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Financial Reporting Bias as a Disincentive for Discretionary Disclosure
Carol Marquardt Stern School of Business
New York University
and
Christine Wiedman Ivey School of Business
University of Western Ontario
Preliminary Draft June 28, 2004
ABSTRACT
This paper examines the role of financial reporting bias as a disincentive for firms’ discretionary disclosure decisions using a sample of 60 firms that issued contingent convertible debt during November 2000 to December 2002. Under SFAS 128, firms often exclude contingent convertibles from their diluted earnings per share calculations, thereby creating an income-increasing bias in diluted EPS. We relate the magnitude of this bias to the quality of firms’ contingent convertible debt disclosures in their EPS and long-term debt footnotes to their financial statements. Using a multivariate ordered probit model, we find that, as predicted, financial reporting bias and disclosure quality are negatively related. We also find that private information acquisition incentives, litigation costs, and earnings relevance are determinants of the disclosure decision. Preliminary results also suggest that disclosure may mitigate pricing differences due to reporting bias.
I. INTRODUCTION
The theoretical literature on disclosure offers a number of motivations for
managers to provide information to parties external to the firm, including overcoming
adverse selection, reducing private information acquisition costs, or reducing the cost of
capital (see Verrecchia 2001). The empirical disclosure literature is similarly focused on
examining managerial incentives for disclosure and finds evidence that capital markets
transactions, corporate control contests, stock compensation, or litigation costs provide
motivation for disclosure; this literature also shows that voluntary disclosure results in
improved stock liquidity, reduced cost of capital, and increased information
intermediation (see Healy and Palepu 2001).
However, far fewer studies examine firms’ motivations for withholding relevant
information from interested parties, and much of this literature relies upon proprietary
cost hypotheses. For example, Verrecchia (1983) argues that incentives to disclose
information are a decreasing function of the potential proprietary costs associated with
the disclosure, and Bens (2002) and Scott (1994) provide empirical evidence that the
existence of proprietary costs is associated with lower disclosure levels and quality.
Litigation cost arguments (see Hughes and Sankar 2000) also offer motives for
nondisclosure of information, but evidence in support of this theory is mixed (see Skinner
1997; Francis, Philbrick, and Schipper 1994).
We extend the disclosure literature by examining the role of financial reporting
bias as a disincentive for firms’ discretionary disclosure. Our analysis focuses on a
sample of 60 firms that issued contingent convertible bonds between November 2000 and
December 2002. Contingent convertibles, or “COCOs,” as they are more commonly
2
known, are convertible bonds that cannot be converted into shares of common stock until
a pre-specified stock price is reached; i.e., conversion is “contingent” upon reaching the
price threshold. This convertible bond structure first appeared in late 2000 and is
becoming increasingly popular, with more than 60% of 2003 and 80% of the year-to-date
2004 convertible debt issues structured as contingently convertible.
The popularity of COCOs stems mainly from their financial reporting effects on
issuers’ diluted earnings per share (EPS) figures (see Marquardt and Wiedman 2004).
Under Statement of Financial Accounting Standard (SFAS) No. 128, a contingency
feature added to a traditional convertible bond often allows firms to exclude the effects of
the bond when calculating diluted EPS, thereby creating an income-increasing financial
reporting bias for COCO issuers. Because managers may expect the revelation of the
amount of this bias to be negatively interpreted by market participants, we argue that it
represents a disclosure-related cost that will discourage some managers from full
disclosure of COCO-related information. We consequently predict a negative relation
between the quality of firms’ COCO-related annual report disclosure quality and the
amount of bias that is present in diluted EPS.
Similar to Botosan (1997) and Bens (2002), we develop two self-constructed
measures of COCO-related disclosure quality. The first measure employs only
information provided in the EPS footnote to firms’ financial statements. We argue that
information disclosed here is most useful to financial statement users because it
immediately alerts them to the fact that diluted EPS is biased upward. Our second
measure of disclosure quality combines information in the EPS footnote with information
in the long-term debt footnote. Rather than simply quantifying the amount of COCO-
3
related information provided, our quality measures attempt to capture both the salience
and the ultimate usefulness of the information to financial statement users.
We examine these footnote disclosures in the year of the debt issue. As perhaps is
expected with a new financial product, we find considerable variation in disclosure
quality across firms. Almost two-thirds of firms do not disclose any information about
COCOs in their EPS footnote, and while all but one firm discuss COCOs in their long-
term debt footnote, there are wide cross-sectional differences in the amount of detail and
ultimate usefulness of the information provided. This inconsistency in disclosure
practices is consistent with assertions made by the Financial Accounting Standards Board
(FASB), who issued Staff Position FAS 129-1 on April 9, 2004 to provide guidance
regarding the appropriate level of disclosure relating to contingent convertible securities.
While the inconsistency and possible inadequacy of COCO-related disclosure is
clearly a matter of concern to FASB constituents, it also provides a unique and
potentially powerful institutional setting in which to examine firms’ discretionary
disclosure decisions. Therefore, in addition to our primary hypothesis involving financial
reporting bias, we use this opportunity to examine a number of other determinants of
disclosure quality that have been suggested in previous research on voluntary disclosure.
Specifically, we predict that COCO-related disclosure quality is decreasing in earnings
relevance and private information acquisition incentives and increasing in litigation costs
and strength of corporate governance.
Using a multivariate ordered probit model, we find that, as predicted, financial
reporting bias is significantly negatively related to our EPS-based measure of COCO-
related disclosure quality. That is, the greater the amount of bias in reported diluted EPS,
4
the lower the quality of firms’ EPS footnote disclosure. We also find that, consistent with
our predictions, COCO-related disclosure quality is significantly negatively related to our
proxies for private information acquisition incentives, trading volume and firm size, and
positively related to stock price volatility, which proxies for litigation costs. We also
report a weakly negative relation between disclosure quality and earnings relevance. We
do not find that our corporate governance variables are significant determinants of
disclosure quality. We obtain similar results using a multivariate regression model with
our combined EPS-and-debt-based measure of disclosure quality as the dependent
variable.
Our finding that managers choose lower levels of disclosure quality when
financial reporting bias is high naturally raises the question of whether their disclosure
decisions have any impact on stock prices. We therefore relate annual market-adjusted
stock returns in the year of the debt issue to two diluted EPS measures – diluted EPS as
reported in firms’ financial statements and an ‘adjusted’ diluted EPS with the financial
reporting bias from the COCO removed. We dichotomize our sample by disclosure
quality, with firms who disclose any information relating to COCOs in their EPS footnote
in one category and firms who provide no information in the other.
For firms with better disclosure, adjusted R2s for the two models are extremely
close, which suggests that disclosure may mitigate any pricing differences that stem from
reporting bias. For firms with poor disclosure, we report a higher adjusted R2 using
diluted EPS as reported, which suggests that investors do not adjust diluted EPS for the
effects of the COCO issue. However, we caution that this difference in adjusted R2 is not
5
significant, possibly due to our small sample size, and thus no firm conclusion may be
drawn.
We contribute to the empirical literature on disclosure in several ways. First, we
provide descriptive evidence on firms’ footnote disclosure practices involving contingent
convertible debt. The inconsistency and inadequacy we document across firms suggests
that regulators acted appropriately in mandating greater disclosure for contingently
convertible financial instruments. One implication of these findings is that market
participants might be better served if regulators could move more quickly in providing
this type of guidance to managers when new financial products appear, as FAS 129-1 was
not released until more than three years after the first COCO appeared.
More importantly, we extend the literature by demonstrating that the revelation of
financial reporting bias may represent a disclosure-related cost that provides a
disincentive for discretionary disclosure. In doing so, we add to the literature that
examines firms’ motivations for nondisclosure of relevant information. More particularly,
we add to the literature that examines the relationship between disclosure and earnings
management. Kasznik (1999) documents an association between voluntary disclosure of
management forecasts and accruals management, but finds a positive, not negative,
relation between the two. Lobo and Zhou (2001), however, also associate disclosure with
earnings management, using AIMR analyst ratings as their proxy for disclosure quality
and discretionary accruals as their earnings management measure, and find that greater
earnings management is associated with lower disclosure quality. Our results are
generally consistent with these findings. One advantage of our study is that we can
precisely measure the degree of financial reporting bias that is associated with a
6
particular transaction and unambiguously connect it to related footnote disclosures; the
more general measures used by Lobo and Zhou make such direct linkage impossible. In
addition, our research design does not suffer from concerns over endogeneity because
poor COCO-related disclosure quality is unlikely to create an opportunity for reporting
bias in our setting – the disclosure decision more likely follows the decision to issue a
COCO rather vice versa.
The remainder of this paper is organized as follows. In Section II, we develop our
disclosure hypotheses. In Section III, we discuss variable measurement and our research
design. We present our sample and descriptive statistics in Section IV and our main
results in Section V. In Section VI, we perform additional tests relating to the pricing
consequences of disclosure quality, and Section VII concludes.
II. HYPOTHESIS DEVELOPMENT
In this section, we motivate our hypotheses regarding the quality of COCO-
related disclosure, drawing upon prior theoretical and empirical findings in the disclosure
literature. We present five empirical predictions, which we discuss individually below.
Disclosure Quality and Financial Reporting Bias
Verrecchia (1983) shows that disclosure-related costs offer an explanation for
managers’ nondisclosure of relevant information. While these costs are often assumed to
be proprietary in nature, we more broadly interpret disclosure-related costs as any
information that is potentially damaging to the firm. Full disclosure of contingent
convertible debt information may be viewed by managers as potentially harmful because
it reveals both the existence and extent of financial reporting bias present in diluted EPS.
7
Investors who take reported diluted EPS at face value and then discover that it is inflated
may react negatively to this news by adjusting prices downward. We consequently expect
that the possibility of a negative investor reaction to revelation of financial reporting bias
will discourage some managers from full disclosure of COCO-related information in the
footnotes to their annual reports. For example, managers may withhold details of the
COCO offering that would allow investors to calculate the amount of the bias, or they
may refrain from mentioning the fact that the offering is excluded from diluted EPS.
It may be argued that investors could obtain the information necessary to calculate
the magnitude of the bias from other sources. For example, if the offering was registered
with the SEC, investors could refer to the offering prospectus; in the more frequent case
of private placements, investors could obtain information from commercial sources such
as Bloomberg. However, these alternatives place costs on investors, and some investors
may be unwilling to risk time and attention to detect bias that is small or may not even
exist (see Hirshleifer and Teoh 2003).
Supposing that investors did expend resources to obtain the required information,
then in theory efficient markets should be able to “undo” any financial reporting bias
present in diluted EPS. However, as noted by Libby, Bloomfield, and Nelson (2002),
experimental evidence suggests that
“awareness of cosmetic differences (and ability to ‘do the math’) does not ensure full consideration of their implications for valuation. The same is true of management’s tendency to opportunistically employ vague reporting standards.”
Relatedly, empirical work has documented that the form of presentation of financial
information affects prices (see Davis-Friday, Folami, Liu, and Mittelstaedt 1999; Schrand
and Walther 2000).
8
This leads to our first hypothesis:
H1: The amount of financial reporting bias arising from contingent convertible debt is negatively related to the quality of the related disclosures.
Disclosure Quality and Earnings Relevance
In viewing the revelation of financial reporting bias in diluted EPS as a
disclosure-related cost that discourages some managers from full disclosure of COCO-
related information, we also consider whether this revelation might be more damaging to
some firms than others, thereby increasing the cost and providing further disincentive for
disclosure. For example, firms where investors pay particularly close attention to
earnings, and diluted EPS in particular, may suffer more negative consequences if the
bias in diluted EPS is revealed than would firms where non-earnings information is of
more interest to investors. This leads to the following hypotheses:
H2: Earnings relevance is negatively related to the quality of COCO-related disclosures.
Disclosure Quality and Information Acquisition Costs
Diamond (1985) presents a model in which firms base their disclosure policies on
information cost savings. In the absence of disclosure, individuals invest in information
acquisition to gain a trading advantage. Total information costs equal the sum of the
individual information production costs. Firm disclosures result in information cost
savings to the economy as a whole because the information is collected only once. This
suggests that firms’ disclosures should increase in the level of private information
production that would occur in their absence, as this maximizes the cost savings.
9
Empirical findings are consistent with this argument. For example, previous
studies (e.g., Lang and Lundholm 1993; Frankel, Johnson, and Skinner 1999) document a
positive relation between disclosure and firm size, which serves as a proxy for private
information acquisition incentives (see King, Pownall, and Waymire 1990). Similarly,
Scott (1994) uses trading volume to measure information costs and documents a positive
relation between trading volume and voluntary disclosure of pension information.
In the case of contingent convertible debt, however, we argue that managers will
choose to increase, rather than decrease, investors’ information acquisition costs because
doing so increases the probability that some investors will not expend the costs to acquire
the information and therefore not discover the extent of the financial reporting bias
present in diluted EPS. This leads to the following hypothesis:
H3: Private information acquisition incentives are negatively related to the quality of COCO-related disclosures.
Disclosure Quality and Corporate Governance
Recent work in the empirical disclosure literature investigates whether corporate
governance affects disclosure policies and reports mixed evidence. For example, Eng and
Mak (2003) find that ownership structure and board composition affect voluntary
disclosure in Singapore firms, but Byrd, Johnson, and Porter (1998) find that voluntary
disclosure of proxy statement compensation information is unrelated to the strength of
corporate governance. There is stronger evidence, however, that corporate governance is
linked to earnings management. Klein (2002) reports a negative relation between board
independence and abnormal accruals, and Dechow, Sloan, and Sweeney (1996) find that
weak governance is associated with a higher probability of accounting fraud.
10
Because it is possible that corporate governance may be a determinant of
disclosure quality and may also constitute a correlated omitted variable if it is related to
the degree of financial reporting bias, we include it as an additional independent variable
in our analysis. In general, we expect proxies for strong corporate governance to be
positively related to the quality of COCO-related disclosures. Formally stated:
H4: The strength of corporate governance is positively related to the quality of COCO-related disclosures. Disclosure Quality and Litigation Costs
Prior literature has linked disclosure policies to litigation costs. Skinner (1994)
offers a litigation cost hypothesis in explaining why firms voluntarily disclose bad news,
and while Francis, Philbrick, and Schipper (1994) find no evidence that preemptive
disclosures deter litigation completely, such disclosures may reduce the costs of
litigation. We consequently expect a positive relation between proxies for litigation costs
and the quality of COCO-related disclosure. Formally stated:
H5: Litigation costs are positively related to the quality of COCO-related disclosures.
III. VARIABLE MEASUREMENT AND RESEARCH DESIGN
In this section, we discuss variable measurement of financial reporting bias,
disclosure quality, earnings relevance, private information acquisition incentives,
corporate governance strength, and litigation costs. We also present our empirical model.
Financial Reporting Bias
In this section, we explain how COCOs create an income-increasing financial
reporting bias for issuers. The essential difference between a COCO and a traditional
11
convertible bond is the addition of the contingent conversion feature, which is a unique
innovation that affects both the bondholder and the issuer. For bondholders, it constrains
their ability to voluntarily convert the bonds into stock. Instead of being able to convert
the bonds to stock at any time, as with traditional convertible bonds, COCOs may be
converted only if certain pre-specified conditions have been met, typically a stock price
increase. For example, Tyco International, who issued the first COCO in November of
2000, required the following events to occur before their notes could be surrendered for
conversion into common shares:
“if the closing sale price of [Tyco’s] common shares for at least 20 trading days in the 30 trading day period ending on the trading day prior to the date of surrender is more than 110% of the accreted conversion price per common share on that preceding trading day; or if [Tyco] called the LYONs for redemption.”
Tyco issued the COCOs with a conversion price of $72.00. Tyco’s common stock
must therefore trade above $79.20 (110% of $72.00) before holders may convert.
However, since voluntary conversions of convertible bonds are infrequent events, this
constraint on holders’ ability to convert is likely to have little, if any, effect on Tyco’s
real stock dilution.1
Contingent conversion does, however, have an important effect on the issuer’s
financial reporting. Under SFAS 128, the common shares that would result from
conversion are “contingently issuable” and not included in diluted EPS calculations until
“necessary conditions for issuance are satisfied” (see paragraph 30). In the Tyco case, the
stock price at the end of fiscal 2001 had not yet reached the 110% threshold required for
1 See Marquardt and Wiedman (2004) for a more complete discussion of voluntary conversion of contingent convertible bonds.
12
conversion, and as a result the dilutive effects of the entire offering were excluded from
the denominator of diluted EPS.
To illustrate, Tyco reported diluted EPS of $2.55 for the fiscal year ending
September 30, 2001. Had the convertible bonds been traditionally structured, Tyco would
have applied the ‘if-converted’ method to the bonds and added $34.8 million of after-tax
interest to the numerator of diluted EPS and 42.5 million dilutive potential common
shares to the denominator of diluted EPS resulting in diluted EPS of $2.51 for fiscal
2001. Contingent conversion creates an upward bias of four cents per share, or almost
2%, in Tyco’s diluted EPS.2
We view this upward effect on reported diluted EPS as bias because, as
Marquardt and Wiedman (2004) empirically demonstrate, the decision to issue COCOs is
mainly driven by the “loophole” in SFAS 128 regarding contingently issuable shares,
which allows COCO issuers to report inflated diluted EPS figures. In addition, equity
analysts advise investors to adjust diluted EPS for the potential dilution arising from
contingently convertible bonds. For example, in a recent Bear Stearns equity report (see
McConnell, Pegg, Senyet, and Mott 2004), analysts state that
“we believe that when comparing investment opportunities, investors should include the potential common stock issuable in connection with convertible securities in their EPS estimates using the if-converted method. This is particularly true if the investor’s target price equals or exceeds the convertible bond’s conversion ‘trigger.’ We continue to believe that the if-converted method provides the best simplistic measure of the cost of having issued convertible debt.”
In other words, analysts recommend that investors “undo” the bias present in diluted EPS
when firms issue COCOs. We therefore use the difference between annual diluted EPS
reported for the fiscal year of issue and the diluted EPS figure that would result through 2 The mean bias for our sample firms is nine cents per share, or 3.3% of diluted EPS.
13
application of the if-converted method, divided by year-end share price, as our measure
of financial reporting bias (BIAS).
COCO Disclosure Quality
In this section, we discuss the disclosure of COCO-related information and
develop our two measures of COCO-related disclosure quality. In general, firms discuss
COCOs in two separate areas of their financial statements: in the EPS footnote and in the
long-term debt footnote. For example, in Tyco’s annual report for the fiscal year ending
September 30, 2001, they provide the following information in their EPS footnote:
“Diluted earnings per common share excludes 48.0 million and 26.4 million shares related to Tyco Industrial’s zero coupon convertible debentures due 2020 and 2021, respectively, because conversion conditions were not met.”
This disclosure alerts financial statement users to the fact that diluted EPS is overstated
and, in explicitly stating the number of excluded shares, provides enough information to
users to calculate an adjusted diluted EPS figure. However, note that the resulting diluted
EPS figure would be a conservative estimate of the figure that would actually result using
the if-converted method, because the after-tax charges that need to be added to the
numerator are not provided. In addition, the 48.0 million shares from the debentures due
2020 (i.e., the original COCO issue) are not weighted by the proportion of the fiscal year
that they were potentially outstanding.3 These deficiencies notwithstanding, this amount
of EPS footnote detail represents a relatively high level of COCO-related disclosure
quality, as no other COCO issuer in our sample provided more information than this in
their EPS footnote.
3 The debentures due 2021 relate to a second COCO offering that Tyco undertook in February 2001. As with the original offering, the 26.4 million shares are not weighted by the two-thirds of the fiscal year that they were potentially outstanding.
14
Tyco also discusses the COCOs in their debt footnote. They report:
“In November 2000, Tyco Industrial completed a private placement offering of $4,657,500,000 principal amount at maturity of zero coupon convertible debentures due 2020 for aggregate net proceeds of approximately $3,374,000,000. In December 2000, Tyco filed a registration statement registering the securities for resale by the holders. Each $1,000 principal amount at maturity debenture was issued at 74.165% of principal amount at maturity, accretes at a rate of 1.5% per annum and is convertible into 10.3014 Tyco common shares if certain conditions are met. The Company may be required to repurchase the securities at the accreted value at the option of the holders on November 17, 2003, 2005, 2007 or 2014. The net proceeds were used to finance and acquisitions and to repay borrowings under the commercial paper program of Tyco International Group.”
From this disclosure, a knowledgable user would be able to calculate the
numerator effects relating to the COCO using the date, proceeds, and yield (and obtaining
the effective tax rate from the income statement). The denominator effects could also be
calculated using the date, principal amount, and conversion ratio (or, alternatively, the
date, proceeds, bond price, and conversion ratio). However, this disclosure does not, by
itself, provide enough information to determine whether the COCO has or has not been
included in diluted EPS calculations, as the conversion conditions have not been
disclosed. Furthermore, a user who was unaware that contingently issuable shares are
excluded from diluted EPS if conversion conditions are not satisfied would not be alerted
to this fact by reading this footnote information. We view this amount of debt footnote
detail as constituting an average level of disclosure quality, as some sample firms provide
more and some provide less COCO-related information than does Tyco.4
We use information disclosed in firms’ EPS and debt footnotes, as in the above
examples, to construct our two empirical measures of COCO-related disclosure quality.
4 In addition, Tyco discusses their COCO offerings in the Management Discussion and Analysis section of their fiscal 2001 annual report. We plan to incorporate MD&A disclosures in a future draft of the paper.
15
Rather than simply quantifying the amount of COCO-related information provided, we
focus on assessing both the salience and the ultimate usefulness of the information to
investors. This focus is consistent with the disclosure requirements newly mandated in
FAS 129-1, which emphasize a user-orientation. We present the disclosure requirements
under FAS 129-1 in Exhibit 1.
Our first measure, EPSDQ, uses information disclosed in the EPS footnote alone.
We argue that information disclosed here is most salient and useful to financial statement
users because it immediately alerts them to the fact that diluted EPS is biased upward.
We define three levels of quality: in the top level, firms explicitly state that diluted EPS
excludes a particular number of shares related to COCOs; in the middle level, the firm
states that diluted EPS excludes shares related to COCOs but does not provide the
amount; and in the bottom level, the firm provides no disclosure related to COCOs. We
assign EPSDQ the values of “3,” “2,” or “1,” where “3” represents the highest disclosure
quality. For example, in the Tyco case, EPSDQ would equal 3, as Tyco disclosed the
number of shares excluded from diluted EPS in its EPS footnote.
Our second measure of disclosure quality, TOTDQ, combines information in the
EPS footnote with information in the long-term debt footnote. Using the details provided
in the debt footnote, we determine whether investors would be able to calculate the effect
of the COCO on the numerator and denominator of diluted EPS, as well as whether the
COCO has or has not been included in reported diluted EPS. We then develop a ten-point
scale of debt disclosure quality, which we term DEBTDQ. This variable ranges from a
high of “9” to a low of “0”.
16
As shown in Exhibit 2, we assign DEBTDQ values based on the ease investors
would have in applying the if-converted method to diluted EPS. We assign the top
ranking of “9” to a firm that discloses the number of shares issuable upon conversion of
the COCO, along with a statement regarding their exclusion from diluted EPS. We assign
the next highest ranking of “8” to a footnote that discloses both the number of shares
issuable and sufficient information to determine whether they are included in diluted
EPS. The next two rankings are used when there is sufficient information to determine
numerator and denominator effects and whether the issuable shares are included in
diluted EPS. The next five rankings (“1” through “5”) indicate varying levels of missing
information, and the lowest ranking of “0” is used when the firm does not provide any
debt footnote disclosure of COCO-related information.
We again refer to the Tyco disclosure as an example. Tyco disclosed enough
information in its debt footnote to determine both numerator and denominator effects in
diluted EPS, but not whether the issuable shares are included, yielding a DEBTDQ of
“5”. We then combine this ten-point scale with EPSDQ to yield a two-digit measure of
COCO-related disclosure quality. Tyco has a EPSDQ value of “3” and a DEBTDQ of
“5,” thus its TOTDQ2 value would be “35” (out of a maximum of “39”). We argue that
this two-digit coding of disclosure quality best captures both the salience and the
usefulness of COCO-related information in firms’ annual reports.
Earnings Relevance
We proxy for earnings relevance in two ways. For our first measure, we follow
Matsumoto (2002) and estimate R2s from industry-specific regressions of annual market-
adjusted stock returns on changes in annual diluted EPS. Our return interval begins three
17
months after the fiscal year-end and ends twelve months later. We use all available
Compustat and CRSP data in the year prior to the bond issue and define industries using
four-digit SIC codes. Because the distribution of R2 is highly skewed, we replace each
coefficient with its decile industry rank. This variable (ERCRANK) varies between one
and ten, with higher values reflecting greater earnings relevance.
Our second measure is earnings performance, defined as return on assets (ROA) in
the year prior to the bond issue. Hayn (1995) shows that profits are more value-relevant
than losses in determining stock returns, which suggests that investors may place greater
weight on good versus bad earnings performance when setting prices.
Private Information Acquisition Incentives
Consistent with previous research (see Lang and Lundholm 1993 and Scott 1994),
we use firm size (SIZE), defined as the log of total assets, and trading volume (TV),
defined as total annual trading volume divided by total shares outstanding at fiscal year-
end, as our proxies for private information acquisition incentives. Both SIZE and TV are
measured in the year prior to the bond offering.
Corporate Governance
We use three proxies for corporate governance: CEO stockholdings (CEOHOLD),
whether the CEO is also the chairman of the board (CEO=COB), and the percentage of
independent board members (%BODIND). Nagar, Nanda, and Wysocki (2004) document
a positive association between discretionary disclosure and CEO holdings, and Dechow,
Sloan, and Sweeney (1996) employ both CEO=COB and %BODIND as governance
variables. CEOHOLD is defined as the total shareholdings owned by the CEO divided by
total shares outstanding, CEO=COB is an indicator variable that equals one if the CEO is
18
also the chairman of the board and zero otherwise, and %BODIND is the percentage of
independent board members. Non-independent board members include: current
employees of the company, past employees (within three years), relatives of an executive
officer, employees of subsidiaries of the company, individuals with significant
transactions or business relations with the company, and directors on interlocking boards.
All three variables are collected from the firm’s proxy statement in the year of the bond
offering. As CEO=COB suggests weak governance, we predict a negative rather than
positive association between this variable and disclosure quality.
Litigation Costs
Because large stock price declines are associated with the incidence of
shareholder litigation, we follow Lang and Lundholm (1993) and use stock price
volatility (VOL) as our proxy for litigation costs. VOL is defined as the annualized
standard deviation of daily stock returns for the year prior to the bond issue.
Empirical Model
We test our disclosure hypotheses using a multivariate ordered probit model in
which the response variable equals EPSDQ, which takes on one of three values, and our
explanatory variables are as defined above. The final model is:
)1()Pr( 765432110 εβββββββαα +++++++++= VOLGOVTVSIZEROAERCRANKBIASEPSDQ
We expect negative estimated coefficients for BIAS, ERCRANK, ROA, SIZE, and
TV and positive estimated coefficients for GOV and VOL. We also test our hypotheses
using multivariate OLS regression, where TOTDQ is the continuous dependent variable
and the independent variables remain unchanged, as follows:
19
)2(76543210 εββββββββ ++++++++= VOLGOVTVSIZEROAERCRANKBIASTOTDQ
IV. SAMPLE AND DESCRIPTIVE STATISTICS
We obtained our convertible bond data from Kynex, Inc., a risk-management firm
that maintains an extensive, detailed database of active convertible securities in the U.S.
market. Our sample period begins with the issue of the first COCO by Tyco in November
of 2000 and ends in December 2002.5 There are 77 COCO issues during this time period.
However, some firms issue COCOs more than once during our sample period; we retain
only the first issue, bringing the number of observations down to 67. We remove an
additional 7 observations due to missing CRSP or proxy statement data. Our final sample
consists of 60 COCOs.
Table 1, Panel A presents descriptive statistics on the firm characteristics of our
sample of 60 COCO issuers. As indicated in Panel A, the typical COCO issuer has mean
(median) market capitalization of $16.4 ($5.4) billion, mean (median) total assets of
$25.7 ($4.6) billion, and total sales of $7.7 ($3.35) billion. As the average Compustat
firm during 2000-2002 has mean market capitalization, total assets, and total sales of
$2.3, $5.1, and $1.9 billion, respectively, these statistics indicate that our sample firms
are, on average, much larger than the typical Compustat firm. Our sample firms are, on
average, in strong financial condition, with mean (median) net income of $706.0 ($196.6)
and mean (median) operating cash flows of $991.0 ($295.1) million. This is not
surprising, given that firms must be profitable in order to derive any significant financial
reporting benefit from issuing COCOs. The typical COCO issuer also has low dividend
yields, with a mean (median) of 0.9% (0.3%).
5 We intend to example our sample period through December 2003 in a future draft of the paper.
20
Sample characteristics of the offerings themselves are also presented in Panel A.
The typical COCO offering is relatively large, with mean (median) proceeds as a
percentage of total assets of 11.4% (6.2%). The number of potentially dilutive shares
issuable upon conversion is also substantial, with mean (median) shares issuable divided
by total shares outstanding of 7.3% (6.0%).
In Panel B of Table 1, we present descriptive statistics on our measures of
disclosure quality. Thirteen out of 60 firms disclosed the number of shares excluded fro
diluted EPS in their EPS footnote, as indicated by an EPSDQ score of “3”. Eight firms
disclosed the fact that COCO-related shares are excluded from diluted EPS
(EPSDQ=”2”), and the majority of firms, 39 out of 60, disclosed no COCO-related
information in their EPS footnote.
We also document wide variation in debt footnote disclosures. While the most
common disclosure practice is to provide sufficient information to apply the if-converted
method to diluted EPS (27 out of 60 firms have a DEBTDQ score of “7”), forty percent of
firms do not provide enough information for users to make this adjustment (24 out of 60
firms have DEBTDQ scores of “5” or below). This inconsistency and inadequacy of
COCO-related disclosure is consistent with statements made by the FASB, as well as
with conclusions drawn by equity analysts. For example, in his review of financial
statement footnotes of 40 COCO issuers, Gainey (2004) characterizes overall disclosure
as “generally poor if the goal is to alert and inform analysts and investors of the existence
of these instruments and their impact on the financials.”
21
We also observe from Panel B that firms who tend to disclose more COCO-
related information in their EPS footnote tend to disclose more in their debt footnote as
well. In fact, the correlation between EPSDQ and DEBTDQ is 0.32 (p=0.0119).
Panel C presents descriptive statistics on our independent variables. Mean
(median) BIAS, measured as the difference between reported and if-converted diluted
EPS divided by share price, is 0.0026 (0.0012). Mean (median) ERCRANK is 5.50 (5.50),
which indicates that the earnings informativeness of COCO issuers is about average
relative to other Compustat firms. Mean (median) ROA is fairly high at 0.063 (0.045),
which is consistent with more profitable firms having more to gain from issuing a COCO.
Mean (median) SIZE, the log of total assets, is 8.67 (8.43), which again indicates that
COCO issuers are large firms. Mean (median) TV, defined as total annual trading volume
divided by shares outstanding, is 22.54 (17.51), which is higher than the average CRSP
firm: mean (median) TV for CRSP firms in 2001 is 13.20 (6.45). Mean (median)
CEOHOLD is 0.024 (0.008). Seventy percent of COCO issuers have CEOs that are also
the chairman of the board – mean CEO=COB equals 0.70 – and mean (median)
%BODIND is 68.3% (71.4%). Lastly, mean (median) VOL is 0.469 (0.450), which is
somewhat higher than average for large firms.
V. RESULTS
We present in Table 2 Pearson correlation coefficients for our dependent and
independent variables. Consistent with H1, our first measure of disclosure quality,
EPSDQ, is significantly negatively correlated with BIAS (ρ = -0.2509, p=0.0531).
However, EPSDQ is not significantly correlated with our proxies for earnings relevance:
22
the coefficient for ERCRANK, while in the predicted direction, is not significantly
different from zero, and the coefficient for ROA is significantly positive rather than
negative (ρ = 0.2646, p=0.0410). Our proxies for private information acquisition
incentives, SIZE and TV, are not significantly correlated with EPSDQ, although their
signs are in the expected direction (ρ=-0.1481 and -0.1477, respectively). Two of the
governance variables, CEOHOLD and CEO=COB are marginally significantly positively
correlated with EPSDQ (ρ=0.2391 and 0.2295, respectively); however, we expected a
negative coefficient for CEO=COB. Lastly, EPSDQ is marginally significantly positively
correlated with VOL (ρ = 0.2290, p=0.0784), consistent with H5.
In general, correlations between our second measure of disclosure quality,
TOTDQ, and the independent variables are similar in sign and magnitude to the
correlations with EPSDQ, which is unsurprising given the extremely high correlation
coefficient between them (ρ=0.9814).
Among the independent variables, the most significant correlation is between
VOL and TV, with ρ=0.6413 (p=0.0001). Other significant coefficients are shown
between BIAS and SIZE (ρ = -0.3036, p=0.0184), which indicates greater financial
reporting bias for smaller firms, and between BIAS and CEO=COB (ρ = -0.3061,
p=0.0174), which indicates less financial reporting bias for firms whose CEOs are also
the chairman of the board. ROA is significantly negatively correlated with SIZE (ρ=-
0.3348, p=0.0089), indicating that for our sample firms, smaller firms tend to have better
earnings performance. ROA is also positively correlated with both CEO=COB
(ρ=0.2222, p=0.0879) and VOL (ρ=0.2668, p=0.0393). Lastly, we report a significantly
negative coefficient between %BODIND and CEOHOLD (ρ=-0.3006, p=0.0196). As
23
both of these variables are meant to capture corporate governance strength, this
correlation highlights the difficulty in identifying appropriate proxies for this construct.
Table 3 presents the results from our multivariate ordered probit model (equation
1). We present three models, each including a separate corporate governance variable.
The response variable, EPSDQ, takes on three values, with higher values indicating
greater disclosure quality. Consistent with H1, the estimated coefficient on BIAS is
significantly negative in all three models, suggesting that financial reporting bias
discourages managers from full disclosure of COCO-related information. Our proxies for
earnings relevance, ERCRANK and ROA, have estimated coefficients in the predicted
direction but do not reach conventional levels of significance; H2 is thus not supported.
However, both SIZE and TV, our private information acquisition incentive proxies, have
significantly negative estimated coefficients, consistent with H3. That is, the greater the
incentives for investors to collect private information, the less likely managers are to
disclose relevant information about their COCOs. This contrasts with the typical findings
in the disclosure literature, which underscores the need to carefully consider the
institutional setting when examining disclosure incentives. None of our corporate
governance proxies, CEOHOLD, CEO=COB, or %BODIND, have significant estimated
coefficients; it does not appear that corporate governance strength plays an important role
in firms’ decisions to disclose COCO-related information. Lastly, VOL, our litigation cost
proxy, is significantly positive, consistent with H5.
In Table 4, we present results using our second measure of disclosure quality,
TOTDQ, which combines information from both the EPS and debt footnotes. Because
TOTDQ is behaves more like a continuous rather than a categorical variable, we use OLS
24
regression in this analysis (equation 2). In general, the results are very similar to those
reported in Table 3. The only difference is that ERCRANK now achieves marginal
significance in Model 3, lending weak support to H2. Also, most of the p-values are
slightly improved, which suggests that TOTDQ may be the more discriminating measure
of the overall quality of COCO-related disclosure.6
VI. ADDITIONAL TESTS
The negative association we document between financial reporting bias and
disclosure quality of COCO-related information raises the question of whether managers’
discretionary disclosure decisions have any impact on prices. We therefore examine the
relative information content of reported diluted EPS versus diluted EPS using the if-
converted method by regressing cumulative annual market-adjusted stock returns on each
earnings measure, as follows:
CAR = β0 + β1DEPS + ε (3)
CAR is measured over a 12-month period beginning three months after the fiscal year
end for the year of the bond issue, and DEPS equals either diluted EPS as reported or
from using the if-converted method, divided by price at fiscal year-end. To assess relative
information content, we compare adjusted R2’s for the two alternative earnings measures
using Vuong’s (1989) Z-statistics.
The results are presented in Table 5. Vuong’s Z-statistic compares the diluted
EPS as reported model with the if-converted model as competing non-nested models; a
positive Z-statistic indicates that the first model performs better than the second. The
6 Results for Tables 3 and 4 do not change when the continuous variables are winsorized at the 5 and 95 percentiles.
25
adjusted R2 using all 60 firms is 9.69% based on diluted EPS as reported and 9.04%
based on the if-converted method. Vuong’s Z-statistic is 1.0709, with a two-tailed p-
value of 0.2846, which indicates that, on average, investors do not “undo” the bias in
reported diluted EPS related to contingent convertible debt.
We repeat this analysis for high- and low-disclosure firms. We define high
disclosers as firms that disclosed any COCO-related information in their EPS footnote
(i.e., firms whose EPSDQ value was either “1” or “2”) and low disclosers as all other
firms. For high-disclosers, adjusted R2’s are remarkably similar for the two models:
7.67% for the as reported model and 7.45% for the if-converted method. For low-
disclosers, adjusted R2’s are somewhat lower for the if-converted model at 10.35% versus
11.30% for the as reported model. Taken together, these results suggest that greater
disclosure may mitigate pricing differences due to financial reporting bias. However, as
none of the Z-statistics are significant, perhaps due to our small sample sizes, no firm
conclusions may be drawn at this time.
VII. CONCLUSION
This paper examines the role of financial reporting bias as a disincentive for
firms’ discretionary disclosure decisions. We exploit a unique institutional setting in
exploring disclosure decisions regarding firms’ use of contingent convertible debt. Using
a sample of 60 firms that issued contingent convertible debt during November 2000 to
December 2002, we document wide cross-sectional differences disclosure practices,
which is consistent with assertions made by the FASB and others. Our two self-
constructed measures of disclosure quality are significantly negatively correlated with the
26
magnitude of the reporting bias that occurs when firms issue contingent convertibles,
thereby extending the empirical disclosure literature.
One advantage of examining contingent convertibles is that we are able to
precisely measure the degree of financial reporting bias that arises from the use of these
financial securities and directly associate it with their related disclosures; such linkages in
previous research were far less straightforward. In addition, the wide variation in
disclosure practices relating to contingent convertibles prior to 2004 create a powerful
setting in which to examine disclosure questions more generally. However, our focus on
contingent convertibles may also limit the generalizability of our results.
27
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30
EXHIBIT 1 Disclosure Requirements for Contingently Convertible Financial Instruments
Under FAS 129-1
1. Significant terms of the conversion features of the contingently convertible security should be disclosed. Terms include:
a. Events or changes in circumstances that would cause the contingency to be met and any significant features necessary to understand the conversion right and the timing of those rights.
b. Conversion price and number of shares into which the security is potentially convertible.
c. Events or changes in circumstances that could adjust or change the contingency, conversion price, or number of shares, including significant terms of those changes.
d. Manner of settlement upon conversion and any alternative settlement methods.
2. Disclosures should indicate whether the shares that would be issued if
the contingently convertible securities were converted are included in the calculation of diluted EPS and the reasons why or why not.
3. Disclosures of information about derivative transactions entered into in
connection with the issuance of the contingently convertible securities may be useful in terms of fully explaining the potential impact of the contingently convertible securities. Such information should include the terms of those transactions and how those relate to the contingently convertible securities.
31
EXHIBIT 2 Summary of the Disclosure Variables
Earnings Per Share Footnote Disclosure:
EPSDQ = [1,2,3] Where
“3” indicates disclosure of number of shares excluded from diluted EPS
“2” indicates disclosure of exclusion of shares from diluted EPS, but not the number of shares
“1” indicates no disclosure
(Long-term) Debt Footnote Disclosure:
DEBTDQ = [0,9] Where
“9” indicates disclosure of number of shares and whether excluded from diluted EPS
“8” indicates disclosure of number of shares and sufficient information to determine whether included in diluted EPS
“7” indicates disclosure of sufficient information to calculate number of shares and after-tax interest charges and whether included in diluted EPS
“6” indicates disclosure of sufficient information to calculate number of shares and whether included in diluted EPS
“5” disclosed sufficient information to calculate number of shares and after-tax interest charges, but not whether included in diluted EPS
“4” indicates disclosure of sufficient information to calculate number of shares, but not whether included in diluted EPS
“3” indicates disclosure of sufficient information to calculate after-tax interest charges, but not number of shares or whether included in diluted EPS
“2” indicates disclosure of insufficient information to calculate number of shares or after-tax interest charges, but sufficient information to determine whether included in diluted EPS
“1” disclosed insufficient information to calculate number of shares, after-tax interest charges, or whether included in diluted EPS
“0” indicates no disclosure
32
TABLE 1 Descriptive Statistics
Panel A: Firm and bond issue characteristics
Variable Mean Std. Dev 1st
Quartile Median 3rd
quartile Firm characteristics: Market value of equity ($MM) 16,368.7 36,499.4 1,895.2 5,363.0 11,174.9 Total assets ($MM) 25,706.3 73,094.0 2,030.8 4,568.7 13,653.2 Sales ($MM) 7,691.5 12,107.5 1,076.8 3,537.4 7,812.5 Net Income ($MM) 706.0 1,675.7 79.6 196.6 550.1 Cash flow from Operations ($MM) 991.0 2,452.6 154.1 295.1 829.8 Dividend yield (%) 0.9% 1.4% 0.0% 0.3% 1.5% Convertible bond issue characteristics: Proceeds ($MM) 542.7 639.2 200.0 348.8 587.8 Proceeds (% of total assets) 11.4% 12.9% 3.1% 6.2% 15.3% Shares issuable on conversion ($MM) 10.4 10.4 4.6 7.0 10.5 Shares issuable on conversion (% of outstanding) 7.3% 5.6% 3.4% 6.0% 8.6% Panel B: Disclosure Variables (N=60)
EPSDQ DEBTDQ 3 2 1 Total
9 2 0 1 3 8 2 0 2 4 7 5 8 14 27 6 0 0 2 2 5 3 0 10 13 4 1 0 5 6 3 0 0 1 1 2 0 0 3 3 1 0 0 0 0 0 0 0 1 1
Total 13 8 39 60
Panel C: Independent Variables
Variable Mean Std. Dev 1st
Quartile Median 3rd
quartile BIAS 0.0026 0.0041 0.0000 0.0012 0.0024 ERCRANK 5.50 2.84 3.00 5.50 8.00 ROA 0.063 0.071 0.015 0.045 0.086 SIZE 8.67 1.47 7.62 8.43 9.52 TV 22.54 19.49 11.07 17.51 26.59 CEOHOLD 0.024 0.057 0.002 0.008 0.019 CEO=COB 0.70 0.46 0.00 1.00 1.00 %BODIND 68.3% 15.7% 58.4% 71.4% 80.0% VOL 0.469 0.116 0.385 0.450 0.532
33
The sample includes 60 contingent convertible bond issues from November 2000 through December 2002. Convertible bond data was provided by Kynex, Inc. The firm characteristics are from Compustat and are presented for the year prior to the bond issue. EPSDQ is a disclosure quality score that measures the COCO information disclosed in the EPS footnote alone. This measure takes on a value of “1”, “2”, or “3”, where “3” represents the highest disclosure quality. DEBTDQ is disclosure quality score ranging from “0” to “9” that measures the COCO information in the long-term debt footnote. Higher values represent high disclosure quality. BIAS is defined as annual diluted EPS as reported for the year of issuance minus diluted EPS using the if-converted method. ERCRANK is the decile rank of R2s from industry-specific regressions of annual market-adjusted stock returns on changes in annual diluted EPS. ROA is the return on assets for the firm. SIZE is the logarithm of total assets. TV is the total annual trading volume divided by total shares outstanding at fiscal year-end. CEOHOLD is defined as total shareholdings owned by the CEO divided by total shares outstanding. CEO=COB is an indicator variable that equals one if the CEO is also the chairman of the board, or zero otherwise. %BODIND is the percentage of independent (non-employee and unaffiliated) board members. VOL is defined as the annualized standard deviation of daily stock returns for the year prior to the bond issue. ERCRANK, ROA, SIZE, TV and VOL are all measured in the year prior to the bond issue.
34
TABLE 2 Pearson Correlation Coefficients
EPSDQ TOTDQ BIAS ERCRANK ROA SIZE TV CEOHOLD CEO=COB %BODIND TOTDQ 0.9814 (0.0001) BIAS -0.2509 -0.2434 (0.0531) (0.0609) ERCRANK -0.0791 -0.0909 -0.0498 (0.5481) (0.4899) (0.7054) ROA 0.2646 0.2465 -0.0773 -0.0400
(0.0410) (0.0576) (0.5573) (0.7614)
SIZE -0.1481 -0.1921 -0.3036 -0.1653 -0.3348
(0.2589) (0.1415) (0.0184) (0.2070) (0.0089)
TV -0.1477 -0.1640 0.1811 -0.0809 -0.0111 -0.2098
(0.2602) (0.2105) (0.1661) (0.5388) (0.9329) (0.1077)
CEOHOLD 0.2391 0.2700 -0.1516 -0.1351 0.0388 0.0051 -0.1623
(0.0658) (0.0370) (0.2474) (0.3034) (0.7685) (0.9689) (0.2155)
CEO=COB 0.2295 0.2038 -0.3061 -0.1551 0.2222 0.1094 -0.1138 0.2004
(0.0777) (0.1184) (0.0174) (0.2366) (0.0879) (0.4052) (0.3865) (0.1248)
%BODIND 0.0418 0.0299 -0.1137 0.0360 0.1276 -0.0036 0.0871 -0.3006 0.0884
(0.7514) (0.8209) (0.3869) (0.7850) (0.3313) (0.9785) (0.5080) (0.0196) (0.5018) VOL 0.2290 0.2055 0.0704 -0.0396 0.2668 -0.1335 0.6413 0.1191 0.0645 -0.0687 (0.0784) (0.1152) (0.5930) (0.7641) (0.0393) (0.3092) (0.0001) (0.3649) (0.6245) (0.6022)
35
EPSDQ is a disclosure quality score that measures the COCO information disclosed in the EPS footnote alone. This measure takes on a value of “1”, “2”, or “3”, where “3” represents the highest disclosure quality. TOTDQ is a disclosure score ranging from 10 through 39 that measures the COCO information in both the EPS footnote and the long-term debt footnote. Higher values represent high disclosure quality. BIAS is defined as annual diluted EPS as reported for the year of issuance minus diluted EPS using the if-converted method. ERCRANK is the decile rank of R2s from industry-specific regressions of annual market-adjusted stock returns on changes in annual diluted EPS. ROA is the return on assets for the firm. SIZE is the logarithm of total assets. TV is the total annual trading volume divided by total shares outstanding at fiscal year-end. CEOHOLD is defined as total shareholdings owned by the CEO divided by total shares outstanding. CEO=COB is an indicator variable that equals one if the CEO is also the chairman of the board, or zero otherwise. %BODIND is the percentage of independent (non-employee and unaffiliated) board members. VOL is defined as the annualized standard deviation of daily stock returns for the year prior to the bond issue. ERCRANK, ROA, SIZE, TV and VOL are all measured in the year prior to the bond issue. P-values are in parentheses.
36
TABLE 3 Multivariate Ordered Probit Model with EPSDQ as Response Variable
Predicted sign Model 1 Model 2 Model 3 Intercept ? 0.2839 0.0971 -0.6854 (0.8794) (0.9590) (0.7531) Intercept2 ? 0.5732 0.5752 0.5799 (0.0020) (0.0020) (0.0020) BIAS - -192.5510 -179.7330 -175.1300 (0.0305) (0.0389) (0.0486) ERCRANK - -0.0985 -0.0883 -0.0947 (0.1832) (0.2224) (0.1877) ROA - -1.7763 -1.6886 -2.0168 (0.5720) (0.5811) (0.5224) SIZE - -0.4008 -0.3877 -0.3947 (0.0204) (0.0215) (0.0204) TV - -0.0566 -0.0534 -0.0581 (0.0070) (0.0042) (0.0035) CEOHOLD + -1.1253 (0.7580) CEO=COB - 0.1620 (0.7235) %BODIND + 1.0295 (0.4090) VOL + 9.3603 8.8999 9.7235 (0.0022) (0.0016) (0.0013) N 60 60 60 Log likelihood -39.41 -39.39 -39.11 Pseudo R2 0.31 0.31 0.31
37
EPSDQ is a disclosure quality score that measures the COCO information disclosed in the EPS footnote alone. This measure takes on a value of “1”, “2”, or “3”, where “3” represents the highest disclosure quality. BIAS is defined as annual diluted EPS as reported for the year of issuance minus diluted EPS using the if-converted method. ERCRANK is the decile rank of R2s from industry-specific regressions of annual market-adjusted stock returns on changes in annual diluted EPS. ROA is the return on assets for the firm. SIZE is the logarithm of total assets. TV is the total annual trading volume divided by total shares outstanding at fiscal year-end. CEOHOLD is defined as total shareholdings owned by the CEO divided by total shares outstanding. CEO=COB is an indicator variable that equals one if the CEO is also the chairman of the board, or zero otherwise. %BODIND is the percentage of independent (non-employee and unaffiliated) board members. VOL is defined as the annualized standard deviation of daily stock returns for the year prior to the bond issue. ERCRANK, ROA, SIZE, TV and VOL are all measured in the year prior to the bond issue. P-values are in parentheses.
38
TABLE 4 Multivariate OLS Regression with TOTDQ as Dependent Variable
Predicted sign Model 1 Model 2 Model 3 Intercept ? 33.6093 33.5596 29.8265 (0.0008) (0.0009) (0.0070) BIAS - -667.6417 -663.2896 -665.8929 (0.0168) (0.0199) (0.0155) ERCRANK - -0.5889 -0.6028 -0.6486 (0.1249) (0.1141) (0.0841) ROA - -6.9227 -9.1115 -11.3471 (0.6859) (0.5954) (0.5105) SIZE - -2.3169 -2.3916 -2.4343 (0.0078) (0.0057) (0.0047) TV - -0.2431 -0.2525 -0.2724 (0.0029) (0.0012) (0.0006) CEOHOLD + 9.1060 (0.6416) CEO=COB - 0.8718 (0.7191) %BODIND + 5.9671 (0.3814) VOL + 40.0332 41.5686 44.7364 (0.0034) (0.0015) (0.0008) N 60 60 60 Adjusted R2 0.27 0.27 0.28
TOTDQ is a disclosure score ranging from 10 through 39 that measures the COCO information in both the EPS footnote and the long-term debt footnote. Higher values represent high disclosure quality. BIAS is defined as annual diluted EPS as reported for the year of issuance minus diluted EPS using the if-converted method. ERCRANK is the decile rank of R2s from industry-specific regressions of annual market-adjusted stock returns on changes in annual diluted EPS. ROA is the return on assets for the firm. SIZE is the logarithm of total assets. TV is the total annual trading volume divided by total shares outstanding at fiscal year-end. CEOHOLD is defined as total shareholdings
39
owned by the CEO divided by total shares outstanding. CEO=COB is an indicator variable that equals one if the CEO is also the chairman of the board, or zero otherwise. %BODIND is the percentage of independent (non-employee and unaffiliated) board members. VOL is defined as the annualized standard deviation of daily stock returns for the year prior to the bond issue. ERCRANK, ROA, SIZE, TV and VOL are all measured in the year prior to the bond issue. P-values are in parentheses.
40
TABLE 5 Tests of Value Relevance
CAR = β0 + β1 Diluted EPS + ε
Diluted EPS as reported
Diluted EPS
using if-converted method
Vuong’s (1989) test of competing
models
Adjusted R2
Adjusted R2 Z-statistic (p-value)
All firms (N=60) 9.69% 9.04% 1.0709
(0.2846)
High-disclosure firms (N=21) 7.67% 7.45% 0.3509 (0.7264)
Low-disclosure firms (N=39) 11.30% 10.35% 1.1200
(0.2628)
CAR is market-adjusted returns, using an equal-weighted portfolio, measured over a 12-month period beginning three months after the fiscal year end for the year of the bond issue. Diluted EPS equals either annual diluted EPS as reported or from using the if-converted method, divided by price at fiscal year-end. High-disclosure firms are firms that disclose any COCO-related information in their EPS footnote; low-disclosure firms are all other firms. The Vuong (1989) Z-statistic compares the reported Diluted EPS model with the adjusted Diluted EPS model as competing non-nested models. A positive Z-statistic indicates that the reported Diluted EPS model performs better than the adjusted model. Probability levels from two-tailed tests are reported in parentheses.