure of previously withheld bad news is likely at the QEAs for a number of reasons. First, earnings are the product of financial statement information prepared according to generally accepted accounting principles (GAAP) which requires the disclosure of any privately received news subject to materiality and verifiability requirements, irrespective of the sign of the news.7 While the flexibility within GAAP provides managers significant discretion in their accounting choices, the reversing nature of discretionary accruals (see Xie 2001) implies that it is difficult to sustain earnings management across multiple successive periods without significantly increasing the probability of detection (Barton and Simko 2002). Financial reporting by listed firms is regulated, with significant costs for firms and managers via regulatory investigations, restatements and personal penalties if accounting practices deviate significantly from acceptable norms (Dechow et al. 1996, Feroz et al. 1991, Palmrose et al. 2004). Second, unlike most voluntary disclosures (e.g., management forecasts), financial statement information is scrutinized by external agents such as outside directors and auditors 7

In practice, the verification requirements imposed for the recognition of bad news are likely to be less strict than those imposed for the recognition of good news. See, for example, Basu (1997), Watts (2003), and LaFond and Roychowdhury (2008).

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before the earnings release. Auditors’ and outside directors’ reputations are tied to their ability to understand managers’ asymmetric incentives and uncover adverse information, as well as managers’ attempts to conceal this information via accrual choices. Failure to do so can result in lawsuits and regulatory penalties in addition to reputation loss, as with Arthur Andersen’s failure to highlight irregular accounting practices at Enron in 2001.8 The checks and balances imposed on financial statement information imply that earnings numbers can at least partially offset managers’ incentives to delay disclosures by reporting negative information, particularly regarding current-period performance. Examples include earnings alerting the market about sales declines, increases in administrative costs etc. Additionally, various earnings components such as bad debt provisions, warranty expenses, inventory write-offs and fixed asset impairments require managers to make estimations of future cash flow losses based on their private information. These features of earnings are welldiscussed in the literature (see, for example, Watts and Zimmerman 1976), and often referred to as examples of accounting conservatism. In conjunction with conservatism in the accounting standards, the checks and balances in the financial reporting process discussed above have an important implication regarding the incremental information content of earnings. We expect earnings to play a greater role in releasing bad news to the market than in releasing good news. Specifically, the proportion of overall news reaching the market in a fiscal period that is released at the time of the earnings announcement relative to that released during the non-announcement period is higher when the overall news is negative than when it is positive. There is a significant literature on the incremental information content of earnings announcements (Beaver 1968, Bamber 1987), but evidence on earnings’ greater informativeness during bad-news periods is lacking. Basu (1997) documents that earnings exhibits greater 8

See for example, Krishnamurthy et al. (2006).

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timeliness in recognizing bad news than in recognizing good news. The Basu asymmetric timeliness measure, however, does not capture the timing of the news release within a fiscal period. Thus, earnings’ asymmetric timeliness with respect to bad news as measured in Basu (1997) can be high even when there is no release of bad news at the earnings announcements, but earnings are more highly associated with bad news reaching the market prior to the announcement. Since only news released at the time of the earnings announcements can be interpreted as earnings’ incremental information content (Beaver 1968, Basu and Shivakumar 2008, Beyer et al 2009), the Basu (1997) measure is inadequate for capturing earnings’ differential informativeness during bad-news versus good-news periods. McNichols (1988) compares earnings announcements returns to returns during similarlength windows in non-announcement periods and finds that the former are less positively skewed. Interestingly, she also reports that the percentage of announcement returns that are negative is lower than the corresponding percentage of negative returns during comparable windows in non-announcements periods. Thus, the evidence in McNichols (1988) is insufficient to conclude whether earnings announcements are proportionately a more important source of bad news than good news. We condition on the sign of the news reaching the market during a fiscal period, and measure QEA informativeness as the proportion of news reaching the market at the time of the QEA relative to that reaching during the non-QEA period. Our first hypothesis can be formally stated as follows:

H1: QEA informativeness is higher when the overall news is negative than when it is positive.

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H1 is based on asymmetric managerial incentives to delay disclosure of bad news relative to good news, under the assumption that the flow of bad news and good news privately observed by the manager is reasonably uniform and not significantly different from each other. It is of course possible that bad-news events are by nature more “lumpy” than good-news events. Greater “lumpiness” of bad news arrival than good news arrival is an alternate explanation for our empirical predictions only if it is additionally true that bad news has a systematically greater tendency than good news to arrive during earnings announcements. This, however, is likely only to the extent that managers wait till the QEAs to discover bad news, and/or the earnings reporting process inclusive of auditor scrutiny uncovers bad news at the time of the QEAs, both of which are consistent with our hypothesis. We expect support for H1 to be particularly strong among firms where factors such as litigation risk are not severe enough to induce managers to disclose impending earnings disappointments early. Anilowski et al. (2007) report that most early disclosures of impending bad news occur via management forecasts of current-quarter’s earnings issued after the previous quarter’s earnings announcement, or short-horizon forecasts. We test whether differential informativeness of QEAs during bad-news periods is more pronounced among firms not issuing such forecasts.

Additionally, the differential informativeness of QEAs in bad-news quarters is likely to be especially high for firms that miss earnings expectations. Earnings misses represent the primary examples of bad news releases at the time of the QEA. They are consequential events, since they can lead investors to revise estimates of future performance and cash flows downwards. Further, firms with earnings below expectations represent clear instances where managers are either unwilling to manage earnings to meet or beat expectations, or the lack of

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flexibility to do so. Consequently, we test whether earnings play a proportionately greater role in releasing bad news for such firms.

2.2 Cross-Sectional Variation We investigate two sources of variation in the differential role of earnings announcements in conveying bad news relative to good news. The first factor is the degree of information asymmetry between managers and shareholders. In firms where the information asymmetry is greater, shareholders are less likely to be cognizant of managers’ privately observed news. This provides managers a greater information advantage that they can exploit upon privately observing bad news. We expect that the greater the information asymmetry, the greater is the opportunity for managers to delay bad news disclosures, and the more pronounced is the role of QEAs in disclosing bad news relative to good news.

H2: QEAs’ differential informativeness during bad-news periods relative to good-news periods is higher among firms with greater information asymmetry between managers and shareholders.

Our basic hypothesis (H1) does not necessarily require that managers are opportunistic, or strategic with respect to their own short-term monetary incentives; their asymmetric incentives to delay bad news disclosures could arise from the perceived benefits of first attempting to reverse the bad news. However, managers’ incentives can also be opportunistic, as when managers are net sellers of stock in a given period. There is significant evidence in the literature that, at the time of insider trades, managers possess undisclosed private information (Seyhun 1986, Noe 1999, and Ke et al. 2003), and in particular, private information regarding future earnings (Beneish and Vargus 2002 and Piotroski and Roulstone 2005). Thus, it is likely that, in some cases, managers possess negative

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information at the time of the insider sale. If negative quarterly returns are a good proxy for the managers’ privately observed bad news, we expect that managers’ incentives to delay disclosure to the extent possible are stronger in the negative-return quarters in which they are also net sellers of stock. 9 Thus, we predict that the incremental informativeness of QEAs in bad-news periods relative to good-news periods is more pronounced in firm-quarters with net insider sales.

H3: QEAs’ differential informativeness during bad-news periods relative to good-news periods is higher in those periods that include net insider sales of firm stock.

2.3 Time-Series Variation We investigate the effect of two regulatory events that are likely to have had a significant influence on the informativeness of QEAs in good versus bad periods. The first event is the passage of Regulation Fair Disclosure (REG FD), effective since the fourth calendar quarter of 2000; the second is the passage of the Sarbanes Oxley Act (SOX), effective since the third calendar quarter of 2002. The academic literature has mixed findings on the effect of REG FD on voluntary disclosure. While there is consensus that it largely succeeded in its direct objective of limiting selective disclosure (see Gintschel and Markov 2004, Mohanram and Sunder 2006), there is also evidence suggesting that REG FD adversely affected the informativeness of voluntary disclosures. For example, Wang (2007) provides evidence consistent with firms reducing voluntary disclosures in response to REG FD, with a concurrent increase in information asymmetry. The results in Chen et al. (2005) suggest that poor-performing firms who reduce 9

Generally, the evidence suggests that insider purchases are more likely to be motivated by private information than insider sales, presumably due to litigation risk (Cheng and Lo 2006, Roulstone 2008, Piotroski and Roulstone 2008). In our sample of firm-quarters with net insider sales, only 48% exhibit negative quarterly returns, suggesting that negative private information is an unlikely motivator for net insider sales. However, conditional on possessing negative information, managers can still have incentives to delay disclosing that information.

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voluntary disclosures post-REG FD experience increased systematic risk, increased analyst forecast dispersion, and decreased analyst forecast accuracy. Chen et al. (2005) also find that prices lead earnings less once guidance is eliminated. Further, while the frequency of management forecasts has generally increased post-REG FD, the proportion of short-horizon forecasts releasing bad news has declined (from 64% in the pre-REG FD period to 57% in the post-REG FD period in our sample).10 The time trends in voluntary disclosure suggest that it is important to examine changes in QEA informativeness with the passage of REG FD. The second regulatory event we examine is SOX. SOX made CEOs and CFOs’ responsibility towards faithful disclosure in financial statements more explicit by requiring certification that, based on their knowledge, their annual and quarterly financial statements fairly describe the financial condition of the company (subject to materiality).11 The criminal prosecutions and disgorgement initiations against managers of firms such as Enron, Worldcom and Adelphia, and the disintegration of audit firm Arthur Andersen likely generated a heightened awareness of the reputation and litigation costs borne by managers and auditors in the post-SOX period.12 We expect that SOX provided both managers and auditors with greater impetus to incorporate adverse information in reported earnings numbers and to be more forthcoming in

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Consistent with the rest of the paper, news content of forecasts is measured using the three day buy-and-hold returns centered on the voluntary disclosures. 11 Section 302 of the Sarbanes Oxley Act explicitly states that “the principal executive officer or officers and the principal financial officer or officers, or persons performing similar functions” are required to certify “in each annual or quarterly report” that, based on the officer’s knowledge, “the report does not contain any untrue statement of a material fact or omit to state a material fact”, and that the financial statements, and other financial information included in the report, “fairly present in all material respects the financial condition and results of operations of the issuer” of the report. 12 The criminal prosecutions ultimately led to prison sentences for managers for up to twenty five years, as for Bernie Ebbers of Worldcom (see for example, CNN Money, 9/23/2005).

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conference calls.13 However, the stricter regulatory climate prevailing in the post-SOX era could also have affected managers’ voluntary disclosure policies in the non-QEA period. In particular, it is possible that managers become more cautious about voluntarily disclosing good news, or about delaying the disclosure of bad news in the post-SOX period. The net effect of these forces on QEAs’ differential informativeness in bad-news periods is an empirical question.

3. Data, Empirical Proxies and Descriptive Statistics 3.1 Data To construct our sample, we begin with all firm-quarters in COMPUSTAT with sufficient data to calculate market value of equity (MVE), book value and leverage. We also require daily returns data from CRSP to compute quarterly returns, earnings announcement returns, and idiosyncratic firm volatility. Analyst following and institutional ownership are obtained from I/B/E/S and Thomson Financial respectively, and are set equal to zero when not available. Finally, our measure of information asymmetry includes the adverse selection component of the bid-ask spread which is measured using the intraday trades and quotes from the NYSE Trades and Quotes database (TAQ). Since common coverage in these databases starts in 1987, our sample includes 150,618 firm-quarters over the 80 quarters from 1987 to 2006, and comprises 10,216 individual firms. In additional tests, we supplement our data with management forecasts obtained from First Call. Since First Call provides little coverage in early years, our additional tests incorporate firm-quarters starting from 1995.

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Cohen et al. (2008) document evidence consistent with firms having less flexibility in reporting earningsincreasing discretionary accruals in the post-SOX period.

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3.2 Measuring informativeness of earnings announcements We measure news using equity returns. Earnings announcement returns (EARt) are defined as the market-adjusted buy-and-hold returns over the three days from day -1 to day +1, where day 0 is the quarterly earnings announcement (QEA). Quarterly returns (RETt) are defined as the market-adjusted buy-and-hold returns starting two days after the earnings announcement of quarter t-1 and ending one day after the announcement of quarter t.14 The mean length of the period over which RET is computed is around 63 trading days. Non-earnings-announcement returns (NEAR) are estimated as (1+RET)/(1+EAR) - 1.15 We measure QEA informativeness using a ratio of the news arriving during the QEAs to that arriving during non-QEA periods, denoted as NEWS_RATIO, and defined as 100*ABS(EAR) / ABS(NEAR). The ratio expresses the absolute value of market-adjusted QEA returns, ABS(EAR), as a percentage of the absolute value of market-adjusted returns during non-QEA periods, ABS(NEAR). While we refer to NEWS_RATIO as a measure of QEA informativeness for brevity, it is important to keep in mind that it is the informativeness of QEAs relative to that of non-QEA periods.16

We require at least twenty five days with trading to compute RET. The market-adjustment involves subtracting the buy-and-hold return on the CRSP value-weighted market index from the corresponding buy-and-hold return of the firm. We also conducted robustness analyses with size and book-to-market adjusted returns, instead of marketadjusted returns. This adjustment involves partitioning firms into five equal groups of size and book-to-market, thus yielding 25 size and book-to-market portfolios. The adjusted return for a firm is then the daily raw return in excess of the daily return on the matching size and book-to-market portfolio. All our subsequent results, including those we obtain in the cross-sectional tests, are robust to using this alternate adjustment. 15 We check the robustness of our analysis to two alternate definitions of the earnings announcement window. In the first, we estimate EAR over day -3 to day +3 with respect to the QEA. In the second, we acknowledge that a longer window is especially suitable for smaller firms, and estimate EAR over day -3 to day +3 for firms below median size, while using day -1 to day +1 for firms above median size. In both specifications, the estimation of NEAR is adjusted accordingly. All our results are robust to both these specifications. 16 NEWS_RATIO is unlikely to be affected systematically by post-earnings-announcement drift (PEAD) or the under-reaction of the market to current-period dollar earnings surprises (Foster, Olsen and Shevlin 1984). PEAD implies that earnings surprises at the time of the QEAs predict returns in the following period; further, most of the “drift” return is realized at the subsequent QEAs (Bernard and Thomas 1989). Thus, in the period of the initial earnings surprise, PEAD is likely to bias the relative informativeness of QEAs downwards; in the period following the initial earnings surprise, PEAD is more likely to bias the relative informativeness of QEAs upwards. The overall effect of drift on NEWS_RATIO is thus ambiguous, and even more so when we subsequently partition on the sign of the returns. 14

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We expect NEWS_RATIO to be high during quarters when the overall news (measured by quarterly return RET) is negative relative to when overall news is positive. Our prediction is easy to follow if EAR and NEAR are always of the same sign. When EAR and NEAR are of differing signs, the analysis is more involved, but NEWS_RATIO is still expected to exhibit the same asymmetry. Specifically, for all observations consistent with our hypothesis NEWS_RATIO is expected to be systematically higher in negative-return periods and lower in positive-return periods. In contrast, for all observations inconsistent with our hypothesis, NEWS_RATIO is expected to exhibit the reverse pattern. Thus, variation in NEWS_RATIO is well-suited to testing whether the relative informativeness of QEAs is higher when overall information reaching the market is negative. This is discussed in greater detail in Appendix 1,

3.3 Measuring information asymmetry We are primarily interested in a measure of information asymmetry that captures managerial opportunities to withhold bad news from external investors. To measure the degree of information asymmetry between managers and external investors, we use a principal components analysis to extract the common variation in five variables: (a) logarithm of firm size, defined as market value of equity, (b) logarithm of one plus analyst following, defined as the number of analysts covering the firm, (c) institutional ownership, or the percentage of outstanding shares owned by institutions, (d) idiosyncratic return volatility, and (e) the adverse selection component of the bid-ask spread. Certain firm types are associated with a large number of investors and/or other market participants tracking the firms’ operations, investments, etc. Such firms are typically characterized by large size and analyst following. We expect such firms to experience less information asymmetry between managers and investors, a consequence of both market

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participants’ greater efforts to uncover information, and managers’ greater willingness to be forthcoming with information (see, for example, Collins et al. 1987). 17 Sophisticated investors are likely to better understand the asymmetric disclosure incentives of managers, making the former more demanding of timely disclosures of adverse information. Additionally, sophisticated investors such as institutions tend to be the price-setters in the market (Gompers and Metrick 2001), which makes managers more responsive to their information demands. Greater idiosyncratic volatility is generally reflective of greater uncertainty about a firm’s operations. While this uncertainty can affect both managers and investors, it is likely to make any managerial information advantage less detectable ex post by external investors. Finally, the adverse selection component of the bid-ask spread measures the extent to which the bid-ask spread quoted for the firm reflects the market makers’ attempts to protect themselves against informed trading and is widely used as a measure of information asymmetry (Foster and Vishwanathan 1993, Brennan and Subrahmanyam 1996). The principal components analysis of the above five variables yields a composite measure of information asymmetry between managers and shareholders, denoted InfoAsymm. InfoAsymm is negatively associated with firm size, analyst following and institutional ownership, and positively associated with idiosyncratic volatility and the adverse selection component of the bid-ask spread. Thus, higher values of the composite measure InfoAsymm represent greater information asymmetry.

17

Note that factors such as size that capture the overall information environment of the firm are also likely to be positively associated with the litigation risk facing managers (Field et al. 2005). However, to the extent that litigation risk ameliorates the adverse selection problem in disclosure by compelling managers to disclose bad news early, we consider it a component of the overall information environment of the firm.

19

3.4 Firm characteristics: variable definitions and descriptive statistics Table 1 presents the pooled means and medians of key variables for our overall sample, as well as the sub-samples representing good-news periods and bad-news periods. Good and badnews periods are identified by the sign of overall quarterly return RET and characterized by the indicator variable BNEWSt which is set equal to one if RETt < 0 and is equal to zero otherwise. Thus BNEWS=1 corresponds to bad-news periods while BNEWS=0 identifies good-news periods. RET is measured over the entire quarterly period (63 trading days on average); the nonearnings-announcement-period return NEAR spans on average a 60-day trading period, excluding the three days around the QEA, and hence corresponds closely to RET. The mean values of RET, EAR and NEAR for the overall sample tend to be more positive than the corresponding medians, which is expected given that the returns are bounded below by -100% and thus tend to be rightskewed.18 As Table 1 demonstrates, the mean and median magnitudes of earnings announcement returns ABS(EAR) are larger in bad-news periods than in good-news periods.

The mean

magnitude of non-announcement returns ABS(NEAR), on the other hand, is lower during badnews periods than good-news periods, while the median magnitudes look largely similar. Highlighting that QEAs are more likely to convey adverse information during bad-news periods, negative earnings announcement returns tend to occur more frequently in periods that RET is negative. Mean BAD_EAR, an indicator variable set equal to one if EAR < 0 is 39.8% in good-news periods and 59.34% in bad-news periods. Confirming this trend, the mean value of MISS, a binary indicator set equal to one if a firm’s earnings are below expectations and zero otherwise, indicates that the probability of firms missing earnings expectations is lower in good-

Strictly speaking, since the returns are market-adjusted, negative RET, EAR and NEAR can be more than 100% in magnitude. Empirically, in our sample, there is no observation of RET, EAR or NEAR that are below -100%.

18

20

news periods (26.2%) than in bad-news periods (44.2%). In computing MISS, expected earnings are set equal to consensus analyst expectations if analyst data are available; otherwise they are based on a seasonal random walk.19 The generally higher means for BAD_EAR relative to MISS suggest that QEAs can convey bad news even when earnings meet or beat expectations, as when investors suspect earnings management, or if earnings gains are expected to be transitory. This can happen when investors scrutinize supplemental information disclosed with earnings releases, or in conference calls, considered “standard practice” in recent times (Tasker 1998, Frankel et al. 1999, Bushee et al. 2003, Skinner 2003).20 The rest of Table 1 reports statistics on a number of firm characteristics. SIZE is defined as the market value of equity, analyst following (NUM_AN) is the number of analysts covering the firm, and institutional ownership (INST_OWN) is the percentage of outstanding shares owned by institutions. Idiosyncratic volatility (IVOL) is computed as the volatility of daily firm returns in excess of market returns in the preceding quarterly period, but excluding the earnings announcement. The adverse selection component of the bid-ask spread (Adv_BidAsk) is computed as the daily average over the last month of the preceding quarter. In computing Adv_BidAsk we follow Brennan and Subhramanyam (1996), who estimate the sensitivity of price changes to order flow based on a model of price formation developed by Hasbrouck (1991).21 BTM is the ratio of the book value of equity to market value of equity and financial leverage LEV is computed as the ratio of total debt to total assets. All firm characteristics are measured at the beginning of the period. The descriptive statistics demonstrate that these firm characteristics generally appear to be similar between good-news and bad-news periods. 19

The consensus analyst expectation is the mean across the final forecast provided by each analyst. Using the median consensus analyst forecast yields similar results. 20 Another possibility is that the earnings expectation models are flawed, particularly those based on seasonal random walk. For a restricted sample of firms with available analyst expectations, we observe the same pattern. 21 Also see Ng et al. (2009).

21

Following Field et al. (2005) we define HITECH as a binary indicator variable that is set equal to one if the firm belongs to the following four-digit SIC industry codes, signifying technology-intensive industries: 2833–2836 (drugs and pharmaceuticals), 3570–3577 (computer and office equipments), 3600–3674 (electrical equipment and electronics), 7371–7379 (software services) or 8731–8734 (R&D services). As the mean value of HITECH shows, 25.1% of the bad-news firm-quarters belong to technology-intensive industries, while the corresponding percentage is 23.3% for the good-news firm-quarters. Finally, INSALE is a binary zero/one indicator set equal to one if insiders have net sales of stock in a given firm-quarter. Net insider sales are measured as the stock sales minus stock purchases across directors and firm executives identified as officers.22 Table 1 indicates that insider sales are slightly less frequent in bad-news periods, where their frequency is around 31.0%, than in the good-news periods, where their frequency is around 35.5%.

3.5 Univariate Analysis of NEWS_RATIO Table 2 reports descriptive statistics on our key variable of interest NEWS_RATIO, separately for the firm-quarters with overall negative returns and those with overall positive returns. We compute the mean and median ratio for every fiscal quarter across the two subsamples, and for each summary measure report the mean of difference across all quarters, along with the associated standard error. We observe that mean NEWS_RATIO is actually higher for good-news quarters than bad-news quarters (Column 1), contrary to our prediction, although the difference is significant only at the 10% level. On the other hand, the median NEWS_RATIO is higher for bad-news quarters than good-news quarters (Column 2), and the difference is significant at the 1% level. Comparing the two summary statistics (means and medians) reveals 22

We exclude divisional officers and officers of subsidiary companies in estimating net insider sales.

22

that the mean ratios tend to be much higher in magnitude than the median ratios. For example, the median NEWS_RATIO for good-news periods indicates that news released during earnings announcements is around 31% of news released during non-announcement periods, while the means indicate that the corresponding percentage is around 103%. This suggests that NEWS_RATIO is right-skewed, and the means are affected by extremely high and unrepresentative ratios potentially driven by low denominators. To address this issue, we compute the natural logarithm of the ratio, denoted Ln(NEWS_RATIO). Columns 3 and 4 in Table 2 respectively report the differences in mean and median Ln(NEWS_RATIO) between bad-news quarters and good-news quarters. Using means and medians of Ln(NEWS_RATIO), we obtain consistently higher values of the ratio for bad-news quarters than good-news quarters, with the differences being statistically significant at the 1% level. Further, consistent with the logged ratio having a more symmetric distribution, the means and medians of the logged ratio yield similar values. To see this, note that the implied NEWS_RATIO for bad-news quarters using the means of the logged ratio is around 34.5% while using the medians it is around 36%.23 The implied NEWS_RATIO for good-news quarters using both means and medians of the logged ratio is around 30%. In our subsequent regression analysis, we use Ln(NEWS_RATIO) as the primary dependent variable.

4. Regression results 4.1 The sign of news and the informativeness of QEAs We use the following regression to test whether the news released during quarterly earnings announcements (QEAs) relative to that released during non-announcement (non-QEA) periods is greater when the overall returns are negative: 23

The implied ratio is simply the exponent of Ln(NEWS_RATIO).

23

Ln(NEWS_RATIO) t = α + β*BNEWSt + εt

(1)

In regression (1), BNEWSt is an indicator variable set equal to one if overall quarterly return RETt < 0 and equal to zero otherwise. Thus, it captures whether the overall news reaching the market in a particular quarter is bad. The intercept, α, represents the mean Ln(NEWS_RATIO) for good-news quarters, while the coefficient on BNEWS, β, captures the extent to which the ratio is different for bad-news quarters. Our primary hypothesis (H1) predicts that the Ln(NEWS_RATIO) is higher when overall quarterly return RET is negative. In other words, we predict that β is significantly positive. Table 3 Model 1 reports the results of estimating the regression (1) over the entire sample of 150,618 firm-quarters. The regression is estimated in the cross-section every fiscal quarter and Table 3 reports the time series means of the coefficients and associated standard errors across the 80 quarters from 1987 to 2006 (following the Fama-Macbeth procedure). The regression results indicate that the mean Ln(NEWS_RATIO) for the good-news periods is 3.414 while the incremental coefficient on BNEWS is 0.126 and statistically significant at the 1% level. Note that the coefficients, by construction, confirm the univariate results obtained in Table 2 on the difference in Ln(NEWS_RATIO) between the bad-news and goodnews quarters. We expect the informativeness of QEAs in bad-news quarters relative to good-news quarters to be more pronounced in the sample of firms without short-horizon forecasts, that is, forecasts of current period’s earnings issued after the previous quarter’s earnings announcements. First Call’s coverage on management forecasts is substantially expanded since 1995 (see Anilowski et al. 2007). Therefore, we investigate the difference between firms with and without short-horizon forecasts after 1995. Model 2 in Table 3 includes the entire sample of

24

firm-quarters beginning in 1995, and Models 3 and 4 include the subsamples of firm-quarters with and without forecasts respectively. Mean (median) quarterly returns (RET) for firms issuing short-horizon forecasts are around -5.66% (-7.04%), while mean (median) quarterly returns for firms not issuing short-horizon forecasts are around 2.04% (-0.02%). Focusing on firms experiencing bad news (RET < 0), mean (median) returns for bad-news firm-quarters with shorthorizon forecasts are around -20.75% (-17.52%), while mean (median) quarterly returns for badnews firm-quarters without short-horizon forecasts are around -15.93% (-12.50%).24 Thus, firms with short-horizon forecasts experience more extreme bad news. The results from Model 2 indicate that our evidence on the incremental informativeness of QEAs during bad-news quarters is robust to using the 133,231 firm-quarters between 1995 and 2006. Model 3 presents results for a subset of the firm-quarters in Model 2: the 13,941 firmquarters with short-horizon forecasts. We find that for this subsample, QEAs are less informative in bad-news periods than in good-news periods. The coefficients imply that the ratio of news disclosed during QEAs to that disclosed during non-QEA periods is 24.6% in bad-news quarters, as opposed to 29.4% in good-news quarters. The results are consistent with forecasts issued in the current quarter pre-empting bad news at the earnings announcements. For the subset of the firm-quarters in Model 2 without forecasts (119,290 firm-quarters) we find strong support for H1, as indicated by Model 4. The coefficient on BNEWS in Model 4 is positive, statistically significant at the 1% level, and implies that the ratio of news disclosed during QEAs to that disclosed during non-QEA periods is 36.7% in bad-news quarters, as opposed to 31.7% in good-news quarters. Recall that by selection, in the sample of firms without any short-horizon forecast, litigation risk is not high enough to warrant early public disclosure of

All reported differences in RET between firms with short-horizon forecasts and those without such forecasts are statistically significant at the 1% level in Fama-Macbeth t-tests.

24

25

impending bad news. Our results show that in this sample, QEAs play a greater role in the disclosure of bad news.

4.2 Cross-sectional variation in the informativeness of QEAs We test the cross-sectional variation in earnings’ more pronounced role in disclosing bad news relative to good news using the following regression: Ln(NEWS_RATIO)t = α0 + α1* RInfoAsymm t-1 + α2*INSALEt + α3* MISSt + α4*RBTMt-1 + α5*RLEVt-1 + α6*HITECH t-1 + β0*BNEWSt + β1* InfoAsymm t-1*BNEWSt + β2*INSALEt*BNEWSt + β3* MISSt*BNEWSt + β4*RBTMt-1*BNEWSt + β5*RLEVt-1*BNEWSt + β6*HITECH t-1*BNEWSt + εt (2)

In the above regression, α0 captures the mean Ln(NEWS_RATIO) for good-news quarters and α1 to α6 capture the variation in α0 with six explanatory variables. Similarly β0 captures the incremental Ln(NEWS_RATIO) for bad-news quarters relative to good-news quarters, and β1 to β6 capture the variation in β0 with six explanatory variables. Our first explanatory variable, used to test H2, is RInfoAsymm. It is the quintile rank of InfoAsymm within every quarter.25 Recall that InfoAsymm measures information asymmetry between managers and shareholders, and is extracted from a principal-components-analysis that yields a measure negatively associated with firm size, analyst following and institutional ownership, and positively associated with idiosyncratic volatility and the adverse selection component of the bid-ask spread. Our second explanatory variable INSALE, used to test H3, is a binary indicator capturing whether there were net insider sales in a firm-quarter. We also include in the model an indicator variable equal to one if a firm’s earnings are below expectations (MISS) and zero otherwise. Firm-quarters with earnings below expectations 25

Using quintile ranks from 0 to 4 facilitates easier comprehension of the economic magnitude of the effect of InfoAsymm on NEWS_RATIO. Our results are qualitatively similar using the continuous variable InfoAsymm.

26

(MISS equaling one) represent instances where managers are either unwilling to manage earnings to meet or beat expectations, or the lack the flexibility to do. If our expectations model is reasonably well-specified then the informativeness of the QEAs in such firms is expected to be especially high in bad-news quarters than in good-news quarters. Note that meeting/beating expectations does not necessarily preclude firms from experiencing bad news at QEAs, as discussed in Section 2.1. Our fourth explanatory variable is the quintile rank of the book-to-market ratio (denoted RBTM). We include RBTM as a control, since Skinner and Sloan (2002) document that the announcement returns to earnings surprises can vary with the growth options of a firm. We also control for the quintile rank of financial leverage (RLEV). The use of accounting numbers in debt contracts implies greater monitoring of reported earnings by debt-holders and therefore, a potentially increased role for earnings in releasing adverse information in highly levered firms. On the other hand demand from private debt-holders in high leverage firms can be associated with release of privately received bad information earlier than earnings announcements to manage litigation risk. Our final control variable is membership in a technology-intensive industry, HITECH. Field, Lowry and Shu (2005) argue that firms in technology-intensive industries experience greater litigation risk, which can lead to firms releasing adverse information via voluntary disclosure prior to QEAs. On the other hand, the complex and volatile nature of these industries can potentially generate greater delays in bad news disclosures and a more important role for QEAs in disclosing bad news. Table 4 Model 1 presents results on cross-sectional variation for the full sample. To understand the partial effect of any of the key explanatory variables on the news ratio, consider

27

as a base scenario a firm-quarter in the lowest quintile of InfoAsymm, book-to-market and leverage, with no insider sale (i.e., INSALE = 0), and with earnings that are above expectations (i.e., MISS = 0). Ln(NEWS_RATIO) for such a firm-quarter is represented by the intercept in good-news periods and the sum of the intercept and the coefficient on BNEWS in bad-news periods. The corresponding implied NEWS_RATIO is 38% for good-news periods and 37% in bad-news periods, with no significant difference between the two. The coefficient on RInfoAsymm in Model 1 is significantly negative, implying that the informativeness of QEAs in good-news periods is declining with our measure of information asymmetry. More importantly, consistent with H2, the coefficient on RInfoAsymm*BNEWS is significantly positive at the 1% level, indicating that the differential informativeness of QEAs in bad-news periods relative to good-news periods is increasing in the degree of information asymmetry. The coefficients on RInfoAsymm and RInfoAsymm*BNEWS imply that if the value of InfoAsymm were to move from the bottom quintile to the top quintile, the asymmetry in implied NEWS_RATIO between bad-news periods and good-news periods would increase by 5 percentage points relative to the base case. Consistent with H3, the coefficient on INSALE*BNEWS is significantly positive at the 1% level, indicating that the differential informativeness of QEAs in bad-news periods relative to good-news periods is higher when there is net selling of the firm’s stock by insiders during the period. The coefficients on INSALE and INSALE *BNEWS imply that relative to the base case, when there is a net insider sale the asymmetry in the implied NEWS_RATIO increases by 5 percentage points relative to the base case. The significant results obtained with RInfoAsymm after controlling for INSALE suggest that managers’ asymmetric incentives to delay bad news disclosures relative to good news

28

disclosures are not all driven by opportunistic reasons related to their insider trades. Rather, even in periods without insider sales, managers perceive benefits to delaying bad news disclosures, for example, those associated with first attempting to reverse the bad news. Finally the coefficients on MISS and MISS*BNEWS imply that relative to the base case, when firms miss expectations, the implied NEWS_RATIO changes to 33% for good-news periods, while it changes to 41% for bad-news periods. Thus, as discussed in Section 2.1, missing expectations appears to be a significant driver of earnings announcements’ increased informativeness during bad new periods relative to good-news periods. We find no evidence of any variation in the differential informativeness of earnings announcements across good-news and bad-news periods with our control variables. Model 2 in Table 4 confirms that the results in Model 1 are robust to using the subsample of firm-quarters between 1995 and 2006. Models 3 and 4 present results for the subsets of the firm-quarters in Model 2 with and without short-horizon forecasts respectively. As expected, with early public disclosure of impending bad news (Model 3), the informativeness of QEAs does not differ significantly across good-news periods and bad-news periods. We also fail to find any significant evidence of cross-sectional variation in the informativeness of QEAs in Model 3. Model 4 demonstrates that cross-sectional variation in the differential informativeness of earnings announcements across good-news and bad-news periods is concentrated among the larger sample with no short-horizon forecasts.

4.3 Time series analysis Table 5 reports the results of our time-series tests analyzing changes in the differential informativeness of earnings announcements in bad-news periods relative to good-news periods with the passage of REG FD and SOX. We examine three sub-periods in our sample. Model 1 of

29

Table 5 includes the first sub-period: all fiscal quarters that in calendar time precede the fourth quarter of 2000 (PRE-REG-FD). Model 2 includes the second sub-period: all fiscal quarters that, in calendar time, correspond to or follow the fourth quarter of 2000 and precede the third quarter of 2002 (POST-REG-FD PRE-SOX). Model 3 includes the third sub-period: all remaining fiscal quarters that in calendar time correspond to, or follow, the third quarter of 2002 (POST- SOX). Note that the number of fiscal quarters in a given sub-period can differ from the number of calendar quarters. According to the coefficient estimates presented in Model 1, the implied NEWS_RATIO in the PRE-REG-FD sub-period is 29% for good-news periods, and 32% for bad-news periods, with the difference being statistically significant at the 1% level. Interestingly, in the second subperiod, the implied NEWS_RATIO for good-news periods is similar to that in the first at 28%, while for bad-news periods, it rises to 40%. The differential informativeness of QEAs in badnews periods (captured by the coefficient on BNEWS), and the total informativeness of QEAs in bad-news periods (captured by the sum of the BNEWS coefficient and the intercept) are both significantly different at the 1% level from the previous sub-period, using a t-test. The results suggest that the changes in the information environment induced by REG FD made QEAs’ role in conveying bad news more pronounced post-REG FD. Finally, Model 3 indicates that in the third sub-period, the implied NEWS_RATIO for good-news periods increases sharply to 38% (relative to 28% in the second sub-period), while for bad-news periods it is 43%, similar to that in the second sub-period. T-tests confirm that in the POST-SOX period, the change in QEA informativeness in good-news periods is statistically significant, but the change in QEA informativeness in bad-news periods is not. The evidence suggests that while SOX provided managers with incentives to postpone the disclosure of good

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news till the QEAs.26 The net effect is a significant decline in the differential informativeness of QEAs in bad-news periods relative to good-news periods in the post-SOX period. To investigate whether the results are affected by the increased practice of firms issuing forecasts of future earnings along with current earnings announcements (see Anilowski et al. 2007), we exclude the sample of firms that issue management forecasts along with earnings announcements. The results (untabulated) are largely unaffected for the first sub-period. In the second and third sub-periods, the changes in QEA informativeness for bad-news and good-news periods are respectively slightly less pronounced, but still significant.27 Overall the results confirm the patterns observed in Table 5.

4.4 Additional analyses 4.4.1 Differential informativeness of QEAs and the Basu asymmetric timeliness measure Basu (1997) documents that earnings are more highly associated with returns when returns are negative than when returns are positive, a phenomenon referred to as asymmetric timeliness of earnings. The Basu measure, by construction, is not affected by the timing of the news release, in particular whether the release occurs at the earnings announcements. In this section, we present evidence that the differential informativeness of QEAs discussed in this paper and the Basu asymmetric measure timeliness measure behave differently in the crosssection. Our basic regression specification is that used in Section 4.2, augmented by an indicator variable capturing the incidence of large negative special items. Prior literature points to negative 26

Consistent with our findings, Ball and Shivakumar (2008) also note the general increase in QEA informativeness with time (particularly post-SOX), although they do not condition on the sign of overall news. 27 In the PRE-REG-FD sub-period, implied NEWS_RATIOs for good-news and bad-news periods are respectively 21.23% and 31.93%. In the POST-REG-FD PRE-SOX sub-period, the implied NEWS_RATIOs for good-news and bad-news periods is respectively 26.60% and 38.81%. In the POST-SOX sub-period, the implied NEWS_RATIO for good-news and bad-news periods is 33.16% and 39.39%.

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special items such as asset write-downs as primary examples of conservative accounting (Basu 1997, Ball 2001, Watts 2003). There is empirical evidence (Frankel and Roychowdhury 2009) that large negative special items including asset write-downs and restructuring charges are associated with greater asymmetric timeliness of earnings. However, the incidence of negative special items is expected to affect the differential informativeness of QEAs, only if the special items are unanticipated by the market. We denote the incidence of negative special items by NEG_SI, a one/zero indicator variable set equal to one when negative special items identified by COMPUSTAT are greater than or equal to 1% of sales in magnitude.

The basic specification for our tests involving the Basu asymmetric timeliness measure is as follows: Et/Pt-1 = α + β*BNEWSt + η*RETt + γ*RETt*BNEWSt + εt.

(3)

In the equation (3), Et represents income before extraordinary items in quarter t, Pt-1 represents the market value of equity at the beginning of quarter t. η captures the timeliness of earnings with respect to positive returns and γ captures the asymmetric timeliness of earnings with respect to negative returns. The following regression represents the basic structure for capturing cross-sectional variation in the Basu measure: Et/Pt-1 = α0 + Σiαi*CS_VARi,t + β0*BNEWSt + Σiβi*CS_VARi,t*BNEWSt + η0*RETt + Σiηi*CS_VARi,t*RETt + γ0*RETt*BNEWSt + Σiγi*CS_VARi,t*RETt*BNEWSt +εt.

(4)

In regression (4), CS_VARi,t denotes ith variable driving cross-sectional variation in period t, and γi captures variation in the asymmetric timeliness coefficient with CS_VARi,t. In addition to the variables discussed in Section 4.2, CS_VAR also include NEG_SI.

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Table 6 reports the results of the cross-sectional estimation. Model 1 presents the results with the differential informativeness of QEAs as the dependent variable, while Model 2 presents the results with the Basu asymmetric timeliness measure. The results in Model 1 of Table 6 indicate that the incidence of negative special items without an earnings miss is negatively associated with differential informativeness of QEAs in bad news periods. The coefficient on BNEWS *NEG_SI is negative and significant at the 5% level. On the other hand, the coefficient on BNEWS*NEG_SI*MISS is positive and significant at the 10% level. In periods that firms report earnings misses and negative special items concurrently, the differential informativeness of QEAs during bad-news periods is more pronounced. Intuitively, negative special items affect the differential informativeness of QEAs only when they cause earnings to fall below expectations. As the results in Model 2 indicate, negative special items affect the Basu measure irrespective of whether the special items are associated with earnings misses or not. The Basu measure is also associated positively with book-to-market and leverage, as expected given prior literature (Khan and Watts 2009, LaFond and Roychowdhury 2008), but unlike the differential informativeness of QEAs. Finally, asymmetric timeliness is positively associated with RInfoAsymm and MISS, but negatively associated with INSALE; recall that differential QEA informativeness is associated positively with all three variables. Thus, cross-sectional variation in the Basu measure is quite distinct from that in differential QEA informativeness, indicating that they capture different aspects of earnings. 4.4.2 The informativeness of filing dates The primary analysis in this paper focuses on the release of mandated earnings information at the time of the QEAs. The full set of mandated financial statements becomes

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available to investors only when the 10-Q and 10-K forms are filed with the SEC. 10-Qs and 10-Ks provide detailed financial data, notes on accounting policies and management’s qualitative discussion about firm performance and risk factors, among other information. Extant literature suggests that filing dates convey incremental information to the market (Easton and Zmijewski 1993, Griffin 2003). In an extension of our analysis with QEAs, we examine if filing dates assume a greater role in the disclosure of bad news than good news. Overall news is measured as the returns over the quarterly period extending from the end of (and excluding) the previous filing date to the end of (and including) the current filing date. We test whether the ratio of the magnitude of filing date market-adjusted returns to market-adjusted returns in the non-filing-date period (FILE_RATIO) is higher when overall quarterly returns are negative than when they are positive. Table 7 reports the results of estimating a regression of Ln(FILE_RATIO) on a zero-one indicator variable which is set to one when quarterly returns over our redefined period are negative. The regressions are estimated for the sub-sample of 97,400 firm-quarters over 19962006 for which filing-date data are available. The implied FILE _RATIOS suggest that the proportion of news released around filing dates during bad-news periods (24.21%) is significantly higher than that during good-news periods (19.26%). The implied ratios are much lower than the corresponding ones obtained with QEAs in Table 3, indicating that filing dates are generally less informative than QEAs.

5. Conclusion Using returns-based measures to capture news, we predict that the ratio of news released during QEAs to that released during the non-QEA period is significantly greater when the quarterly returns are negative, relative to when they are positive. Our results are consistent with our predictions.

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As expected, our evidence is particularly concentrated among firms that do not issue short-horizon forecasts. We also observe that short-horizon forecasts are generally issued in periods that are characterized by more extreme negative returns, consistent with these firms facing potentially greater litigation risk. Our collective evidence suggests that QEAs play a valuable information role by restricting delays in bad news disclosures in the large majority of cases before they become a source of significant litigation risk. Our cross-sectional tests provide evidence that QEAs increased role during bad-news periods is even greater in firms characterized by higher information asymmetry between managers and shareholders. Consistent with the role of QEAs being more crucial when managers have direct monetary incentives to delay bad news disclosures, we find that the differential informativeness of QEAs in bad-news periods is more pronounced in firm-quarters with net insider sales of stock. Finally time series analysis suggests that the role of QEAs in releasing bad news became more pronounced with the passage of REG FD, while the role of QEAs in releasing good news became more pronounced with the passage of SOX. Importantly, however, the differential role of QEAs in disclosing bad news versus good news persists in the post-SOX period. Overall, our study highlights the role of earnings announcements in ameliorating the adverse selection problem inherent in managerial disclosures.

35

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39

Appendix 1: NEWS_RATIO Magnitudes under Various Scenarios

RET < 0 Consistency with H1 Magnitude of NEWS_RATIO RET >= 0 Consistency with H1 Magnitude of NEWS_RATIO

EAR, NEAR of the same sign EAR < 0 EAR > 0 NEAR < 0 NEAR > 0

EAR, NEAR of different sign EAR > 0 EAR < 0 NEAR < 0 NEAR > 0

Could be consistent or inconsistent High if consistent, Low if not

Not possible

Inconsistent

Consistent

Not possible

Low

High

Not possible

Could be consistent or inconsistent Low if consistent, High if not

Inconsistent

Consistent

High

Low

Not possible

This appendix tabulates the scenarios under which NEWS_RATIO is expected to be relatively high versus relatively low. NEWS_RATIO is defined as 100*ABS(EAR)/ABS(NEAR). EAR is the cumulative market-adjusted returns on trading days -1 to +1 relative to the quarterly earnings announcement (QEA), NEAR represents the cumulative market-adjusted non-QEA period returns (spanning all trading days included in RET except for the trading days included in EAR). ABS(EAR) and ABS(NEAR) represent absolute values for EAR and NEAR respectively. RET represents quarterly market-adjusted returns beginning two days after the QEA for the previous quarter and ending one day after the QEA for the current quarter. To establish the patterns in NEWS_RATIO, first consider cases when EAR and NEAR are of the same sign. If it is true that QEAs play a proportionately greater role in releasing bad news than good news, as our hypothesis states, then for cases when RET < 0, ABS(EAR) is expected to be high relative to ABS(NEAR). Similarly, when RET > 0, our hypothesis would imply that ABS(EAR) is expected to be low relative to ABS(NEAR).

40

Next, consider the scenarios with differing signs on EAR and NEAR, beginning with the case when RET < 0, EAR < 0 and NEAR > 0. This case is clearly consistent with our hypothesis: all of the negative information is released at the QEAs. Since overall returns are negative, by construction EAR will be higher than NEAR in magnitude and NEWS_RATIO will be high. The scenario where RET < 0, EAR > 0 and NEAR < 0 is inconsistent with our hypothesis: all of the negative information is released during the non-QEA period. EAR by construction must be lower in magnitude than NEAR, since overall returns are negative, generating a low NEWS_RATIO. Thus, NEWS_RATIO functions well as an empirical proxy by assuming high values for negative-return observations consistent with our hypothesis and lower values for those that are inconsistent. To generate the asymmetry predicted by our hypothesis, NEWS_RATIO also needs to assume lower values for all positive-RET observations that are consistent with our hypothesis and higher values for those that are inconsistent. We examine the positive-RET cases with EAR and NEAR of differing sign to ensure that this is true. First, we focus on RET > 0, EAR < 0 and NEAR > 0. This case is consistent with our hypothesis: all of the positive information for the period reaches the market during the non-QEA period. Since overall returns are positive, by construction EAR will be lower than NEAR in magnitude and NEWS_RATIO will be low. Finally, in the positive-return case that is inconsistent with our hypothesis (RET > 0, EAR > 0 and NEAR < 0) EAR by construction has to be higher in magnitude than NEAR, since overall returns are positive, generating a higher NEWS_RATIO. In summary, variation in NEWS_RATIO is well-suited to testing whether the relative informativeness of QEAs is higher when overall information reaching the market is negative.

41

Table 1 – Descriptive Statistics Table 1 presents descriptive statistics for the pooled sample of 150,618 firm-quarters over the 80 quarters from 1987-2006, and for two subsamples: (1) firm-quarters with positive abnormal returns (BNEWS=0), and (2) firmquarters with negative abnormal returns (BNEWS=1). RET represents quarterly market-adjusted returns beginning two days after the quarterly earnings announcement for the previous quarter and ending one day after the final earnings announcement for the current quarter. BNEWS is an indicator variable equal to 1 if RET is negative, and 0 otherwise. EAR is the cumulative market-adjusted returns on trading days -1 to +1 relative to the quarterly earnings announcement, NEAR represents the cumulative market-adjusted non-earnings announcement period returns (spanning all trading days included in RET except for the trading days included in EAR). ABS(RET), ABS(EAR) and ABS(NEAR) represent absolute values for RET, EAR and NEAR respectively. BAD_EAR is an indicator variable set equal to one if EAR < 0. MISS is a binary indicator set equal to one if a firm’s earnings are below expectations and zero otherwise. In computing MISS, expected earnings are set equal to analyst expectations if analyst data is available; else they are based on a seasonal random walk. MVE is the beginning-of-quarter market value of equity, NUM_AN is the beginning-of-period number of analysts following the firm, INST_OWN is the beginning-of-period percentage institutional ownership, IVOL (idiosyncratic volatility) is the volatility of daily firm returns in excess of market returns in the preceding quarterly period, excluding the earnings announcements, Adv_BidAsk is the adverse selection component of the daily bid-ask spread (based on Hasbrouck 1991) computed as the daily average over the last month of the preceding quarter, BTM is the beginning-of-period book-to-market ratio (book value of equity to market value of equity), LEV is the beginning-of-period leverage measured using ratio of total debt, both long-term and short-term, to total assets, and HITECH is a binary indicator variable that is set equal to one if the firm belongs to any of the following four-digit SIC industry codes: 2833–2836, 3570–3577, 3600–3674, 7371–7379 or 8731–8734. INSALE is a binary indicator set equal to one for firm-quarters with net insider sales, and zero otherwise. Net insider sales are measured as the sales of stock minus purchases of stock across directors and firm executives identified as officers. All variables are expressed in percentages except for MVE which is in $’ million and NUM_AN which is the number of analysts.

Full Sample RET EAR NEAR ABS(RET) ABS(EAR) ABS(NEAR) BAD_EAR MISS MVE ($ million) NUM_AN INST_OWN IVOL ADV_BidAsk BTM LEV HITECH INSALE N of firm-quarters

Means BNEWS =0 BNEWS =1

Full sample

Medians BNEWS =0 BNEWS =1

1.43 0.18 1.33 18.44 5.85 17.46 49.78 35.59

20.30 2.13 18.15 20.30 5.59 19.19 39.80 26.62

-16.65 -1.68 -14.78 16.65 6.11 15.80 59.34 44.19

-0.47 0.03 -0.61 12.57 3.84 11.80 0.00 0.00

12.63 1.22 11.41 12.63 3.68 11.72 0.00 0.00

-12.52 -1.19 -11.53 12.52 4.00 11.86 100.00 0.00

2249.56 7.28 43.63 3.31 3.21 53.87 21.10 24.23 33.23

2328.04 7.43 44.72 3.15 3.16 55.99 21.12 23.29 35.51

2174.41 7.13 42.59 3.46 3.25 51.85 21.09 25.14 31.04

368.56 5.00 43.06 2.76 1.15 44.34 17.21 0.00 0.00

388.24 5.00 44.74 2.62 1.13 45.97 17.34 0.00 0.00

351.50 5.00 41.51 2.93 1.17 42.87 17.08 0.00 0.00

73,682

76,936

150,618

42

150,618

73,682

76,936

Table 2 – Univariate Tests of NEWS_RATIO NEWS_RATIO is defined as 100*ABS(EAR)/ABS(NEAR). ABS(EAR) is the absolute value of cumulative market-adjusted returns on trading days -1 to +1 relative to the QEA, ABS(NEAR) is the absolute value of the cumulative market-adjusted non-earnings announcement period returns. Ln(NEWS_RATIO) is the natural logarithm of NEWS_RATIO. BNEWS is an indicator variable equal to 1 if RET is negative, and 0 otherwise, where RET represents quarterly marketadjusted returns beginning two days after the quarterly earnings announcement for the previous quarter and ending one day after the final earnings announcement for the current quarter. Mean and median NEWS_RATIO and Ln(NEWS_RATIO) are computed every year and the table reports the means of each across the 80 quarters from 1987-2006, along with the associated standard error computed using Fama-Macbeth procedure. ***, **, * represent statistical significance at a minimum 0.01, 0.05, and 0.1 level respectively.

Column 1: Column 2: Column 3: Mean Median Mean Implied NEWS_RATIO NEWS_RATIO Ln(NEWS_RATIO) Ratio

Column 4: Median Ln(NEWS_RATIO)

Implied Ratio

BNEWS=1

98.96

36.69

3.54

34.49

3.58

35.98

BNEWS=0

103.47

31.01

3.41

30.40

3.41

30.17

DIFFERENCE

-4.51 * (2.43)

5.68 *** (0.86)

80

80

N of quarters

0.13 *** (0.03)

80

43

0.18 *** (0.03)

80

Table 3 – Differential Informativeness of QEAs in Bad-News Periods and Good-News Periods QEAs are quarterly earnings announcements. The table presents the results of quarterly Fama-Macbeth regressions. The dependent variable, Ln(NEWS_RATIO) is the natural logarithm of NEWS_RATIO, which in turn is defined as 100*ABS(EAR)/ABS(NEAR). ABS(EAR) is the absolute value of cumulative marketadjusted returns on trading days -1 to +1 relative to the QEA, ABS(NEAR) is the absolute value of the cumulative market-adjusted non-earnings announcement period returns. BNEWS is an indicator variable equal to 1 if overall quarterly return RET is negative, and 0 otherwise. Implied Ratio is the exponent of the corresponding coefficient. Model 1 includes the sample of 150,618 firm-quarters between 1987 and 2006. Model 2 includes the subsample of 133,231 firmquarters between 1995-2006. Model 3 includes the subsample of 13,941 firm-quarters between 1995 and 2006 that issue forecasts of current earnings following the previous quarter’s earnings announcements, or short-horizon forecasts. Model 4 includes the subsample of 109,290 firm-quarters between 1995 and 2006 that do not issue short-horizon forecasts. Standard errors are reported in parentheses below coefficients. ***, **, * represent statistical significance at a minimum 0.01, 0.05, and 0.1 level respectively.

Dependent Variable: Ln(NEWS_RATIO) Model 1 Model 2 Predicted Sign

Full Sample Coeff.

Intercept BNEWS N of quarters R squared Intercept+BNEWS

+

Implied Ratio

Subsample from 1995 Coeff.

Implied Ratio

Model 3

Model 4

Subsample of Forecasters Subsample of Non(from 1995) forecasters (from 1995) Coeff.

Implied Ratio

Coeff.

Implied Ratio

3.4144 *** (0.0260) 0.1263 *** (0.0267) 80 0.0072

30.40

3.4524 *** (0.0335) 0.1057 *** (0.0331) 48 0.0061

31.58

3.3803 *** (0.0366) -0.1782 *** (0.0487) 48 0.0139

29.38

3.4572 *** (0.0338) 0.1460 *** (0.0336) 48 0.0071

31.73

3.5407 *** (0.0214)

34.49

3.5581 *** (0.0303)

35.10

3.2021 *** (0.0422)

24.59

3.6032 *** (0.0299)

36.72

44

Table 4 – Cross-Sectional Variation in the Differential Informativeness of QEAs QEAs are quarterly earnings announcements. The table presents the results of quarterly Fama-Macbeth regressions. The dependent variable, Ln(NEWS_RATIO) is the natural logarithm of NEWS_RATIO, which in turn is defined as 100*ABS(EAR)/ABS(NEAR). RInfoAsymm is the quintile rank of InfoAsymm, which is extracted from a principalcomponents-analysis, and is negatively associated with firm size, analyst following and institutional ownership, and positively associated with idiosyncratic volatility and the adverse selection component of the bid-ask spread. RBTM is the quintile rank of beginning-of-period book-to-market. RLEV is the quintile rank of beginning-of-period financial leverage. Model 1 includes the sample of 150,618 firm-quarters between 1987-2006, Model 2 includes the subsample of 133,231 firm-quarters between 1995-2006, Model 3 includes the subsample of 13,941 firm-quarters between 1995-2006 that issue short-horizon forecasts and Model 4 includes the subsample of 109,290 firm-quarters between 1995-2006 that do not issue short-horizon forecasts. All other variables are defined in the notes to Table 1. Standard errors are reported in parentheses below coefficients.***, **, * represent statistical significance at a minimum 0.01, 0.05, and 0.1 level respectively. Dependent Variable: Ln(NEWS_RATIO) Model 1 Model 2 Model 3 Model 4 Predicted Subsample of Subsample of NonSubsample from Sign Full Sample Forecasters forecasters (from 1995 (from 1995) 1995)

Intercept

RInfoAsymm INSALE MISS RBTM RLEV HITECH BNEWS RInfoAsymm*BNEWS

+

INSALE*BNEWS

+

MISS*BNEWS

+

RBTM*BNEWS RLEV*BNEWS HITECH*BNEWS N of quarters R Squared

3.6317 (0.0498) -0.0767 (0.0096) -0.0316 (0.0316) -0.1299 (0.0269) -0.0058 (0.0100) -0.0148 (0.0111) 0.0186 (0.0249) -0.0191 (0.0561) 0.0385 (0.0105) 0.1336 (0.0321) 0.1797 (0.0374) 0.0055 (0.0135) -0.0034 (0.0116) 0.0092 (0.0419) 80 0.0332

***

3.7245 (0.0544) -0.0860 (0.0110) -0.0402 (0.0182) -0.1763 (0.0259) -0.0067 (0.0084) -0.0240 (0.0059) 0.0191 (0.0279) -0.1040 (0.0677) 0.0448 (0.0125) 0.1488 (0.0234) 0.2471 (0.0423) 0.0094 (0.0125) 0.0031 (0.0084) 0.0194 (0.0476) 48 0.0249

***

***

*** *** ***

45

*** *** ** ***

***

*** *** ***

3.1981 *** (0.7873) -0.0038 (0.9650) 0.1167 (0.8675) 0.0791 (0.9360) -0.0602 (0.9572) -0.0016 (0.9698) 0.0231 (0.8884) 0.1858 (0.7726) -0.0361 (0.9645) -0.0091 (0.8446) -0.2622 *** (0.9123) 0.0662 (0.9559) -0.0058 (0.9662) -0.1310 (0.8741) 48 0.1068

3.7592 (0.0571) -0.0912 (0.0112) -0.0416 (0.0192) -0.2016 (0.0273) -0.0024 (0.0084) -0.0264 (0.0061) 0.0165 (0.0268) -0.0676 (0.0716) 0.0311 (0.0132) 0.1574 (0.0242) 0.3172 (0.0429) 0.0065 (0.0128) -0.0005 (0.0082) 0.0534 (0.0478) 48 0.0288

*** *** ** ***

***

** *** ***

Table 5 – Time-Series Variation in the Differential Informativeness of QEAs QEAs are quarterly earnings announcements. The table presents the results of quarterly Fama-Macbeth regressions. The dependent variable, Ln(NEWS_RATIO) is the natural logarithm of NEWS_RATIO, which in turn is defined as 100*ABS(EAR)/ABS(NEAR). ABS(EAR) is the absolute value of cumulative market-adjusted returns on trading days -1 to +1 relative to the QEA, ABS(NEAR) is the absolute value of the cumulative market-adjusted non-earnings announcement period returns. BNEWS is an indicator variable equal to 1 if RET is negative, and 0 otherwise. Implied Ratio is the exponent of the corresponding coefficient. Model 1 includes all fiscal quarters that in calendar time precede the enactment of Regulation FD in the fourth quarter of 2000 (PRE-REG-FD). Model 2 includes all fiscal quarters that in calendar time correspond to, or follow, the fourth quarter of 2000, and precede the enactment of the Sarbanes-Oxley Act in the third quarter of 2002 (POST-REG-FD PRE-SOX). Model 3 includes all remaining fiscal quarters that in calendar time correspond to, or follow, the third quarter of 2002 (POST- SOX). The number of fiscal quarters in a given sub-period can differ from the number of calendar quarters. Standard errors are reported in parentheses below coefficients. ***, **, * represent statistical significance at a minimum 0.01, 0.05, and 0.1 level respectively. Dependent Variable: Ln(NEWS_RATIO) Model 1 Model 2 POST-REG-FD Predicted PRE-REG-FD Period PRE-SOX Period Sign Implied Implied Coeff. Coeff. Ratio Ratio Intercept BNEWS N of quarters R Squared Intercept+BNEWS

+

Model 3 POST-SOX Period Coeff.

Implied Ratio

3.3788 *** (0.0277) 0.0885 *** (0.0319) 57 0.0066

29.34

3.3208 *** (0.0667) 0.3897 *** (0.0582) 11 0.0176

27.68

3.6334 *** (0.0540) 0.1211 *** (0.0368) 20 0.0039

37.84

3.4673 *** (0.0220)

32.05

3.7105 *** (0.0391)

40.87

3.7545 *** (0.0318)

42.71

Difference in Intercept from prior period Difference in BNEWS from prior period Difference in Intercept + BNEWS from prior period

46

-0.0580 (0.0725)

0.3126 *** (0.0859)

0.3012 *** (0.0663)

-0.2686 *** (0.0689)

0.2432 *** (0.0449)

0.0440 (0.0506)

Table 6 – Differential Informativeness of QEAs and Asymmetric Timeliness of Earnings The table presents the results of quarterly Fama-Macbeth regressions. In Model 1, the dependent variable is Ln(NEWS_RATIO), the natural logarithm of NEWS_RATIO, which in turn is defined as 100*ABS(EAR)/ABS(NEAR). In Model 2, the dependent variable is E/P where E represents income before extraordinary items in quarter t, P represents the market value of equity at the beginning of quarter t. NEG_SI is a one/zero indicator variable set equal to one when negative special items are greater than or equal to 1% of sales in magnitude. All other variables are defined in the notes to Table 1 and Table 4. Models 1 and 2 include the sample of 150,618 firm-quarters between 1987-2006. Standard errors are reported in parentheses next to the coefficients. ***, **, * represent statistical significance at a minimum 0.01, 0.05, and 0.1 level respectively. Model 1 Model 2 Dependent Variable: Dependent Variable: Ln(NEWS_RATIO) E/P Intercept

RInfoAsymm INSALE MISS NEG_SI NEG_SI*MISS RBTM RLEV HITECH BNEWS RInfoAsymm*BNEWS INSALE*BNEWS MISS*BNEWS NEG_SI*BNEWS NEG_SI*MISS*BNEWS RBTM*BNEWS RLEV*BNEWS HITECH*BNEWS RET

3.6413 *** -0.0719 *** -0.0337 -0.1265 *** -0.0251 0.0208 -0.0051 -0.0166 0.0383 -0.0157 0.0306 *** 0.1461 *** 0.1856 *** -0.2542 *** 0.1620 * 0.0027 0.0005 0.0039

RInfoAsymm*RET INSALE*RET MISS*RET NEG_SI*RET NEG_SI*MISS*RET RBTM*RET RLEV*RET HITECH*RET RET*BNEWS

RInfoAsymm*RET*BNEWS INSALE*RET*BNEWS MISS*RET*BNEWS NEG_SI*RET*BNEWS NEG_SI*MISS*RET*BNEWS RBTM*RET*BNEWS RLEV*RET*BNEWS HITECH*RET*BNEWS N of quarters R Squared

80 0.0419

45

(0.0411) (0.0107) (0.0340) (0.0302) (0.0843) (0.1029) (0.0104) (0.0119) (0.0254) (0.0495) (0.0122) (0.0337) (0.0443) (0.0728) (0.0922) (0.0148) (0.0130) (0.0449)

0.0221 *** -0.0036 *** 0.0010 -0.0081 *** -0.0352 ** 0.0012 0.0013 *** -0.0004 -0.0104 *** -0.0041 ** 0.0007 -0.0006 -0.0014 0.0020 0.0004 0.0006 0.0013 *** 0.0020 0.0064 -0.0020 0.0052 * -0.0369 *** 0.0012 0.1622 -0.0011 0.0013 0.0108 ** -0.0945 *** 0.0272 *** -0.0182 *** 0.0360 *** 0.0863 ** -0.1248 0.0332 *** 0.0151 *** -0.0126 80 0.3185

(0.0013) (0.0004) (0.0007) (0.0007) (0.0157) (0.0209) (0.0003) (0.0003) (0.0014) (0.0017) (0.0004) (0.0009) (0.0010) (0.0155) (0.0177) (0.0005) (0.0005) (0.0018) (0.0070) (0.0016) (0.0028) (0.0036) (0.0483) (0.2024) (0.0015) (0.0019) (0.0047) (0.0183) (0.0045) (0.0055) (0.0054) (0.0416) (0.1689) (0.0043) (0.0037) (0.0093)

Table 7 – Differential Informativeness of Filing Dates in Bad-News Periods and Good-News Periods FileDates are the filing dates of 10-Qs and 10-Ks. The table presents the results of quarterly Fama-Macbeth regressions. Overall returns for quarter t are measured over the period extending from from FileDatet-1 + 2 to FileDatet + 1. Filing date returns for period t are estimated over FileDatet - 1 to FileDatet + 1. Non-filing-date returns are backed out from the quarterly return and the filing date return. All returns are market-adjusted. The dependent variable, Ln(FILE_RATIO) is the natural logarithm of the ratio of the absolute value of filing date return to the absolute value of the non-filing-date return. BNEWS is an indicator variable equal to 1 if overall return in the quarterly period described above is negative, and 0 otherwise. Implied Ratio is the exponent of the corresponding coefficient. The test includes 97,400 firm-quarters, a sub-sample of the observations in Table 3 with data available on filing dates. Standard errors are reported in parentheses below coefficients. ***, **, * represent statistical significance at a minimum 0.01, 0.05, and 0.1 level respectively.

Dependent Variable: Ln(FILE_RATIO) Predicted Sign Intercept BNEWS

+

N of quarters R squared Intercept+BNEWS

46

Coeff.

Implied Ratio

2.9579 *** (0.0328) 0.2289 *** (0.0294) 44 0.0089

19.26

3.5407 *** (0.0318)

24.21