Opportunity knocks but once: delayed disclosure of financial items in earnings

announcements and neglect of earnings news

Yifan Li

San Francisco State University

Alexander Nekrasov

University of Illinois at Chicago

Siew Hong Teoh

University of California, Irvine

Published in Review of Accounting Studies, 2020, 25: 159–200

Abstract

We define a delayed disclosure ratio (DD) as the fraction of 10-Q financial statement items that

are withheld at the earlier quarterly earnings announcement. We find that higher DD firms have

a greater delay in investor and analyst response to earnings surprises: (i) the fraction of total

market reaction to quarterly earnings news realized around the earnings announcement (after

the 10-Q filing) is smaller (greater), and (ii) analysts are more likely to defer issuing forecasts

from immediately after the earnings announcement to after the 10-Q filing. Consistent with our

limited attention model predictions, the response catch-up associated with DD is incomplete

even after the delayed items are fully disclosed at the 10-Q filing date, and persists until the

next earnings announcement date. The return reaction to earnings news over the entire quarter

does not vary with DD, so differences in earnings informativeness do not explain the DD effect.

Our findings suggest that, for limited attention effects to be mitigated, the timing of disclosures

must be coincident with the focal periods—at earnings announcement dates—when investors

and analysts are paying the most attention.

Keywords: Delayed disclosure, Analyst and investor underreaction, Earnings response

coefficient, Post-earnings announcement drift, Limited attention, Market efficiency

JEL Codes: G14, G18, G28, G29, G38, M41, M45

We thank Lucile Faurel, Joanna Ho, Sonya Lim, Ben Lourie, Radhika Lunawat, Mort Pincus, Devin

Shanthikumar, Terry Shevlin, Christopher Schwarz, Zheng Sun, and seminar/conference participants at

the Pennsylvania State University, the University of California-Irvine, the 2018 American Accounting

Association Meeting, FARS 2016 Midyear Conference, SCARF 2016 Conference, the University of

Illinois at Chicago 2016 Accounting Conference, and the UCLA/UCI/USC Accounting conference for

helpful comments.

1

1 Introduction

Quarterly earnings press releases are a major channel through which companies release

financial information. These releases usually precede the filings of Form 10-Q with the

Securities and Exchange Commission (SEC) by more than two weeks. Because the releases are

timelier than the filings, investors and analysts react more strongly to earnings announcements

than to the filing date disclosures.1

Nevertheless, evidence indicates that investors and analysts underreact to earnings

news even at the announcement date. The resulting post-event delayed reaction, commonly

referred to as the post-earnings announcement drift (PEAD), is robust to various research

design choices and sample periods (Ball and Brown 1968; Foster, Olsen, and Shevlin 1984;

Bernard and Thomas 1989; Livnat and Mendenhall 2006; Ben-Rephael, Da, and Israelsen

2017). The literature has thus concluded that investors and analysts are inefficient processors

of information contained in current earnings news about future earnings (Bernard and Thomas

1990; Abarbanell and Bernard 1992; Zhang 2008).

In this paper, we examine the role of delayed disclosure of financial statement items in

the quarterly earnings press release and the role of limited attention of investors and analysts

in explaining this inefficiency. Specifically, we define the delayed disclosure ratio, DD, as the

ratio of the number of 10-Q financial statement items that are withheld in the quarterly earnings

press release to the total number of distinct financial statement items reported in the 10-Q filing.

We predict that a larger DD is associated with less investor and analyst response to earnings

news at the announcement date and greater PEAD. If some investors update beliefs at

1 In our sample, market reactions and analyst revisions at the earnings announcement are almost twice as large as

at the filing date. Specifically, the mean absolute market-adjusted abnormal return is 6.54% around earnings

announcements and 3.77% around 10-Q filings. The mean absolute analyst earnings forecast revision is 0.50%

around earnings announcements and 0.32% around 10-Q filings (untabulated). The weak investor reaction at filing

dates is consistent with the work of Easton and Zmijewski (1993), who examine a pre-EDGAR sample. Griffin

(2003) finds a significant reaction around 10-Q/K for a post-EDGAR sample. However, Li and Ramesh (2009)

report that the significant reaction is driven by 10-Q/K filings that coincide with earnings releases.

2

infrequent, discrete intervals, we also predict that the underreaction at the earnings

announcement date associated with DD is not eliminated at the 10-Q filing date but persists to

the next time investors update their beliefs. In other words, if the financial statement

information supporting the earnings news does not “strike while the iron is hot,” its effect could

be suppressed until the next earnings announcement. We use a limited attention model to derive

these surprising implications for investor reactions to earnings news.

Delayed disclosure of supporting financial statement items in earnings announcements

has been a matter of concern to regulators, information intermediaries, and professional

investors. The SEC’s Committee on Improvements in Financial Reporting (commonly called

the Pozen committee, 2008) and the Chartered Financial Analyst (CFA) Institute (2007) have

called for fuller financial statement disclosures in earnings press releases. 2 The National

Investor Relations Institute’s (NIRI) statement on the Standards of Practice for Investor

Relations, issued in 2008 and updated in 2013, specifically urges firms to include—in their

entirety—income statement, balance sheet, and statement of cash flows in the earnings release.

Consistent with the perspective above, these agencies argue that full financial statement

disclosures in the earnings announcements reduce information acquisition and attention costs,

which lessens the informational disadvantage for less sophisticated participants and enhances

the informational efficiency of the capital market. The greater financial statement disclosure at

the earnings announcement also helps market participants obtain earlier access to critical

information for valuation.

Fully rational investors and analysts should react immediately to earnings surprises,

regardless of whether some of the financial statement items supporting the earnings news are

2 The importance of the timing of financial information dissemination was also raised in an SEC Concept Release

in April 2016. The Commission has raised questions about the costs and benefits of quarterly reporting, including:

“Should we revise or eliminate our rules requiring quarterly reporting?” The SEC mandated quarterly reports in

1970. However, even prior to the SEC’s adopting the quarterly Form 10-Q, more than 70 percent of public

companies produced quarterly reports (SEC Concept Release, April 2016).

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missing from the earnings press releases. If information is missing, a rational observer uses the

available information to make inferences about the missing items and future earnings.

Conditional upon the earnings surprise at the announcement date, the forecasts of a rational

observer are equal to the conditional expectation of earnings. So investor expectations and

analyst forecasts (setting aside agency problems) will be unbiased, and the equity market will

be efficient.3

Extensive empirical literature, including evidence of PEAD, suggests that investors are

imperfectly rational. Hirshleifer, Lim, and Teoh (2011) offer a limited attention theory to

explain PEAD. Building on this approach, we provide a limited attention model with

predictions about how the availability of supporting information from financial statement items

affects investors’ delayed reaction. We also provide intuitive arguments about how delayed

disclosure will affect analyst reactions.

The key difference between our paper and previous studies is that we examine the

importance of supporting information arriving when the earnings surprise signal is being

processed. This paper thus provides insight into the effects of the release of financial

information in installments rather than all at once, and highlights the importance and relevance

of matching disclosure timing to when observers are maximally attentive, such as at periodic

earnings announcements.

To derive the implications of delayed disclosure for investor reactions to earnings news,

we modify the limited attention model of Hirshleifer, Lim, and Teoh (2011). The model in

Section 2 analyzes how delayed disclosure of financial statement items affects the

announcement date price reaction to earnings surprises and PEAD. It does so by comparing the

3 Studies suggest that more detailed financial statement item disclosure represents higher disclosure quality (Chen,

Miao, and Shevlin 2015; Francis, Schipper, and Vincent 2002; Collins, Li, and Xie 2009) and enhances the

credibility of earnings by limiting managers’ degrees of freedom to manage earnings (Hirst, Koonce, and

Venkataraman 2007; D’Souza, Ramesh, and Shen 2010). While disclosure quality or credibility shifts the weight

that fully attentive rational investors put on earnings news, these factors do not imply that delayed disclosure

induces a systematic delayed reaction, or PEAD, unless inattention is also present.

4

equilibrium prices, conditional on the arrival of news in two regimes: in the timely disclosure

regime (TD-Regime), the firm’s earnings and financial statement information are revealed at

the earnings announcement date; in the delayed disclosure regime (DD-Regime), only earnings

are disclosed at the earnings announcement date, and other financial statement information is

not revealed until the filing date.

A prediction from this model is that the sensitivity to earnings news at the

announcement date is lower and PEAD is higher in the DD-Regime than in the TD-Regime.

Intuitively, under the DD-Regime, attentive investors face higher uncertainty about firm value.

Assuming investors are risk averse, higher uncertainty results in higher arbitrage costs, so

attentive investors trade less aggressively to exploit inattentive investors’ underreaction to

earnings news. Therefore, the DD-Regime underreaction is more severe.

Under the further assumption that the fraction of attentive investors is lower at the filing

date than at the earnings announcement date, the model offers the surprising implication of

incomplete catch-up of price reactions at the filing date in the DD-Regime. The full catch-up

occurs only at the next earnings announcement date, when investors again pay greater attention

to the firm.

Delayed, incomplete catch-up is consistent with the maxim that “opportunity knocks

but once.” A firm has a special opportunity to convey value-relevant information to investors

at the earnings announcement date, when the investors’ attention is high. If the firm misses this

opportunity, either inadvertently or intentionally, by disclosing value-relevant financial

information in installments, the earnings information disclosed at the earnings announcement

date will not be impounded into investor valuations to the same extent as if the other financial

information had been disclosed at the same time. Furthermore, under our hypotheses, even

when the missing information is revealed at the later 10-Q filing date, it will not be incorporated

into prices to the same extent as if it had been disclosed at the earnings announcement date.

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Analysts similarly have attention constraints, and when there is a cost of analyzing firm

financial statements and issuing forecasts, they may not choose to develop forecasts both at the

earnings-announcement and filing dates. Given the advantage of timeliness, we expect analysts

to issue forecasts more often after the earnings announcement than after the filing date, all else

equal. However, when disclosure of value-relevant information is delayed, making forecasting

at the earnings announcement date more challenging, some analysts may choose to revise only

after the filing date. So we expect fewer forecasts after earnings announcements and more

forecasts after filing dates when supporting financial information is delayed. Furthermore,

assuming the costs and differences in interpretation of earnings news are higher when

supporting financial information is withheld, we expect greater average forecast underreaction

to earnings surprises, lower forecast accuracy, and greater forecast dispersion when delayed

disclosure is high.

Two forces could lead to results contradicting our predictions. First, firms may disclose

more financial statement items other than earnings when bottom-line earnings are less

informative.4 In this case, the delayed disclosure ratio would be low, but investor and analyst

reaction to earnings news might also be weak because earnings are less important. Second,

investors and analysts may need more time to analyze information from expanded disclosures.

This idea contrasts sharply with our above argument that having less information makes

forecasting more difficult for analysts. If bottom-line earnings are a good summary statistic for

expected future cash flows, disclosure of the full set of financial statement items could be

counterproductive. Hirshleifer, Lim, and Teoh (2009) find that the arrival of competing signals

distracts market participants and slows reaction to earnings news. Arif et al. (2017) find that

the reaction to annual earnings news is muted and PEAD is higher when the earnings

4 For example, Chen, DeFond, and Park (2002) find that companies disclose balance sheets in earnings press

releases when current earnings are likely to be less informative or when future earnings are more uncertain.

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announcement is made concurrently with the release of the 10-K filing, especially when the

concurrent 10-K is longer and more difficult to process. The distraction idea contrasts with our

argument. Thus, whether delayed disclosure is associated with delayed investor and analyst

reaction to earnings news remains an empirical question.

In the empirical analysis, we use the Compustat Preliminary History database to

identify financial statement items that are disclosed in quarterly earnings press releases, and

the Compustat Quarterly database to identify items that are reported in the 10-Q filing.5 All of

our tests use firm- and time-fixed effects to control for potential omitted variables.

Consistent with our predictions, we find that delayed disclosure, DD, is negatively

associated with the immediate market reaction, positively associated with PEAD, and not

significantly associated with the reaction to earnings news over the entire quarter. So DD relates

to the timing of market reactions to earnings news but not the informativeness of earnings

information. When supporting information is delayed, the market reaction to earnings news is

partly delayed from immediately around the earnings announcement to after the 10-Q filing.

This suggests that the market is slow to incorporate earnings news until corroborating

information arrives, which in our model reduces the risk, for attentive investors, of trading

aggressively based on public earnings information. In terms of the magnitude of DD effect, we

find that an increase in DD from zero to one corresponds approximately to a decrease in ERC

of 37% and an increase in PEAD of 42%. Most interestingly, the delayed reaction persists even

after the 10-Q filing and is fully corrected only at the next earnings announcement. This test

confirms our model’s implication that “opportunity knocks but once.” As robustness checks,

we confirm that similar results hold using a change specification, using residual DD from the

regression of DD on an expanded set of explanatory variables, and using delayed disclosure of

5 We focus on quarterly earnings announcements to avoid the issue of audit completeness at the announcements

of annual earnings (Schroeder 2016; Marshall, Schroeder, and Yohn 2019). In an additional analysis, we examine

the effect of delayed disclosure in the annual earnings announcements.

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industry peers as an instrument for the firm’s delayed disclosure. Analyses of delayed

disclosure separately for the income statement, the balance sheet, and the statement of cash

flows reveal that delayed disclosure of each of the three statements is negatively associated

with the immediate reaction to earnings news. In contrast, the positive association with the

post-earnings announcement drift is largely due to the delayed disclosure of balance sheet items.

We next examine the association between delayed disclosure and analyst reactions to

earnings news. We find that delayed financial statement disclosure is associated with a greater

delay in analyst forecasts following the earnings announcement. Specifically, for firms with

high DD, the portion of earnings forecasts made within two trading days of the earnings

announcement date is low, while the portion of earnings forecasts made after the 10-Q filing is

high. For high DD firms, the delay in issuance of earnings forecasts is not fully resolved within

a few days of the additional financial information being disclosed at the 10-Q filing. The

delayed reaction instead persists to the next quarter’s earnings announcement. We also find that

a higher DD is associated with a larger magnitude of analyst underreaction to the earnings

surprise, higher analyst forecast dispersion, and lower analyst forecast accuracy. DD

differences are not driven by differences in the number of financial items in the 10-K/Q. Finally,

we find that the relation between DD and delay in analyst forecasts is more pronounced for less

experienced analysts, consistent with past evidence that these analysts are more strongly

affected by forecasting difficulty (Bradshaw, Lee, and Peterson 2016).

There are three caveats regarding our method and inferences. First, in testing our

predictions, we try to use a simple and objective measure of overall delay in financial statement

disclosure. Yet in some industries and economic conditions, particular financial items may be

relatively more important, so a measure that assigns greater weights to these items could have

higher power. Second, we assume that greater disclosure of financial statement information is

useful to outsiders (a similar assumption can be found in Chen et al. [2002], Hirst et al. [2007],

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Hewitt [2007], and D’Souza et al. [2010]). However, in some cases, information overload may

have a negative effect. Finally, as in most empirical studies, endogeneity is challenging to

control for. Although our results are robust to using firm fixed effects, residual DD, and

instrumented DD, we advise caution in drawing causal inferences.

Our study contributes to the research on the effects of financial statement disclosures

in earnings press releases. The three papers that are most closely related to the current paper

are Levi (2008), Louis, Robinson, and Sbaraglia (2008), and Miao, Teoh, and Zhu (2016).

Similar to our study, these papers examine how investor reactions are affected by the financial

statement items that are disclosed in the earnings press releases versus only in the 10-Q filings.

The key difference is that these papers are confined to the accrual anomaly and the disclosure

of accrual items in the earnings press releases. In contrast, our study is more general in that it

compares investor reactions at various dates—the initial earnings press release date, the 10-Q

filing dates, and subsequent earnings press release dates—conditional on the relative degree of

delayed disclosure of all financial statement items.6

Given the wider scope for potential mispricing of financial statement items beyond

accrual-related items, it is important to examine how the fraction of 10-Q financial statement

items whose disclosure is delayed can affect how quickly the information is incorporated into

stock prices. Unlike accruals, earnings news is always announced in the earnings press release,

so the financial statement items disclosed in the earnings press release play a different role in

our study—they reduce information uncertainty for sophisticated investors. Given the opposing

views on the effects of financial statement disclosures (Chen et al. 2002; Arif et al. 2017),7 the

6 The samples in Levi (2008) and Louis, Robinson, and Sbaraglia (2008) are also smaller: six quarters from 2001

to 2002 in the former, and four years from 1999 to 2002 in the latter. Because we are focused on the potential

mispricing of general financial statement items, we are also able to sidestep the thorny difficulties of estimating

discretionary accruals, a common problem for accrual anomaly studies. 7 Chen et al. (2002) show that financial statement disclosures can indicate lower informativeness of earnings,

which suggests a lower ERC. Arif et al. (2017) find that concurrent disclosure of annual earnings news and the

annual financial statement filings leads to information overload, lower response to earnings news, and a greater

PEAD.

9

answer to our research question is not obvious, and so requires empirical investigation.

2 Limited attention predictions and hypotheses

Our key variable of interest is delay in financial statement disclosure from the earnings

press release date to the 10-Q filing date. We use a limited attention model to derive predictions

for how delayed disclosure, DD, affects investor reaction to earnings news, and use other

intuitive arguments to predict how DD may affect the timing, accuracy, and other properties of

analyst forecasts in reaction to earnings news.

2.1 A limited attention model of delayed price reactions to earnings news

We begin with the limited attention models of Hirshleifer and Teoh (2003) and

Hirshleifer, Lim, and Teoh (2011), and consider a setting in which investors are risk averse, a

fraction f of investors is inattentive to the earnings and financial statement disclosures, and the

remaining fraction 1 – f of investors is attentive to all publicly available information.8 All

investors participate in a market for a single risky security (stock), which can be exchanged for

riskless asset (cash).

The timeline for the model is shown in Figure 1. Let P0 denote the stock price at date 0

before the earnings announcement. At date 1, which corresponds to the earnings announcement

date, investors receive public information about the terminal value of the stock. At date 2,

which corresponds to the filing date, investors may receive further public information about

the terminal value of the stock. At date 3, stockholders receive the terminal payoff of the stock.

Following Hirshleifer and Teoh (2003), we assume for modeling convenience that the stock is

in zero net supply,9 so the equilibrium stock price at date 1 equals a weighted average of the

8 It does not matter for the analysis whether the attentiveness of any given investor at a given date is random or is

the outcome of a deterministic process. What matters is the fraction of investors who are attentive at each date.

Inattentive investors do not know there is a signal that they are ignoring, i.e., they do not know that they are

inattentive. 9 The zero net supply assumption implies a zero net market risk premium, which eliminates the nuisance risk

premium term from the pricing equation. Investor risk aversion still plays a role by determining relative weights

10

beliefs of the two investor groups conditional on information available at date 1:

1 3 3[ | ] (1 ) [ | ]I AP E P E P , (1)

where the superscript I or A denotes the belief of inattentive or attentive investors, respectively,

and is an increasing function of f, the fraction of inattentive investors:

3

3 3

( )

( ) (1 ) ( )

I

I A

f P

f P f P

, (2)

where A,I(P3) = 1/varA,I(P3) is the perceived precision about firm value of attentive and

inattentive investors. Equations (1) and (2) follow from the market-clearing condition that the

date 1 total demand for the risky asset by attentive and inattentive investors equals the

outstanding supply. Because investors are risk averse, the weights of attentive and inattentive

investors (1- and , respectively) are increasing functions of their perceived precision about

the firm value.

Consider two alternative regimes. In the TD-Regime, the date 1 information set ϕ

consists of earnings e and an additional financial statement item . In the DD-Regime, ϕ

consists of earnings e only, and is withheld at date 1 and only reported at date 2. Attentive

investors update their priors upon the arrival of the information at date 1, but inattentive

investors ignore the information. Therefore, the price movement at date 1 reflects only the

Bayesian updates of attentive investors. In TD-Regime, the price at date 1 is

1 3 3 3 3( , ) [ | , ] (1 ) [ | , ] [ ] (1 ) [ | , ]I AP e E P e E P e E P E P e , (3)

where the first expectation is the prior expectation for the terminal value P3 and the second

expectation is the fully rational Bayesian update for P3, conditional on observing both pieces

of information e and , and the effective weight on the inattentive beliefs in the pricing equation

is given by:

by attentive and inattentive investors in the pricing equation.

11

3

3 3

( )

( ) (1 ) ( | , )

I

I A

f P

f P f P e

. (4)

In Case 2, the price at date 1 when only e is observed is given by

1 3 3 3 3( ) [ | ] (1 ) [ | ] [ ] (1 ) [ | ]I AP e E P e E P e E P E P e . (5)

As before, the first expectation for the inattentive investors is just the prior expectation of

terminal value P3, and the second expectation is the fully rational Bayesian update for the

terminal value based only on e. The effective weight for the beliefs of inattentive investors is

given by

3

3 3

( )

( ) (1 ) ( | )

I

I A

f P

f P f P e

. (6)

Since precision A(P3|e) < A(P3|e,), the weight ω on inattentive investors’ beliefs in setting

price at date 1 is higher in the DD-Regime than the weight on their beliefs in the TD-Regime.

Intuitively, attentive risk-averse investors trade less aggressively in the DD-Regime, where

uncertainty about firm value is higher (precision A(P3|e) < A(P3|e,)). So their weight on

equilibrium price is lower, and the weight of inattentive investors is higher. The price reaction

at date 1 upon the arrival of earnings news e e depends on the expectation of price at date 1,

conditional on e e as follows.

TD-Regime:

1 0 3 3 0[ ( , ) | ] [ ] (1 ) [ | ]E P e P e e E P E P e P . (7)

DD-Regime:

1 0 3 3 0[ ( ) | ] [ ] (1 ) [ | ]E P e P e e E P E P e P . (8)

Differentiating (7) and (8) with respect to earnings news e e , we obtain the earnings response

coefficients (ERCs) in the two cases.

TD-Regime:

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3

1 0 3,

[ ( , ) | ] [ | ](1 ) (1 )

( )P e

dE P e P e e dE P e

d e e de

. (9)

DD-Regime:

3

1 0 3,

[ ( ) | ] [ | ](1 ) (1 )

( )P e

dE P e P e e dE P e

d e e de

. (10)

The term 3,P e is the ERC if all investors were fully attentive and f, , and ω were zero.

Comparing (9) and (10), the actual ERCs differ between the two cases by the difference

between and ω. As explained above, since A(P3|e) < A(P3|e,) and ω > , the ERC in

the DD-Regime (10) is less than the ERC in the TD-Regime (9). This leads to the following

proposition.

Proposition 1: The ERC to earnings news is lower when financial statement disclosure is

delayed (DD-Regime) than when it is not (TD-Regime).

To derive implications for post-earnings announcement drift (PEAD), we calculate the

price change from the earnings announcement, date 1, to the terminal payoff, date 3. In the TD-

Regime, where both e and are disclosed, the expected price change conditional on the

earnings news e e is

3 1 3 3[ ( , ) | ] ( [ | ] [ ])E P P e e e E P e E P . (11)

Differentiating (11) with respect to earnings news e - �̅�, the PEAD coefficient is

3

3 3 3,

( [ | ] [ ]) [ | ]

( )P e

d E P e E P dE P e

d e e de

. (12)

If all investors were attentive, would be zero, so PEAD would be zero. When some

investors are inattentive, PEAD is positive, even in this case of timely disclosure. As in the

work of Hirshleifer, Lim, and Teoh (2011), the magnitude of PEAD in our study increases with

the fraction f of inattentive investors, since increases with f.

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Consider the DD-Regime, in which only e is disclosed at the earnings announcement

date and the additional financial statement item is disclosed only at the filing date. The

expectation for the price change from the earnings announcement to the terminal payoff,

conditional on the earnings news, is

3 1 3 3[ ( ) | ] ( [ | ] [ ])E P P e e e E P e E P . (13)

Differentiating (13) with respect to earnings news, we obtain the prediction for the PEAD

coefficient as

3

3 3,

( [ | ] [ ])

( )P e

d E P e E P

d e e

. (14)

Comparing (12) and (14), PEAD is larger in the DD-Regime than in the TD-Regime because

the effective weight of inattentive investors is larger in the former than in the latter, ω > .

Proposition 2: PEAD is larger when financial statement disclosure is delayed (DD-Regime)

than when it is not (TD-Regime).

Now consider the price reaction at the filing date, date 2. In the TD-Regime, the reaction

of both inattentive and attentive investors will remain unchanged at date 2. Inattentive investors

ignore information at the earnings announcement date and continue to ignore information at

the filing date. Since both pieces of information were disclosed at the earnings announcement

(date 1), the attentive investors have already reacted fully to the information, so there is no

additional reaction at the filing date (date 2).

In contrast, in the DD-Regime, there is an additional reaction at date 2. Recall that f is

the fraction of inattentive investors at date 1. We denote f’ as the fraction of inattentive investors

at the filing date. Given a fixed cost of attending and the fact that the earnings announcement

is more timely than the filing, it is reasonable to assume that f’ > f, so there are more inattentive

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investors at the filing date (date 2) than at the earnings announcement (date 1). To simplify the

derivation, we assume that investors who are inattentive at date 1 remain inattentive at date 2

and that investors who are attentive at date 1 either remain attentive (fraction 1 – f’) or become

inattentive (fraction f’ – f) at date 2. This assumption is not necessary to arrive at the conclusion.

Appendix A shows that the price at the filing date, P2, is a weighted average of beliefs by (i)

inattentive investors (fraction f), (ii) investors attentive to earnings (fraction 1– f), and (iii)

investors attentive to both earnings and the additional financial statement item (fraction f’ –

f).

The difference in the total price change from date 0 to date 2 between the TD-Regime

and the DD-Regime depends on the difference in the expectation of date 2 price E[P2|e,] in

the two cases. In the former, this expectation is the same as the expectation at date 1, because

both e and are available at date 1. This expectation is formed by the fraction f of inattentive

investors I setting price expectations at the prior date, as they do not update, and the fraction 1

– f of attentive investors that update based on both pieces of information.

In the DD-Regime, the fraction of inattentive investors remains at f. The fraction of

investors attending to e remains the same as in the TD-Regime, 1 – f . However, the fraction of

investors attending to is 1 – f’, which is smaller than in the TD-Regime because f’ > f. This

difference drives the higher conditional variance for this subgroup in the DD-Regime; therefore,

the effective weight on investors who are fully attentive to both e and is lower than in the

TD-Regime. Thus the total reaction to earnings news from date 0 to date 2 is smaller in the

DD-Regime than in the TD-Regime. Because the sensitivity of total investor response to

earnings news over dates 1 and 2 is lower in the former than in the latter, there is a greater

sensitivity to earnings news in the catch-up investor reaction after the filing date in the DD-

Regime than in the TD-Regime.10 (At the extreme, if all investors ignore filing date information,

10 Risk aversion prevents the attentive investors at the filing date from being able to fully arbitrage away the

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f’ = 1, then in the DD-Regime there is no catch-up reaction at the filing date, and all of the

catch-up reaction occurs at the terminal payoff, date 3.) This leads to the following proposition.

Proposition 3: The sum of the earnings response coefficients at the earnings announcement

date and at the filing date is lower in the DD-Regime than in the TD-Regime. PEAD after the

filing date is higher in the DD-Regime than in the TD-Regime.

2.2 Hypotheses for investor immediate and delayed reaction to earnings news

Propositions 1 and 2 show that the market reaction to earnings news, ERC, is more

muted, and that post-earnings announcement drift, PEAD, is more pronounced, when the

disclosure of the financial statement item is delayed—that is, when DD is high. Intuitively,

delaying financial statement disclosure increases arbitrage risk for attentive investors by

increasing the uncertainty about firm value at the earnings announcement date.11 As a result,

attentive investors trade less aggressively to exploit inattentive investors’ underreaction to

earnings news, which leads to a lower immediate reaction to earnings news and a greater PEAD.

Thus we have the following testable hypotheses.

H1a: Stock returns in the short announcement window are less sensitive to earnings news when

companies delay financial statement disclosure in earnings press releases. In other words,

firms with higher DD have smaller ERCs.

H1b: The post-earnings announcement return reaction (PEAD) is higher when companies

delay financial statement disclosure in earnings press releases. In other words, firms with

higher DD have larger PEAD.

Studies have found that the market reacts to news faster and more efficiently when

investors are more sophisticated (Bartov, Radhakrishnan, and Krinsky 2000), when investor

attention is greater (Hirshleifer, Lim, and Teoh 2009), and when earnings information is

mispricing induced by the inattentive investors at the earlier earnings announcement date. 11 This prediction is consistent with the Francis et al. (2007) finding that information uncertainty, proxied by the

noise in how accruals map into cash flows, positively relates to PEAD.

16

presented more saliently (Huang, Nekrasov, and Teoh 2018).12 Here, we test for a different

attention effect, one that relates to the mismatch in the timing of when firms disclose supporting

information and when investors are most attentive.

To test (H1a) and (H1b), we estimate the following regressions of cumulative abnormal

return over the earnings announcement window, CAR_EA, and over the post-earnings

announcement window, CAR_DRIFT.

CAR_EAjt = α + β1 RSUEjt + β2 DDjt + β3 RSUEjt * DDjt

+ Controls + RSUEjt * Controls +εjt, (15a)

CAR_DRIFTjt = α + β4 RSUEjt + β5 DDjt + β6 RSUEjt * DDjt

+ Controls + RSUEjt * Controls +εjt, (15b)

where CAR_EA is the cumulative abnormal return over the three-day window centered on the

earnings announcement date. CAR_DRIFT is the cumulative abnormal return over the period

starting two days after the earnings announcement for quarter t and ending one day after the

earnings announcement for quarter t+1 [+2, Next EA+1].13 RSUE is the decile rank of the

standardized unexpected earnings. We use firm size (SIZE) and analyst following

(ANA.FOLLOW) to control for information environment. We include market-to-book ratio

(MTB) to control for firm growth opportunity; past stock returns (RET) to control for changes

in the expected future performance; and institutional ownership (INST.OWN) to control for

investor base. We use the decile rank of the number of same-day earnings announcements by

other firms as a distraction proxy, as suggested by Hirshleifer, Lim, and Teoh (2009) (NRANK).

To control for potential omitted variables, we add firm fixed effects and time (year-quarter)

fixed effects to all regressions. Definitions of all variables are provided in Appendix B. If

delayed disclosure results in delayed investor response to earnings news, we predict that the

12 Huang et al. (2018) study the effects of presentation format, whereas our study examines the timing of the

disclosure of the detailed financial statement items. 13 We include the return over the next earnings announcement window since research shows that much of the

delayed investor reaction is concentrated in that period (Bernard and Thomas 1990).

17

coefficient on RSUE * DD is negative, β3 < 0, in regression (15a) and positive, β6 > 0, in

regression (15b).

We next examine the relation between DD and the market reaction to earnings news at

the 10-Q filing date and the price drift after the filing date to the next earnings announcement.

In Section 2, we derived the price at the filing date, assuming that the fraction of inattentive

investors at the filing date, f’, is greater than the fraction of inattentive investors at the earnings

announcement date: f’ > f. The assumption is consistent with the evidence in past research that

investor attention to news is higher when the news is disclosed more prominently or when

investor expectations of news arrival is higher.14 We showed that, in the DD-Regime, investors

do not fully catch up at the filing date, so there is a post-filing drift. This happens because

financial statement disclosure at the time of relatively low investor attention (the filing date) is

less effective in reducing arbitrage risk than disclosure at the time of relatively high investor

attention (the earnings announcement date). Proposition 3 of the model predicts that DD is

positively associated with a post-filing drift. Thus we have the following hypothesis:

H2: The post-filing reaction to earnings news is higher when the firm delays financial statement

disclosure. In other words, firms with higher DD have higher post-filing drift in returns.

To test H2, we estimate investor reaction between the 10-Q filing and the next earnings

announcement and around the next earnings announcement date.

14 Past empirical studies find that investor attention is influenced by, among other factors, the coverage of the

announcement in prominent media outlets (Klibanoff, Lamont, and Wizman 1998), the day of the week

(DellaVigna and Pollet 2009), the number of same day other firm earnings announcements (Hirshleifer, Lim, and

Teoh 2009), the dissemination of the announcement on social media (Blankespoor, Miller, and White 2014), and

the salience of the earnings announcement headline (Huang, Nekrasov, and Teoh 2018). Additionally, the Wall

Street Journal publishes anticipated dates when earnings will be released but not when financial statements will

be filed with the SEC, so investors are more likely to be attentive on earnings announcement dates than on filing

dates. You and Zhang (2011) make a similar argument that investors pay greater attention to earnings

announcements than 10-K filings. In the model, we assume that an information signal, in the form of financial

statement items, is more likely to be processed by investors when it is disseminated more prominently or when

investor attention is higher, i.e., in the earnings press release.

18

2.3 Hypotheses for analyst response to earnings news

Analysts expend time and effort to form earnings forecasts. When there are costs of

analyzing firm financial statements and issuing forecasts, analysts with limited resources may

devote analytical attention to the firm only at either the earnings announcement date or the

filing date each quarter, whereas less constrained analysts may analyze the firm at both event

dates. The majority of analysts—around 71% of our sample (untabulated)—issue earnings

forecasts for a given firm only once a quarter.

Given the advantage of timeliness, analysts are likely to issue forecasts as soon as

possible after the earnings announcement, all else equal. When disclosures of valuation-

relevant financial statement items are delayed until the subsequent 10-Q filing date, issuing

forecasts earlier has the advantage of timeliness, but the forecasts will be noisier and require

more effort (for estimating missing items). Delaying forecasts to after the 10-Q filing, when

the information items used in the forecast derivation are available, offers the benefits of less

effort and greater accuracy. So we expect that, when the disclosure of financial statement items

is delayed until the 10-Q filing, analysts are more likely to delay their forecasts to after the

filing date. This leads to the following hypotheses.

H3a: When companies delay financial statement disclosure, the proportion of analyst earnings

forecasts made immediately after the earnings announcement declines.

H3b: When companies delay financial statement disclosure, the proportion of analyst earnings

forecasts made after the 10-Q filing rises.

To test these hypotheses, we estimate the following regressions.

%FORECASTSjt = α1 + β1 DDjt + Controls + εjt, (16)

where %FORECASTS is the proportion of earnings forecasts issued in a specific time

subwindow, relative to the total number of earnings forecasts issued in the period starting on

the day of the earnings announcement and ending two days before the next earnings

19

announcement. We calculate %FORECASTS in four subwindows: around the earnings

announcement [0,+1] (we refer to this measure as %FORECASTS_EA), between the earnings

announcement and the 10-Q filing [+2, Filing Date-2], around the 10-Q [Filing Date-1, Filing

Date +1], and between the 10-Q and the next earnings announcement [Filing Date+2, Next EA-

2]. The relative proportion of forecasts in different time windows is designed to capture the

timing, rather than the number, of analyst earnings forecasts.

Control variables include the decile rank of standardized unexpected earnings (RSUE),

firm size (SIZE), the market-to-book ratio (MTB), past stock returns (RET), analyst following

(ANA.FOLLOW), institutional ownership (INST.OWN), and the decile of the number of same-

day earnings announcements by other firms (NRANK). We predict that the coefficient on the

delayed disclosure ratio, DD, is negative (β1 < 0) for %FORECASTS in the earnings

announcement window (H3a) and positive (β1 > 0) for %FORECASTS between the 10-Q and

the next earnings announcement (H3b).

We turn next to the hypotheses for forecast underreactions and accuracy. Consistent

with limited analyst attention (or possibly with agency issues), studies show that analysts

underreact to earnings news contained in earnings announcements (Mendenhall 1991;

Abarbanell, and Bernard 1992). Specifically, research finds that analyst earnings forecast errors

for quarter t+1 are positively correlated with earnings surprises in quarter t. Analyst

underreaction to earnings news is higher when it is more costly for analysts to obtain the

additional information needed for more efficient forecasts, that is, when the information is on

small firms and firms with lower analyst coverage.

When firms delay financial disclosure in earnings announcements, we expect the lack

of relevant items at the earnings announcement to impede the development of earnings

forecasts, leading to lower forecast accuracy and higher forecast dispersion across analysts.

Therefore, we hypothesize that delayed disclosure will be associated with (i) greater analyst

20

underreaction to earnings news, (ii) lower forecast accuracy, and (iii) higher forecast dispersion.

H4a: Analyst underreaction to earnings surprises is higher when companies delay financial

statement disclosure in earnings press releases.

H4b: Analyst forecast accuracy is lower when companies delay financial statement disclosure

in earnings press releases.

H4c: Analyst forecast dispersion is higher when companies delay financial statement

disclosure in earnings press releases.

To test these hypotheses, we estimate the following regression equations.

FUTURE.RSUEjt+1 = α + β1 RSUEjt + β2 DDjt + β3 RSUEjt*DDjt

+ Controls + RSUEjt * Controls + εjt; (17a)

ABS.FEjt+1 = α + β1 DDjt + β2 ABS.FEjt + β3 MISSjt + β4 ABS.FEjt*MISSjt

+ Controls + εjt; (17b)

STD.ESTjt+1 = α + β1 DDjt + β2 ABS.FEjt + β3 MISSjt + β4 ABS.FEjt*MISSjt

+ Controls + εjt; (17c)

where FUTURE.RSUEjt+1 is the decile rank of the analyst earnings forecast error for quarter

t+1 (Actual EPSjt+1 minus Forecasted EPSjt+1), scaled by the stock price at the end of quarter

t, and Forecasted EPSjt+1 is the median of forecasts issued either (i) between the earnings

announcement and the 10-Q filing, or (ii) between the 10-Q filing and the next earnings

announcement. ABS.FEjt+1 is the absolute value of analyst earnings forecast error for quarter

t+1 (Actual EPSjt+1 minus Forecasted EPSjt+1), scaled by the stock price at the end of quarter

t. STD.ESTjt+1 is the standard error of analyst earnings forecasts for quarter t+1, scaled by the

stock price at the end of quarter t. MISSjt equals one if quarter t earnings miss the analyst

forecast and zero otherwise. Controls is the same set of control variables as in equation (1). We

expect the coefficient on RSUEjt*DD in equation (17a), the coefficient on DD in equation (17b),

and the coefficient on DD in equation (17c) to all be positive.

21

3 Sample, data, and empirical results

3.1 Sample and data

We obtain financial statement information included in quarterly earnings

announcements from the Compustat Preliminary History database (Preliminary), company

financial data in 10-Q filings from Compustat, stock returns and prices from CRSP, and

analysts’ earnings forecasts from I/B/E/S. Following the literature, we exclude utilities and

financial services firms (SIC codes 4900–4999 and 6000–6999). Our sample covers all years

available on the Preliminary History database from 1990 through 2013, excluding 1999, when

Compustat collected only limited items from earnings announcements.15 We drop observations

for the fourth fiscal quarter (Section 4.8 examines them), observations with less than three

trading days between the earnings announcement date and the 10-Q filing date, and

observations with less than five financial statement items in any of the three financial

statements (income statement, balance sheet, and statement of cash flows) in the 10-Q filing.

The final sample for the market reaction tests consists of 121,807 firm-quarter observations.

For the analyst response tests, we also require at least one forecast for the next quarter earnings

issued after the current quarter’s earnings announcement. The final sample for the analyst

reaction tests consists of 66,763 observations. Appendix C describes the details of the sample

selection.

3.2 Measure of delayed financial statement disclosure

To measure the delay of financial statement disclosure in earnings press releases, we

calculate the delayed disclosure ratio, DD, which equals the number of financial statement

15 To check the accuracy of the Prelim data, we select a random sample of 50 firms with available observations

before and after 1999. We then manually identify financial statement items disclosed in earnings press releases

and compare the delayed disclosure ratio based on the manually collected data and the ratio based on the Prelim

data. The Spearman correlation between the two ratios exceeds 0.90 both before and after 1999, suggesting that

the delayed disclosure measure based on the Prelim data is reasonably accurate.

22

items that are not disclosed in the earnings press release but reported in the corresponding 10-

Q filing scaled by the number of financial statement items reported in the 10-Q filing. The

Preliminary database is used to identify which financial statement items are disclosed for a

given firm-quarter earnings announcement.16 We calculate DD as a simple fraction of delayed

items rather than as a dollar value-weighted ratio because market participants do not know the

value of delayed items at the time of the earnings announcement. Also, it is not clear whether

items with relatively large magnitudes, such as cost of goods sold and goodwill, are more

important than items with relatively small magnitudes, such as operating income and

inventory.17

In calculating DD, our goal is to construct a simple and objective measure that captures

overall delay of financial statement information and to relate this measure to the delayed

reaction to earnings news. An alternative approach would be to analyze delayed disclosure of

individual items or groups of items with distinct functional roles. Our approach has two

advantages. First, which items are more (less) important likely depends on the industry, the

economic conditions, the disclosure of related items, and other factors. Second, firms that delay

disclosure of some items are also more likely to delay disclosure of other items. The overlap

makes it empirically difficult to classify delayed items into categories with distinct roles. This

also suggests that DD is a reasonable construct of overall delay in financial statement disclosure.

3.3 Descriptive statistics

Table 1 presents descriptive statistics. The average fraction of financial statement items

16 Delayed disclosure is measured by comparing the disclosure in the earnings press release with the disclosure in

the same quarter 10-Q filing. As a robustness check, we also calculate DD by comparing items disclosed in the

earnings press release with items reported in the 10-Q filing for the same quarter last year. The correlation between

this DD and our main measure is 0.9982. All our results are qualitatively and quantitatively similar when using

this alternative DD measure (untabulated). 17 Nevertheless, most of the results hold when using dollar value–weighted DD. Higher dollar value–weighted

DD is negatively (positively) associated with the fraction of analyst forecasts issued immediately after the earnings

announcement (after the 10-Q filing) and the market reaction to earnings news immediately around the earnings

announcement (after the 10-Q filing) (untabulated).

23

that are delayed till the 10-Q filing, DD, is 57.2%.18 The average number of analysts issuing

earnings forecasts immediately after the earnings announcement, FORECASTS_EA, is 3.992.

The average proportion of such forecasts relative to all forecasts, %FORECASTS_EA, is 39.6%.

The average proportion of earnings forecasts issued after the 10-Q, %FORECASTS_[Filing+2,

Next EA-2], is 39.2%. As in other studies that use analyst forecasts, firms in our sample are

relatively large, with a mean (median) market capitalization, MV, of $2,301.3 ($295.9) million.

DD exhibits significant variation with an interquartile range of 0.430 to 0.803. Variation

in DD comes mainly from the variation in the number of items withheld in the earnings

announcement, rather than the variation in the number of items in the 10-Q filing. The

correlation between DD and the number of items withheld in the earnings announcement is

0.992, whereas the correlation between DD and the number of items in the 10-Q filing—that

is, the denominator of the DD ratio—is -0.070 (untabulated). Most of the variation in DD is

due to cross-sectional rather than within-firm variation. Individual firms typically do not make

big period-to-period changes in the amount of information that is withheld at the earnings

announcement. The correlation between DD in the current quarter and DD in the same quarter

last year is 0.71 (untabulated). All our tests control for firm fixed effects, so our research focus

is on within-firm changes in DD. In additional analysis, we also estimate tests using a change

specification.

Table 2 reports correlations among variables. Consistent with H3a and H3b, DD is

negatively associated with the proportion of earnings forecasts issued immediately after the

earnings announcement, %FORECASTS_EA, and positively associated with the proportion of

earnings forecasts issued after the 10-Q filing (correlations -31.7% and 20.5%, respectively).

DD is also negatively associated with firm size, analyst following, and institutional

18 The average percentage of delayed income statement, balance sheet, and cash flow statement items is 24.7%,

51.5%, and 86.4%, respectively (untabulated). The descriptive statistics are comparable with those of D’Souza et

al. (2010).

24

ownership.19

Figure 2 shows graphically %FORECASTS for firms in the bottom decile of DD (the

solid blue line) and firms in the top decile of DD (the dashed red line). The horizontal axis

shows time intervals between the current and next earnings announcement. The vertical axis

shows the portion of earnings forecasts issued by the indicated point in

time: %FORECASTS_[0, τ], where τ = +1, Filing Date-2, Filing Date+1, or Next EA-2. As the

figure reveals, the portion of earnings forecasts issued within two trading days is notably lower

when DD is high (14.1% for high DD versus 53.0% for low DD). Conversely, the portion of

analyst forecasts delayed until after the 10-Q filing is greater when DD is high (56.6% for high

DD versus 32.8% for low DD).20

3.4 Main results

Our first test examines whether investor immediate reaction to earnings news is weaker

for firms that delay financial statement disclosure (H1a). Table 3 shows the results of the

regression of the firm stock return on RSUE*DD and control variables. To check whether total

reaction to earnings news is associated with DD, we first examine the investor reaction over

the window that covers both the announcement and post-announcement windows (columns 1

and 2). The coefficient on RSUE*DD is insignificant (-0.014, p = 0.215), suggesting that the

informativeness of earnings news does not relate significantly to DD. The remaining four

columns show results for investor immediate reaction. Results in columns 3 and 4 establish the

baseline for the average ERC in our sample. Consistent with the results of other studies,

announcement window returns are positively associated with earnings surprise (coefficient =

0.082, p <0.001). Consistent with H1a, the coefficient on RSUE*DD is negative and significant

19 Together, firm size, institutional ownership, and analyst following explain 12.1% of the variation in DD based

on regression R2 (untabulated). 20 While Figure 2 also suggests that there is a positive association between DD and %FORECASTS_[EA+2, Filing

Date -2], the results in the next section show that this association is negative and insignificant in the multivariate

analysis.

25

(-0.036, p <0.001), indicating that the immediate price reaction to earnings surprises is weaker

when firms delay financial statement disclosure. An increase in DD from zero to one

corresponds to a decrease in ERC of approximately 44% (-0.036/0.082=-44%). Importantly,

the total reaction is not significantly associated with DD, which suggests that the lower

immediate reaction for these firms is due to delayed response to earnings news rather than

differences in earnings informativeness.

Table 4 directly tests the relation between DD and investor delayed reaction to earnings

news (H1b). If firms with higher DD experience greater delay in investor reaction to earnings

news, we expect a stronger association between earnings surprise, RSUE, and abnormal return

after the earnings announcement, CAR_DRIFT. Panel A reports results of the regression of

CAR_DRIFT on RSUE*DD and control variables. The first two columns establish the

benchmark for the magnitude of the average delayed reaction in our sample. Consistent with

the post-earnings announcement drift, the coefficient on RSUE is positive and significant

(0.054, p <0.001). Consistent with H1b, the coefficient on RSUE*DD in the last two columns

is positive and significant (0.025, p =0.032), suggesting that investor delayed reaction to

earnings news is greater when DD is high. An increase in DD from zero to one corresponds to

an increase in PEAD of approximately 46% (0.025/0.054=46%).21

We next examine, in greater detail, when investor delayed reaction is corrected. If

inattentive investors are not focusing on the firm at the 10-Q filing date, then the delayed

reaction associated with DD will not be eliminated immediately at the filing date (H2). Instead,

the association between DD and the post-earnings announcement drift will continue even after

the remaining information becomes publicly available.

21 We add further robustness checks. In addition to year fixed effects, we add a control for a time trend in the

immediate and delayed response to earnings news by including an interaction between RSUE and a time trend

variable. The time trend variable is the natural logarithm of (year – 1988), and year is the observation’s fiscal year

from 1989 to 2013 (Collins, Li, and Xie 2009). The untabulated results are consistent with those in Tables 3 and

4. As another robustness check, we use earnings surprise based on a seasonal random walk instead of analyst

forecasts, and find similar results.

26

Table 4 Panel B shows the results of the return tests for the following subwindows:

between the earnings announcement and the 10-Q filing (columns 1 and 2), around the 10-Q

(columns 3 and 4), between the 10-Q and the next earnings announcement (columns 5 and 6),

and around the next earnings announcement (columns 7 and 8). Consistent with the delayed

reaction to earnings news stemming from the delay of supporting financial information till the

10-Q filing, there is no correction before the 10-Q. Instead, the relation between DD and

investor reaction is negative and insignificant in the window prior to the filing date (-0.004, p

= 0.308). The results in columns 3 and 4 indicate that there is also no significant immediate

correction at the time of the 10-Q filing, which is consistent with the idea that investors do not

pay as much attention to 10-Q filings as they do to earnings announcements. The correction of

the delayed reaction happens only after the 10-Q filing. The coefficient on RSUE*DD is

positive after the 10-Q filing (0.023, p = 0.010) and around the next earnings announcement

(0.005, p = 0.044). The results indicate that the relation between DD and investor reaction to

earnings news extends beyond the time of arrival of the delayed information.

Figure 3 shows graphically the timing of investor reaction to earnings news for firms

with DD=0 (the solid blue line) and firms with DD=1 (the dashed red line).22 Consistent with

the results in Tables 3 and 4, the delayed reaction starts at the earnings announcement. The

delayed reaction is not corrected before or immediately at the time of the 10-Q filing but

persists beyond the filing date and is corrected only after the next earnings announcement. As

a result, firms that have a greater portion of financial disclosure delayed till the 10-Q filing also

have a greater portion of the total market reaction delayed until after the filing. Specifically,

54.2% (27.4%) of reaction is delayed until after the filing when DD=1 (DD=0).

We next test the association between delayed disclosure and analyst delayed response

to earnings news (H3a and H3b). Table 5 columns 1 and 2 show the results for the portion of

22 The notes to Figure 3 provide details on how the graph is constructed.

27

forecasts issued in the earnings announcement window, %FORECASTS_EA. Consistent with

H3a, the coefficient on DD is negative and significant (-0.019, p =0.006). This indicates that,

when firms delay financial statement disclosure, the portion of timely analyst forecasts

decreases.

The remaining columns show the results for the proportion of delayed analyst forecasts

issued in three post-announcement subwindows: between the earnings announcement and the

10-Q filing (columns 3 and 4), around the 10-Q (columns 5 and 6), and between the 10-Q and

the next earnings announcement (columns 7 and 8). There is no significant relation between

DD and %FORECASTS between the earning announcement and the 10-Q (-0.007, p =0.292).

The results in columns 5 and 6 indicate that there is no significant immediate response to the

10-Q filing (0.001, p =0.331), while the positive and highly significant coefficients in the last

two columns indicate that analysts respond to the arrival of information in the 10-Q filing with

a delay (0.025, p <0.001).

Overall, the results in Table 5 are consistent with (H3a) and (H3b). When firms delay

financial statement disclosure, analysts are less likely to issue earnings forecasts following the

earnings announcement and more likely to do so after the 10-Q. The relation between DD and

the timing of earnings forecasts does not disappear immediately when the delayed information

arrives in the 10-Q filing but persists beyond the filing date.

We next test whether delayed disclosure is associated with the magnitude of analyst

underreaction to earnings news (H4a), analyst forecast accuracy (H4b), and analyst forecast

dispersion (H4c). Table 6 Panel A presents the results of the regression of future earnings

forecast error, FUTURE.RSUE, on current earnings surprise, RSUE, the interaction variable of

interest, RSUE*DD, and control variables. To establish the baseline for the magnitude of

average analyst underreaction in our sample, we first estimate a regression of FUTURE.RSUE

and the 10-Q filing on RSUE and control variables (columns 1 and 2). Consistent with the prior

28

research, current earnings surprise is significantly positively associated with future earnings

forecast error (coefficient = 0.218, p <0.001). Consistent with H4a, the coefficient on

RSUE*DD is positive and significant (0.066, p = 0.010). When compared to the average analyst

underreaction, the magnitude of the coefficient on RSUE*DD indicates that an increase in DD

from zero to one corresponds to an increase in the analyst underreaction of approximately 30%

(0.066/0.218= 30%). The last two columns show the results for forecasts issued after the 10-Q

filing. The coefficient on RSUE*DD is positive and significant (0.059, p = 0.033), indicating

that the underreaction persists even after the arrival of supporting information in the 10-Q.

These findings corroborate the conclusion from the market tests that there is immediate

underreaction and that the underreaction persists after the filing date.

The results of the regression of absolute analyst forecast errors on DD reveal a similar

pattern (Panel B of Table 6). Consistent with H4b, the coefficient on DD is positive and

significant (0.003, p < 0.001), suggesting that analyst forecast accuracy is lower when firms

delay financial statement disclosure. The coefficient on DD is also significant after the filing

date (0.003, p < 0.001).

In Panel C, we find a positive association between DD and analyst forecast standard

errors (0.001, p < 0.001), which is consistent with disclosure delay increasing forecast

dispersion (H4c). DD effects again persist after the filing of 10-Q, as evidenced by a positive

coefficient on DD in the post-filing window (0.001, p < 0.001).

4 Robustness tests and additional analyses

4.1 Adding further controls and using residual delayed disclosure ratio

To examine whether the relation between DD and investor and analyst response to

earnings news is incremental to other factors that may affect the choice of DD, we perform the

following two-stage analysis. In the first, we regress DD on an expanded set of explanatory

29

variables and calculate residual DD, RES.DD. In the second, we re-estimate the investor and

analyst response tests using RES.DD. The first-stage regression is as follows.

DDjt = α + β1 RSUEjt + β2 SIZEjt + β3 MTBjt + β4 RETjt + β5 ANA.FOLLOWjt

+ β6 INST.OWNjt + β7 EA.LAGjt + β8 SMOOTHjt + β9 JMOBjt

+ β10 PRO.FORMAjt + β11 SPEC.ITEMjt + β12 EARN.VOLjt + β13 LOSS jt

+ β14 NEG.SUE jt + β15 HIGH.TECHjt + β16 MERGERjt + β17 YOUNGjt

+ β18 RET.VOLjt + β19 BIG4jt + εjt.

(18)

In addition to the base set of control variables in the main analysis (SIZE, MTB, RET,

ANA.FOLLOW, INST.OWN, and NRANK), we use numerous additional control variables. We

add a control for the timing lag between the fiscal quarter end and the earnings announcement

date (EA.LAG), since the fraction of financial statement items disclosed in the earnings

announcement is likely to be negatively associated with the earnings announcement lag

(Schroeder 2016). We add a proxy of income smoothing (SMOOTH) and an indicator of the

firm just meeting or beating earnings expectations (JMOB), to proxy for managerial incentives

to intervene in the earnings reporting process (D’Souza et al. 2010). We also include an

indicator for the use of pro forma earnings (PRO.FORMA), since Regulation G requires

companies to disclose items excluded from pro forma earnings. Following Chen et al. (2002),

we also include variables to capture settings in which current earnings are less likely to be a

sufficient valuation metric: earnings volatility (EARN.VOL), an indicator of negative earnings

(LOSS), an indicator of negative earnings surprise (NEG.SUE), a high-tech industry indicator

(HIGH.TECH), an indicator of mergers and acquisitions (MERGER), an indicator of special

items (SPEC.ITEM), a young firm indicator (YOUNG), and an indicator of high return volatility

(RET.VOL). To proxy for the effect of the auditor, we include an indicator of a Big Four auditor

(BIG4). All variables are defined in Appendix B.

The results of the estimation of equation (18) are reported in Table 7 Panel A. DD tends

to be lower for large firms as well as for those with greater analyst following, institutional

30

ownership, and Big Four auditors, suggesting that firms with richer information environments

disclose more financial statement items at earnings announcements. DD is lower for firms that

use pro forma earnings, consistent with the prediction that the disclosure of items excluded

from pro forma earnings reduces delayed disclosure. DD also tends to be lower for firms with

special items, higher earnings volatility, and losses, as well as for high-tech firms and young

firms, suggesting that managers provide financial statement disclosures when future earnings

are more uncertain. Table 7 Panel B reports the results of investor and analyst response tests

using the residual DD variable. The results are similar to those in Tables 3–6, indicating that

our results are robust to adding further controls and using the residual DD measure.23

4.2 Instrumental variable approach

We employ an instrumental variable approach to further mitigate the concern about

potential omitted correlated variables influencing the degree of delayed disclosure. Our

approach follows Holzman, Marshall, Schroeder, and Yohn (2019), who use disclosure by

industry peers to instrument the firm’s disclosure in earnings press releases. The measure is

likely to be a reasonable instrument since the industry peers’ disclosure is not chosen by the

firm but is a significant predictor of the firm’s disclosure. Specifically, our instrument for DD

is the median delayed disclosure ratio in the same four-digit SIC industry in the previous quarter.

The instrument for DD*RSUE is the interaction of the instrument for DD and RSUE. The results

of this analysis, not tabulated for brevity, are consistent with the findings from our main tests.

23 We conduct two sets of robustness tests. First, we add earnings announcement lag, special items indicator, loss

indicator, indicator of negative earnings surprise, and their interactions with earnings surprise as additional

controls to the main regressions in Tables 3-6. The results of the key independent variables—RSUE*DD in Tables

3-4 and Table 6 (Panel A) and DD in Table 5 and Table 6 (Panels B and C)—are robust. Next, regarding the

residual DD variable in the 2SLS regressions in Table 7, we also add the additional controls in the second stage

regression. The results for the key independent variables relating to residual DD remain robust. Since residual DD

is orthogonal to the control variables used in the first stage, the two-stage approach avoids the need to include, in

the second stage, a large number of interactions, RSUEjt*Controljt, that are highly correlated with each other, and

thus increases the reliability of the empirical inferences.

31

4.3 Robustness tests using year-over-year changes

Our main tests use firm fixed effects to isolate within-firm variation in delayed

disclosure and control for potential omitted variables. We re-estimate our tests using the change

specification as an alternative. Specifically, for each dependent and independent variable, we

calculate the year-over-year change and estimate regression using these changes. Untabulated

results are consistent with the results using firm fixed effects.

4.4 Management guidance

Many firms provide earnings guidance during earnings announcements. To ascertain

whether DD effect is incremental to investor and analyst response to earnings guidance, we

add a control for guidance surprise. Similar to earnings surprise, we measure guidance surprise

as the decile rank of the difference between earnings guidance and consensus forecast. We also

include an indicator variable that equals one if the firm issues earnings guidance and zero

otherwise. Untabulated results show that the results are robust to controlling for earnings

guidance.

4.5 Conference calls

Companies often hold conference calls around their earnings announcements.

Kimbrough (2005) finds that analyst and investor underreaction to earnings news is lower after

firm-initiated conference calls. To examine the incremental effect of DD, we calculate an

indicator variable that equals one if there is a conference call during the earnings announcement

window [-1,+1] and zero otherwise. We also try a conference call initiation indicator that equals

one after the firm initiates earnings calls and zero otherwise. Untabulated results show that our

results are robust to controlling for conference calls.

4.6 Early and late subperiods

The financial reporting environment changed over the sample period. In particular,

32

Regulation G (Reg G), adopted by the Securities and Exchange Commission in 2003, requires

firms that supplement GAAP earnings by non-GAAP earnings to quantitatively reconcile the

two measures. Since items excluded from pro forma earnings must be disclosed, the

reconciliation can reduce delayed disclosure if the firm did not disclose those items before.

Consequently, we test the effect of DD before and after Reg G. Untabulated results show that

the effect of DD is significant in both subperiods.

4.7 Annual earnings announcements

Our analyses are based on quarterly earnings announcements for the first three quarters.

Since annual financial statements are audited, whether the audit has been completed may affect

financial statement disclosure in annual earnings announcements and the market response to

annual earnings news (Schroeder 2016; Marshall, Schroeder, and Yohn 2019).24 We examine

the effect of delayed disclosure on the market reaction to annual announcements where we

control for the audit completion. Similar to the findings for quarterly announcements, delayed

disclosure is significantly negatively associated with the immediate market reaction. In contrast,

the association between delayed disclosures and delayed reaction to annual announcements is

not statistically significant, which may be partially explained by the Rangan and Sloan (1998)

finding that the post-earnings-announcement drift is relatively smaller after annual

announcements than after quarterly announcements.25

24 Schroeder (2016) finds that completed audits at the earnings announcement date enhance the information

content of additional financial statement items at the annual earnings announcement. Marshall et al. (2019) find

that the market places more weight on good annual earnings news announced after audit completion. Our study

differs from these studies in that we study quarterly earnings that do not have audit-related issues. In addition, our

limited attention approach affords predictions for post-event investor reactions, whereas the credibility effect from

completed audits in these studies predicts only earnings announcement period reactions and not post-event

reactions. 25 The lower magnitude of PEAD after annual announcements is likely to result in a lower test power. We find

that even though the magnitude of the coefficient on RSUE*DD might suggest an economically meaningful effect

when compared to the average PEAD after annual announcements, the coefficient is not statistically significant.

33

4.8 Delayed disclosure for income statement, balance sheet, and statement of cash flows

Our findings indicate that delayed disclosure of financial statement information has, on

average, a negative effect on how the market processes earnings news. However, the effect of

delayed disclosure may differ across financial statements. For example, Holzman et al. (2019)

show that investors do not always benefit from greater disclosure of income statement items.

We thus examine how the effect of delayed disclosures on investor reaction to earnings news

varies for the income statement, balance sheet, and statement of cash flows. Table 8 reports the

results of estimating regressions (15a) and (15b) using the delayed disclosure separately for the

income statement (DD.IS), the balance sheet (DD.BS), and the statement of cash flows

(DD.SCF). The results show that the delayed disclosure of each of the three statements is

negatively associated with the immediate reaction to earnings news. In contrast, the positive

effect on the post-earnings announcement drift is largely attributable to the delayed disclosure

of balance sheet items.26

4.9 Analyst experience

Bradshaw, Lee, and Peterson (2016) suggest that inexperienced analysts are more likely

to experience forecasting difficulties. We therefore examine whether delayed disclosure has a

stronger effect on inexperienced analysts. We obtain the number of prior quarters for which the

analyst has issued earnings forecast for the firm, partition the analysts in the bottom (top)

quartile as the low (high) experience group, and rerun the analyst reaction tests separately for

the two groups. Untabulated results show that the negative relation between DD and the

proportion of timely forecasts is more pronounced among inexperienced analysts than among

experienced analysts. In contrast, the effects of DD on analyst underreaction to earnings news,

forecast dispersion, and forecast accuracy are similar for both groups. These findings suggest

26 Holzman et al. find that delayed disclosure of operating income items increases PEAD, whereas delayed

disclosure of nonoperating income items decreases PEAD, so the net PEAD effect from delayed disclosure of

items in the overall income statement is weak, which is consistent with our finding.

34

that inexperienced analysts take more time to issue forecasts when DD is high. When they do

issue forecasts, the effects of DD on their forecast quality resemble those for experienced

analysts.

5. Conclusion

A large body of research finds that investors and analysts are slow in updating

expectations about future earnings following earnings news announced in earnings press

releases. This study examines the link between the delay of investor and analyst reaction to

earnings news and delayed financial statement disclosure in earnings press releases. We show

that, for companies that delay financial statement disclosure until the 10-Q filing, investor

immediate reaction to earnings is weaker and investor delayed reaction to earnings after the

10-Q is stronger. We also show that analysts are less likely to issue earnings forecasts after the

earnings announcement and more likely to issue forecasts after the 10-Q filing. Delayed

disclosure is positively associated with analyst underreaction to earnings news and forecast

dispersion and negatively associated with forecast accuracy. Overall, the results suggest that,

when firms delay financial statement disclosure in earnings announcements, investors and

analysts have greater difficulty processing and responding to earnings news.

Our study complements work on expanded financial statement disclosure in earnings

press releases. Research has examined the role of expanded disclosure as a source of additional

information news, which can be viewed as competing with earnings when earnings are less

value relevant. Our study contributes to this literature by showing that delayed financial

statement disclosure is associated not only with a lower amount of information contained in

earnings press releases but also with a delay in investor and analyst reaction to earnings news

that continues even after the delayed financial information is disclosed in 10-Qs/Ks. The

findings are consistent with alleged benefits in the call by regulators and financial

intermediaries for greater financial statement disclosure in earnings press releases.

35

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38

Appendix A: Price at the filing date for delayed disclosure regime

This appendix describes date 2 price in the delayed disclosure regime (DD-Regime) in the

model of Section 2. Date 1 is the earnings announcement. Date 2 is the 10-Q filing. And date

3 is the terminal payoff. The fraction of inattentive investors is f at date 1 and f’ at date 2. Given

the fixed cost of attending and the greater timeliness of the earnings announcement compared

to the 10-Q filing, it is reasonable to assume that f’ > f, so there are more inattentive investors

at date 2 than at date 1. Inattentive investors I at date 1 will continue to be inattentive at date 2.

Investors paying attention at date 1 observe e but not (as it is unavailable), and investors

paying attention at date 2 observe both e and . Thus a fraction 1 – f’ of investors pay attention

to both e and , and an additional fraction f’ – f of investors pay attention only to e. We use

superscripts I, e, and (e,) to denote the three investor groups.

The date 2 price is determined by market clearing, so that the total demand for the risky

asset by the three investor groups equals its outstanding supply. The pricing equation at date 2

will be a weighted average of beliefs of these three groups of investors, and the weights depend

on f and f’ as well as the respective precision ((P3) = 1/var(P3)) of the terminal value P3 as

perceived by them.

],|[]|[][),( 3,,

332 ePEePEPEeP eeeeII , (1A)

where 3,

3 3 3

( )

( ) ( ' ) ( | ) (1 ') ( | , )

II

I e e

f P

f P f f P e f P e

(2A)

3,

3 3 3

( ' ) ( | )

( ) ( ' ) ( | ) (1 ') ( | , )

ee

I e e

f f P e

f P f f P e f P e

(3A)

,

, 3,

3 3 3

(1 ') ( | , )

( ) ( ' ) ( | ) (1 ') ( | , )

ee

I e e

f P e

f P f f P e f P e

(4A)

39

Appendix B: Variable definitions

Variable Definition

ABS.FE The absolute value of earnings forecast error for quarter t+1

(Actual EPSjt+1 minus Forecasted EPSjt+1) scaled by the stock price

at the end of quarter t. Forecasted EPSjt+1 is the median of all

forecasts issued after the quarter t earnings announcement and

before the earnings announcement for quarter t+1. Forecast errors

in two subwindows are also examined: before the 10-Q filing, [0,

Filing Date -2], and after the 10-Q filing, [Filing Date, Next EA-2].

ANA.FOLLOW Analyst following, measured as the natural logarithm of the number

of analysts following the firm.

BIG4 The indicator variable that equals one if the firm’s annual financial

statement was audited by Deloitte, PricewaterhouseCoopers, Ernst

& Young, or KPMG.

CAR[window] The cumulative abnormal return over a given time window. Five

subwindows are used: around the earnings announcement [-1,+1],

between the earnings announcement and the 10-Q filing [+2, Filing

Date -2], around the 10-Q [Filing Date -1, Filing Date +1], between

the 10-Q and the next earnings announcement [Filing Date +2, Next

EA -2], and around the next earnings announcement [Next EA -1,

Next EA +1]. The abnormal return is calculated as the raw stock

return minus the return on the respective Fama-French reference

portfolio based on size and book-to-market ratio (six portfolios are

formed based on size and book-to-market, 2 x 3).

CAR_DRIFT CAR for the period starting two days after the earnings

announcement for quarter t and ending one day after the earnings

announcement for quarter t+1 [+2, Next Earnings Announcement

Date +1].

CAR_EA CAR for the earnings announcement window [-1,+1].

DD The delayed disclosure ratio, calculated as the number of financial

statement items that are missing in the earnings announcement but

reported in the corresponding 10-Q filing for a given firm-quarter

scaled by the number of nonmissing financial statement items

reported in the corresponding 10-Q filing.

DD.IS, DD.BS, and DD.SCF are the delayed disclosure ratios of

income statement items, balance sheet items, and cash flow

statement items, respectively.

EA.LAG The natural logarithm of the number of days between the fiscal

quarter end and the earnings announcement date for quarter t.

40

EARN.VOL The standard deviation of earnings before extraordinary items

scaled by total assets, calculated over past eight quarters.

%FORECASTS_[window] The number of analyst earnings forecasts issued in a given

subwindow divided by the total number of earnings forecasts issued

in the window starting on the day of the earnings announcement

and ending two days before the earnings announcement for quarter

t+1. Four subwindows are used: around the earnings announcement

[0,+1], between the earnings announcement and the 10-Q filing

[+2, Filing Date -2], around the 10-Q filing [Filing Date -1, Filing

Date +1], and between the 10-Q filing and the next earnings

announcement [Filing Date +2, Next EA -2].

%FORECASTS_EA %FORECASTS for the earnings announcement window [0,+1].

FUTURE.RSUE The decile rank of the analyst earnings forecast error for quarter

t+1 (Actual EPSjt+1 minus Forecasted EPSjt+1) scaled by the stock

price at the end of quarter t, where Forecasted EPSjt+1 is the median

of all forecasts issued after the earnings announcement for quarter

t and before the earnings announcement for quarter t+1. Forecast

errors in two subwindows are also examined: before the 10-Q filing

[0, Filing Date -2] and after the 10-Q filing [Filing Date, Next EA-

2].

HIGH.TECH The indicator variable that equals one for firms in the following

industries: drugs (SIC code 2833–2836), R&D services (8731–

8734), programming (7371–7379), computers (3570–3577),

electronics (3600–3674), and precise measurement instruments

(3810–3845).

INST.OWN Institutional ownership, measured as the sum of all institutional

holdings of the stock scaled by the number of shares outstanding.

The measure is based on the most recent institutional ownership

data available in month t-1.

JMOB The indicator variable that equals one if the current earnings

surprise is between 0 and 3 cents per share and zero otherwise.

LOSS The indicator variable that equals one if the firm reports a negative

net income before extraordinary items in the current quarter and

zero otherwise.

MERGER The indicator variable that equals one if the firm engages in

mergers and acquisitions in the current quarter and zero otherwise.

MISS The indicator variable that equals one if quarter t earnings are

below the analyst forecast and zero otherwise.

MTB The market-to-book ratio measured at the end of the fiscal quarter

t.

41

NEG.SUE The indicator variable that equals one if quarter t earnings are less

than the consensus earnings forecast (or less than earnings for the

same quarter last year when analyst consensus forecast is not

available), and zero otherwise.

NRANK The decile rank of the number of same-day earnings

announcements by other firms.

PRO.FORMA The indicator variable that equals one if IBES actual earnings per

share is not equal to earnings per share excluding extraordinary

items (Compustat item EPSPXQ) and zero otherwise.

RET The stock returns prior to the earnings announcement measured

over the window [-60,-3].

RET.VOL The indicator variable that equals one if the standard deviation of

daily stock returns over prior 250 days is above industry median

and zero otherwise.

RSUE The decile rank of standardized unexpected earnings, SUE, where

SUE is calculated as the difference between announced quarterly

earnings as reported by I/B/E/S and the consensus earnings

forecast, scaled by stock price at the end of previous fiscal quarter.

When consensus analyst forecast is not available, SUE is calculated

as announced earnings minus earnings for the same quarter last

year, scaled by stock price at the end of previous fiscal quarter.

SIZE The natural logarithm of market value of equity at the end of the

fiscal quarter t.

SMOOTH The correlation between change in total accruals and change in

operating cash flows over past eight quarters, multiplied by -1.

SPEC.ITEM The indicator variable that equals one if the special item variable

(SPIQ) in Compustat is non-zero, and zero otherwise.

STD.EST The standard error of analyst forecasts for quarter t+1 EPS that are

issued after the quarter t earnings announcement and before the

earnings announcement for quarter t+1, scaled by the stock price at

the end of quarter t. Standard errors of forecasts in two subwindows

are also examined: before the 10-Q filing, [0, Filing Date -2], and

after the 10-Q filing, [Filing Date, Next EA-2].

YOUNG The indicator variable that equals one if the firm’s age is below the

two-digit SIC industry median and zero otherwise. Firm age is the

number of years from initial public listing to the current fiscal

quarter.

42

Appendix C: Sample selection

Firm-quarter observations from the Compustat Preliminary History database over

1990–2013, excluding year 1999 486,742

minus: Utilities and financial services firms (SIC codes 4900–4999 and 6000–

6999) (116,878)

minus: Observations with less than three days between the earnings announcement

date or with the earnings announcement date before fiscal quarter end (10,138)

minus: 10-Q/K financial statements have less than five data items (7,746)

minus: No preliminary data (64,416)

minus: Missing stock return data from CRSP (116,503)

minus: The 4th fiscal quarters (49,254)

Sample for Market Reaction Tests 121,807

minus: No analyst earnings forecasts for the next quarter after the current quarter’s

earnings announcement (55,044)

Sample for Analyst Reaction Tests 66,763

43

Date 2

Filing date

Date 1

Earnings announcement

Shareholders receive

terminal payoff, P3

Date 3

Terminal date

Fraction of inattentive

investors, f’ > f Fraction of inattentive

investors, f Price, P0

Firm releases earnings, e,

and financial statement item, δ

Firm releases earnings, e Firm releases financial

statement item, δ

Figure 1: Timeline for the model

Timely disclosure regime

(TD-Regime):

Delayed disclosure regime

(DD-Regime):

Date 0

Prior to earnings

announcement

44

0%

20%

40%

60%

80%

100%

PER

CEN

TAG

E O

F A

NA

LYST

S FO

REC

AST

S

TIME

Low DD

High DD

Next EA10-Q/K FilingEA

Figure 2: Analyst delayed response to earnings announcements

This figure shows the timing of analyst earnings forecasts for firms with DD in the bottom decile (the

solid blue line) and firms with DD in the top decile (the dashed red line). The horizontal axis shows

time intervals between the current earnings announcement and next earnings announcement. The

vertical axis shows the fraction of total forecasts that are issued by the indicated point in

time: %FORECASTS_[0, τ], where τ = +1, Filing Date-2, Filing Date+1, or Next EA-2. All variables

are defined in Appendix B.

EA-1 EA+1 Filing-2 Filing+1 Next EA-2

Low DD 0.0% 53.0% 65.3% 67.2% 100.0%

High DD 0.0% 14.1% 38.4% 43.4% 100.0%

45

0%

20%

40%

60%

80%

100%P

ERC

ENTA

GE

OF

REA

CTI

ON

CO

MP

LETE

D

TIME

DD=0

DD=1

Next EA10-Q/K FlingEA

Figure 3: Investor delayed response to earnings announcements

This figure shows the timing of investor reaction to earnings news for firms with DD=0 (the solid blue

line) and firms with DD=1 (the dashed red line). The vertical axis shows the percentage of total reaction

completed. The horizontal axis shows time intervals between the current earnings announcement and

next earnings announcement. The graph is constructed the following way: We run regressions CAR = α

+ β1 RSUE + β2 DD + β3 RSUE * DD + Controls + ε with CAR over different windows [-1, τ], where τ

= +1, Filing Date-2, Filing Date+1, Next EA-1, or Next EA+1. All variables are defined in Appendix

B. For firms with DD=0, the reaction up to time τ, relative to the total reaction, is β1[-1, τ]/β1[-1, Next

EA+1]. For firms with DD=1, the reaction up to time τ, relative to the total reaction, is (β1[-1, τ]+ β3[-

1, τ])/(β1[-1, Next EA+1]+β3[-1, Next EA+1]).

EA-1 EA+1 Filing-1 Filing+1 Next EA-1 Next EA+1

DD=0 0.0% 60.7% 69.6% 72.6% 97.8% 100.0%

DD=1 0.0% 38.3% 45.0% 45.8% 93.3% 100.0%

46

Table 1 Descriptive statistics

Variable Mean Median Std.Dev. P25 P75

DD 0.572 0.566 0.254 0.430 0.803

SUE 0.001 0.000 0.042 -0.001 0.003

CAR_EA 0.003 0.001 0.088 -0.040 0.046

CAR_DRIFT -0.007 -0.011 0.241 -0.138 0.116

#FORECASTS_EA 3.992 2.000 4.700 1.000 6.000

%FORECASTS_EA 0.396 0.375 0.324 0.067 0.667

%FORECASTS_[Filing+2, Next EA-2] 0.392 0.375 0.298 0.143 0.600

MV 2,301.3 295.9 6,918.9 75.9 1,209.2

MTB 2.975 2.086 3.154 1.285 3.485

RET 0.022 0.014 0.231 -0.102 0.135

#Analysts 5.044 3.000 5.434 0.000 7.000

INST.OWN 0.490 0.494 0.279 0.251 0.721

#EA 231.3 220.0 134.0 120.0 336.0

The table reports descriptive statistics of key variables over the sample period, 1990–2013.

#FORECASTS_EA is the number of forecasts issued within two trading days of the earnings

announcement date [0,+1]. %FORECASTS_[Filing +2, Next EA -2] is %FORECASTS for the window

between the 10-Q and the next earnings announcement. MV is the market value of equity at the end of

the fiscal quarter, in millions of dollars. #Analysts is the number of analysts following the firm. #EA is

the number of same date earnings announcements. All other variables are defined in Appendix B.

47

Table 2 Correlations among variables

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

(1) DD

(2) SUE 0.005

(3) CAR_EA 0.002 0.126

(4) CAR_DRIFT -0.021 0.051 0.049

(5) % FORECASTS[0,+1] -0.317 0.037 0.003 0.055

(6) % FORECASTS[Filing +2, Next EA -2] 0.205 -0.017 -0.003 -0.087 -0.652

(7) SIZE -0.268 -0.038 -0.022 -0.043 0.143 -0.027

(8) MTB -0.041 0.011 -0.025 0.003 0.017 -0.003 0.275

(9) RET 0.017 0.105 -0.026 0.002 -0.000 0.001 -0.023 0.107

(10) ANA.FOLLOW -0.268 -0.058 -0.010 -0.024 0.138 -0.026 0.741 0.150 -0.080

(11) INST.OWN -0.349 -0.043 -0.004 -0.031 0.271 -0.139 0.645 0.075 -0.054 0.598

(12) NRANK -0.136 0.012 -0.012 0.017 0.064 -0.069 0.085 0.059 -0.019 0.078 0.087

The table reports Pearson correlations among key variables. Correlations significant at the 10% level or lower are reported in bold. All the variables are as

defined in Appendix B.

48

Table 3 Total and immediate market reaction to earnings news

CAR_TOT or CAR_EA = α + β1 RSUEjt + β2 DDjt + β3 RSUEjt*DDjt

+ Controls + RSUEjt * Controls + εjt (15a)

Total Reaction Immediate Reaction

[0, Next EA+1] Pred. [-1,+1] [-1,+1]

Coeff. p-value sign Coeff. p-value Coeff. p-value

(1) (2) (3) (4) (5) (6)

RSUE 0.195 *** <0.001 + 0.082 *** <0.001 0.110 *** <0.001

RSUE*DD -0.014 0.215 H1a: - -0.036 *** <0.001

DD -0.001 0.845 0.015 *** <0.001

SIZE -0.082 *** <0.001 -0.011 *** <0.001 -0.007 *** <0.001

MTB 0.004 *** <0.001 0.000 * 0.096 -0.000 * 0.056

RET -0.115 *** <0.001 -0.030 *** <0.001 -0.037 *** <0.001

ANA.FOLLOW -0.007 *** 0.003 0.005 *** <0.001 -0.008 *** <0.001

INST.OWN -0.013 0.174 -0.002 0.360 -0.022 *** <0.001

NRANK 0.016 *** 0.003 -0.000 0.974 0.007 *** <0.001

RSUE*SIZE -0.015 *** <0.001 -0.009 *** <0.001

RSUE*MTB -0.002 * 0.088 0.001 *** <0.001

RSUE*RET 0.090 *** <0.001 0.012 *** 0.005

RSUE*ANA.FOLLOW 0.031 *** <0.001 0.026 *** <0.001

RSUE*INST.OWN 0.008 0.552 0.037 *** <0.001

RSUE*NRANK -0.011 0.194 -0.013 *** <0.001

Firm FE Yes Yes Yes

Year-Quarter FE Yes Yes Yes

#obs 121,807 121,807 121,807

R2 0.176 0.169 0.177

The table reports results of the regression to test the association between the delayed disclosure ratio and total and immediate market reaction to earnings news.

All variables are defined in Appendix B. *, **, *** denote significance at the 10%, 5%, and 1% levels, respectively, based on two-tailed tests.

49

Table 4 Delayed investor reaction to earnings news

Panel A: Overall delayed investor reaction

CAR_DRIFTjt = α + β1 RSUEjt + β2 DDjt + β3 RSUEjt*DDjt

+ Controls + RSUEjt * Controls + εjt (15b)

Predicted [+2, Next EA+1] [+2, Next EA+1]

sign Coeff. p-value Coeff. p-value

(1) (2) (3) (4)

RSUE + 0.054 *** <0.001 0.076 *** <0.001

RSUE*DD H1b: + 0.025 ** 0.015

DD -0.017 *** 0.008

SIZE -0.077 *** <0.001 -0.074 *** <0.001

MTB 0.002 *** <0.001 0.004 *** <0.001

RET -0.037 *** <0.001 -0.078 *** <0.001

ANA.FOLLOW 0.003 ** 0.019 0.001 0.682

INST.OWN -0.007 0.284 0.008 0.420

NRANK 0.011 *** 0.001 0.008 0.102

RSUE*SIZE -0.006 ** 0.012

RSUE*MTB -0.003 *** 0.002

RSUE*RET 0.079 *** <0.001

RSUE*ANA.FOLLOW 0.004 0.250

RSUE*INST.OWN -0.027 ** 0.034

RSUE*NRANK 0.004 0.590

Firm FE Yes Yes

Year-Quarter FE Yes Yes

#obs 121,807 121,807

R2 0.144 0.146

50

Panel B: Delayed investor reaction within subwindows

[+2, Filing Date -2] [Filing Date -1,

Filing Date +1]

[Filing Date +2,

Next EA -2]

[Next EA -1,

Next EA +1]

Coeff. p-value Coeff. p-value Coeff. p-value Coeff. p-value (1) (2) (3) (4) (5) (6) (7) (8)

RSUE 0.012 ** 0.015 0.006 ** 0.040 0.040 *** <0.001 0.012 *** <0.001

RSUE*DD -0.004 0.308 -0.003 0.238 0.023 ** 0.010 0.005 ** 0.044

DD 0.001 0.824 0.002 0.290 -0.013 ** 0.025 -0.004 ** 0.028

SIZE -0.011 *** <0.001 -0.003 *** <0.001 -0.050 *** <0.001 -0.004 *** <0.001

MTB 0.000 0.611 0.000 * 0.083 0.003 *** <0.001 0.000 *** 0.009

RET -0.032 *** <0.001 -0.002 0.255 -0.045 *** <0.001 0.002 0.277

ANA.FOLLOW -0.000 0.941 0.001 0.123 0.001 0.727 -0.001 0.344

INST.OWN 0.001 0.868 0.005 *** 0.009 -0.002 0.809 0.003 0.177

NRANK 0.003 * 0.080 0.002 0.101 0.003 0.456 0.002 0.214

RSUE*SIZE -0.001 0.182 0.000 0.447 -0.002 0.361 -0.002 *** <0.001

RSUE*MTB -0.000 0.225 -0.000 0.249 -0.002 * 0.087 -0.000 ** 0.047

RSUE*RET 0.023 *** <0.001 -0.002 0.397 0.060 *** <0.001 -0.000 0.925

RSUE*ANA.FOLLOW 0.005 *** 0.001 -0.000 0.841 -0.002 0.625 0.000 0.881

RSUE*INST.OWN 0.016 *** 0.001 -0.006 ** 0.034 -0.029 ** 0.010 -0.002 0.484

RSUE*NRANK -0.003 0.386 0.001 0.466 0.008 0.254 -0.002 0.197

Firm FE Yes Yes Yes Yes

Year-Quarter FE Yes Yes Yes Yes

#obs 121,807 121,807 121,807 121,807

R2 0.093 0.090 0.137 0.084

The table reports results of the regression to test the association between the delayed disclosure ratio and delayed investor reaction to earnings news. The

dependent variable in Panel A is the cumulative abnormal return over the period starting two days after the earnings announcement for quarter t and ending one

day after the earnings announcement for quarter t+1. In Panel B, the dependent variable is the cumulative abnormal return over the indicated subwindow. All

variables are as defined in Appendix B. *, **, *** denote significance at the 10%, 5%, and 1% levels, respectively, based on two-tailed tests.

51

Table 5 Analyst delayed response to earnings announcements

%FORECASTSjt = α + β1 DDjt + Controls + εjt

(16)

Time Windows

Pred.

[0, +1] Pred.

[+2, Filing Date -2] Pred.

[Filing Date -1,

Filing Date +1] Pred.

[Filing Date +2,

Next EA -2]

Sign Coeff. p-value Sign Coeff. p-value Sign Coeff. p-value Sign Coeff. p-value

(1) (2) (3) (4) (5) (6) (7) (8)

DD H3a: - -0.019 *** 0.006 ? -0.007 0.299 ? 0.001 0.758 H3b: + 0.025 *** 0.001

RSUE 0.018 *** <0.001 0.006 0.111 -0.002 0.251 -0.022 *** <0.001

SIZE -0.009 *** <0.001 -0.018 *** <0.001 -0.003 *** <0.001 0.030 *** <0.001

MTB -0.002 *** <0.001 0.001 *** 0.003 0.000 0.929 0.001 ** 0.045

RET 0.003 0.519 0.008 * 0.091 0.002 0.404 -0.013 ** 0.018

ANA. FOLLOW 0.018 *** <0.001 0.007 *** 0.004 -0.001 0.369 -0.024 *** <0.001

INST.OWN 0.041 *** <0.001 -0.005 0.569 0.004 0.242 -0.040 *** <0.001

NRANK -0.005 0.265 0.018 *** <0.001 -0.001 0.490 -0.012 ** 0.016

Firm FE Yes Yes Yes Yes

Year-Quarter FE Yes Yes Yes Yes

#obs 66,763 66,763 66,763 66,763

R2 0.520 0.308 0.202 0.347

The table reports results of the test of analyst delayed response to earnings news. The dependent variable is the proportion of analyst earnings forecasts made

in the indicated time window, relative to the total number of forecasts made between the current earnings announcement and next earnings announcement. All

variables are defined in Appendix B. *, **, *** denote significance at the 10%, 5%, and 1% levels, respectively, based on two-tailed tests.

52

Table 6 Analyst underreaction to earnings news and forecast accuracy

Panel A: Analyst underreaction to earnings news

FUTURE.RSUEjt+1 = α + β1 RSUEjt + β2 DDjt + β3 RSUEjt*DDjt + Controls +

RSUEjt * Controls + εjt (17a)

Pred.

[0, Filing Date -2] [Filing Date,

Next EA -2]

Sign Coeff. p-value Coeff. p-value Coeff. p-value

(1) (2) (3) (4) (5) (6)

RSUE + 0.218 *** <0.001 0.023 0.465 0.047 0.189

RSUE*DD H4a: + 0.066 *** 0.010 0.059 ** 0.033

DD -0.043 *** 0.004 -0.037 ** 0.024

SIZE -0.033 *** <0.001 -0.048 *** 0.000 -0.031 *** 0.000

MTB 0.002 *** <0.001 0.004 *** 0.001 0.001 0.601

RET 0.130 *** <0.001 0.094 *** 0.000 0.035 ** 0.035

ANA.FOLLOW -0.009 ** 0.019 -0.004 0.554 -0.010 0.247

INST.OWN -0.031 ** 0.015 -0.030 0.116 -0.049 ** 0.017

NRANK 0.013 ** 0.033 0.019 * 0.079 0.018 0.127

RSUE*SIZE 0.032 *** 0.000 0.011 * 0.055

RSUE*MTB -0.003 0.131 -0.000 0.892

RSUE*RET 0.072 *** 0.004 0.057 ** 0.047

RSUE*ANA.FOLLOW -0.008 0.531 0.026 * 0.084

RSUE*INST.OWN -0.005 0.852 -0.007 0.827

RSUE*NRANK -0.012 0.516 -0.003 0.886

Firm FE Yes Yes Yes

Year-Quarter FE Yes Yes Yes

#obs 60,808 60,808 54,472

R2 0.213 0.214 0.211

53

Panel B: Analyst forecast accuracy

ABS.FEjt+1 = α + β1 DDjt + β2 ABS.FEjt + β3 MISSjt +β4 ABS.FEjt*MISSjt +Controls+εjt (17b)

Pred. [0, Filing Date -2] [Filing Date , Next EA -2]

Sign Coeff. p-value Coeff. p-value (3) (4) (5) (6)

DD H4b: + 0.003 *** <0.001 0.003 *** <0.001

ABS.FE 0.002 *** <0.001 0.003 *** <0.001

MISS -0.005 *** <0.001 -0.005 *** <0.001

ABS.FE*MISS 0.017 *** <0.001 0.015 *** <0.001

SIZE -0.007 *** <0.001 -0.006 *** <0.001

MTB 0.000 0.986 0.000 0.274

RET -0.006 *** <0.001 -0.004 *** <0.001

ANA.FOLLOW 0.002 *** <0.001 0.002 *** <0.001

INST.OWN -0.009 *** <0.001 -0.007 *** <0.001

NRANK -0.001 0.204 -0.000 0.487

Firm FE Yes Yes

Year-Quarter FE Yes Yes

#obs 60,808 54,472

R2 0.601 0.608

Panel C: Analyst forecast dispersion

STD.ESTjt+1 = α + β1 DDjt + β2 ABS.FEjt + β3 MISSjt + β4 ABS.FEjt*MISSjt +

Controls + εjt (17c)

Pred. [0, Filing Date -2] [Filing Date , Next EA -2]

Sign Coeff. p-value Coeff. p-value (3) (4) (5) (6)

DD H4c: + 0.001 *** <0.001 0.001 *** <0.001

ABS.FE 0.001 *** <0.001 0.001 *** <0.001

MISS -0.002 *** <0.001 -0.002 *** <0.001

ABS.FE*MISS 0.005 *** <0.001 0.006 *** <0.001

SIZE -0.002 *** <0.001 -0.002 *** <0.001

MTB 0.000 ** 0.036 -0.000 0.102

RET -0.001 *** <0.001 -0.002 *** <0.001

ANA.FOLLOW 0.001 *** <0.001 0.001 *** <0.001

INST.OWN -0.003 *** <0.001 -0.003 *** <0.001

NRANK 0.000 0.233 -0.000 0.609

Firm FE Yes Yes

Year-Quarter FE Yes Yes

#obs 50,296 41,078

R2 0.668 0.631

Panel A reports results of the test of the association between the delayed disclosure ratio and analyst

underreaction to earnings news. Panel B reports results of the test of the association between the delayed

disclosure ratio and analyst forecast accuracy. Panel C reports results of the test of the association

between the delayed disclosure ratio and analyst forecast dispersion. The sample sizes in Panel C are

smaller than in Panel A/B due to the requirement of at least two analyst forecasts to compute forecast

dispersion. All variables are as defined in Appendix B. *, **, *** denote significance at the 10%, 5%,

and 1% levels, respectively, based on two-tailed tests.

54

Table 7 Additional analyses: using residual delayed disclosure

Panel A: First-stage estimation

DDjt = α + β1 RSUEjt + β2 SIZEjt + β3 MTBjt + β4 RETjt + β5 ANA.FOLLOWjt

+ β6 INST.OWNjt + β7 EA.LAGjt + β8 SMOOTHjt + β9 JMOBjt

+ β10 PRO.FORMAjt + β11 SPEC.ITEMjt + β12 EARN.VOLjt

+ β13 LOSSjt + β14 NEG.SUEjt + β15 HIGH.TECHjt

+ β16 MERGERjt + β17 YOUNGjt + β18 RET.VOLjt + β19 BIG4jt + εjt

(18)

Predicted Coeff. p-value

sign (1) (2)

RSUE ? -0.010 ** 0.016

SIZE - -0.003 *** <0.001

MTB ? 0.001 ** 0.021

RET ? 0.002 0.381

ANA.FOLLOW - -0.015 *** <0.001

INST.OWN - -0.061 *** <0.001

EA.LAG + 0.057 *** <0.001

SMOOTH + 0.003 0.312

JMOB + -0.009 *** <0.001

PRO.FORMA - -0.004 *** 0.002

SPEC.ITEM - -0.014 *** <0.001

EARN.VOL - -0.280 *** <0.001

LOSS - -0.009 *** <0.001

NEG.SUE - -0.010 *** 0.005

HIGH.TECH - -0.005 *** <0.001

MERGER - -0.002 0.284

YOUNG - -0.028 *** <0.001

RET.VOL - -0.006 *** <0.001

BIG4 - -0.019 *** <0.001

Industry FE Yes

Year FE Yes

#obs 111,034

R2 0.346

55

Panel B: Second-stage estimation

Pred.

Time Window Pred

. Time Window

Sign Coeff. p-value Sign Coeff. p-value

Immediate and Delayed Market Reaction to Earnings News

CAR = α + β1 RSUEjt + β2 RES.DDjt + β3 RSUEjt*RES.DDjt

+ Controls + RSUEjt * Controls + εjt [0, +1] [+2, Next EA+1]

RES.DD*RSUE - -0.052 *** <0.001 + 0.042 *** <0.001

[+2, Filing Date -2] [Filing Date-1, Filing Date +1]

RES.DD*RSUE - -0.008 ** 0.031 ? -0.001 0.719

[Filing Date +2, Next EA -2] [Next EA -1, Next EA +1]

RES.DD*RSUE + 0.035 *** <0.001 + 0.013 *** 0.001

Analyst Delayed Response to Earnings Announcements

%FORECASTSjt = α + β1 RES.DDjt + Controls + εjt

[0, +1] [+2, Filing Date -2]

RES.DD - -0.020 *** 0.004 ? -0.001 0.847

[Filing Date -1, Filing Date +1] [Filing Date +2, Next EA -2]

RES.DD ? 0.000 0.874 + 0.020 *** 0.008

Analyst Underreaction to Earnings News

FUTURE.RSUEjt = α + β1 RSUEjt + β2 RES.DDjt + β3 RSUEjt*RES.DDjt

+ Controls + RSUEjt * Controls + εjt [0, Filing Date -2] [Filing Date, Next EA -2]

RES.DD*RSUE + 0.059 ** 0.021 ? 0.049 * 0.076

Analyst Forecast Errors

ABS.FEjt+1= α + β1 RES.DDjt + Controls + εjt

[0, Filing Date -2] [Filing Date, Next EA -2]

RES.DD + 0.003 *** <0.001 ? 0.002 *** <0.001

Analyst Forecast Dispersion

STD.ESTjt+1 = α + β1 RES.DDjt + Controls + εjt

[0, Filing Date -2] [Filing Date, Next EA -2]

RES.DD + 0.001 *** <0.001 ? 0.001 *** <0.001

Panel A reports the results of the regression of delayed disclosure ratio, DD, on a set of explanatory

variables. Panel B reports the results of the tests using the residual delayed disclosure ratio, RES.DD,

estimated from the regression in Panel A. Panel B regressions include the base set of control variables

(SIZE, MTB, RET, ANA.FOLLOW, INST.OWN, and NRANK), their respective interactions with RSUE,

and firm and year-quarter fixed effects. All variables are as defined in Appendix B. *, **, *** denote

significance at the 10%, 5%, and 1% levels, respectively, based on two-tailed tests.

56

Table 8 Additional analyses: the effect of delayed disclosure across the income

statement, balance sheet, and statement of cash flows

Coeff. p-value Coeff. p-value Coeff. p-value

Immediate Market Reaction to Earnings News

Y = CAR_EA

RSUE*DD.IS -0.028 *** <0.001

RSUE*DD.BS -0.021 *** <0.001

RSUE*DD.SCF -0.016 *** <0.001

Delayed Market Reaction to Earnings News

Y = CAR_DRIFT

RSUE*DD.IS 0.021 0.146

RSUE*DD.BS 0.017 *** 0.008

RSUE*DD.SCF 0.007 0.420

Delayed Market Reaction in Sub-windows

Y = CAR [+2, Filing Date-2]

RSUE*DD.IS -0.004 0.490

RSUE*DD.BS -0.003 0.280

RSUE*DD.SCF -0.001 0.695

Y = CAR [Filing Date-1, Filing Date+1]

RSUE*DD.IS -0.004 ** 0.009

RSUE*DD.BS -0.001 0.079

RSUE*DD.SCF 0.002 * 0.251

Y = CAR [Filing Date+2, Next EA-2]

RSUE*DD.IS 0.027 ** 0.031

RSUE*DD.BS 0.016 *** 0.004

RSUE*DD.SCF 0.003 0.696

Y = CAR [Next EA-1, Next EA+1]

RSUE*DD.IS 0.003 0.335

RSUE*DD.BS 0.003 ** 0.046

RSUE*DD.SCF 0.003 0.176

CONTROLS Yes Yes Yes

RSUE*CONTROLS Yes Yes Yes

Firm FE Yes Yes Yes

Year-Quarter FE Yes Yes Yes

#obs 121,807 121,807 121,807

This table reports the results of estimating regressions (15a) and (15b) using the delayed disclosure ratio

of income statement items (DD.IS), balance sheet items (DD.BS), or cash flow statement items

(DD.SCF). All regressions include the base set of control variables (SIZE, MTB, RET, ANA.FOLLOW,

INST.OWN, and NRANK), their respective interactions with RSUE, and firm and year-quarter fixed

effects. All variables are as defined in Appendix B. *, **, *** denote significance at the 10%, 5%, and

1% levels, respectively, based on two-tailed tests.