Why Do Public Firms Issue Private and Public Securities?
Armando Gomes
Gordon Phillips
ABSTRACT
We examine public rms' issues of private and public debt, convertibles, and common equity securities. The market for public rms issuing private securities is large. Of the over 13,000 issues
we examine, more than half are in the private market. We nd that asymmetric information
plays a major role in the choice of security type within public and private markets. Conditional on issuing in the public market, rms' predicted probability of issuing equity declines
and issuing debt increases with measures of asymmetric information. We nd a weak reversal
of this sensitivity in the private market. We also nd large di erences in the sensitivity of
security issue decisions to market timing, risk and investment opportunity variables in public
and private markets. Our results point to a potentially important unexplored dimension of
capital structure - the public-private funding ratio in addition to the debt-equity ratio.
This version: February 16, 2007
Comments Welcome
Washington University and University of Maryland and NBER respectively. Gomes can be reached at [email protected]
and Phillips (corresponding author) can be reached at [email protected]. We thank the nancial support provided
by the Rodney White Center for nancial research. We also thank John Graham for data on marginal tax rates and Murillo
Campello, Mark Chen, Kathleen Hanley, Jerry Hoberg, Josh Lerner, Craig MacKinlay, Alan Morrison, Matthew Spiegel,
Catherine Schrand as well as seminar participants at Arizona, Boston University, Cornell, Florida, George Washington, Harvard, Illinois, Minnesota, Penn State, Rochester, Rutgers, UBC, UCLA, Utah, Texas-Austin, Tulane, Washington University,
Wharton, the ACLE/JFI Conference and the NYU Five Star Conference for helpful comments. We alone are responsible for
the conclusions and analysis in this paper.
Electronic copy of this paper is available at: http://ssrn.com/abstract=972723
Why Do Public Firms Issue Private and Public Securities?
ABSTRACT
We examine public rms' issues of private and public debt, convertibles, and common equity securities. The market for public rms issuing private securities is large. Of the over 13,000 issues
we examine, more than half are in the private market. We nd that asymmetric information
plays a major role in the choice of security type within public and private markets. Conditional on issuing in the public market, rms' predicted probability of issuing equity declines
and issuing debt increases with measures of asymmetric information. We nd a weak reversal
of this sensitivity in the private market. We also nd large di erences in the sensitivity of
security issue decisions to market timing, risk and investment opportunity variables in public
and private markets. Our results point to a potentially important unexplored dimension of
capital structure - the public-private funding ratio in addition to the debt-equity ratio.
Electronic copy of this paper is available at: http://ssrn.com/abstract=972723
1
Introduction
In this study we examine why public rms issue di erent security types within public and private security
markets. We study both private and public issues of debt, convertibles, and common equity, a total of
six di erent security-market choices. Our comprehensive database makes it possible for us to assess the
factors that impact both security type and market choice.
The private security market is increasingly important for public rms. Of the over 13,000 issues by
public rms we examine, more than half are in the private market, comprising issuances of equity, debt,
and convertible bonds and convertible preferred stock (henceforth, convertibles). Among the rms that
choose to issue equity or convertibles, 58 percent of the issues are in the private market, and among small
public rms ( rms in the lowest size quartile) 75 percent of the equity and convertible issue are in the
private market.
The market in which
rms sell securities and the type of securities that
rms issue are important
corporate nance decisions. The existence of asymmetric information might induce rms to sell securities
to private parties who may be better informed, or who might produce information more e ciently, thus
mitigating adverse selection problems. Moreover, rm risk and investment opportunities might in uence
both the choice of market in which rms sell securities and the security a rm issues to mitigate agency
problems.
Our study uses a methodology that allows us to jointly determine how
rms use security issuance
decisions of multiple types and in di erent markets as a mechanism to address asymmetric information
and agency problems. To examine issuance decisions in both private and public markets, we link a private
equity and convertible database, a private debt database, and the SDC new-issue database, to Compustat
and CRSP. We also link these databases to IBES so that we can use analyst earnings forecast data to
construct measures of asymmetric information.
We have three main results on security issuance. First, measures of asymmetric information are major
determinants of security issuance decisions within private and public markets. If a rm issues in the public
market, the probability that it will issue equity declines, and the probability that it will issue debt increases,
with proxies for the degree of information asymmetry. However, the sensitivity of security issuance choice
to asymmetric information is signi cantly lower in the private market than in the public market. In fact,
the probability of a rm issuing private equity and convertibles versus private debt slightly increases with
asymmetric information, a reversal of the ordering in the public market. We call these results the \security
issuance ranking."
Our analysis of the stock market returns around equity issues shows that they are negatively related
with the degree of information asymmetry for public equity and convertible o erings, but that the reverse
1
holds for private equity o erings. This evidence is consistent with the view that public investors believe
private investors obtain or produce valuable information, and that learning about private investments
is more valuable when there is a higher degree of asymmetric information. Overall, given that security
laws allow sharing of nonpublic information with private investors who sign nondisclosure agreements with
the rm, our evidence is consistent with private investors obtaining information about the rm and its
prospects.2
Second, there is a fundamental di erence in the market timing of security decisions in the public and
private markets. Firms are more likely to issue public equity rather than private equity if their stock price
has recently risen. In addition, security issuance to the public market - but not in the private market more closely follows earnings report announcements. The lack of timing for private security issuances is
consistent with an information exchange occurring in private placements when the few investors acquiring
securities (the median number of investors in private equity issuances is three) are likely to negotiate
directly with the rm.
Third, agency problems between security holders and the trade-o theory explain rms security choices
in both security markets. Firms with higher risk and investment opportunities and lower pro tability are
more likely to issue equity than debt in both private and public markets. We extend these ndings by
showing that such rms are also more likely to issue privately, and that the sensitivity of the equity-debt
decision for these variables is less pronounced in the private market.
By considering all the security-
market choices rather than a more limited choice set, we are able to draw some novel implications on the
in uence of risk on security issuance. In particular, we show empirically that rms issue private debt for
moderate levels of risk, but rms with high levels of risk and asymmetric information tend to issue private
convertibles or equity.
While we do not test the traditional Myers and Majluf (1984) pecking-order theory of capital structure,
we examine the importance of asymmetric information to security issuance. Our overall results on security
issuance show that traditional pecking-order theory and tests of theories of security issuance should take
into account the market where the security is issued as well as the type of security. Our ndings on security
issuance conditional on issuing in the public market provide support for the proposition that rms with
high measures of asymmetric information are less likely to issue equity. However, overall, our study does
not support the proposition that rms with high measures of asymmetric information avoid securities that
are informationally sensitive. Instead, we nd a slight positive sensitivity of private equity and convertibles
issuance to asymmetric information relative to private debt.
Our results showing that the probability that rms issue privately increases with asymmetric informa2
Note the securities disclosure laws, including Regulation FD, exempt communications by the rm from the disclosure
restrictions when those communications are to investors who \have expressly agreed to maintain the communication in condence pursuant to a con dentiality agreement." An article by Houston and Laitin (2000) at the law rm Robins, Kaplan,
Miller and Ciresi L.L.P., states: \As a result, companies should require con dentiality agreements prior to disseminating
diligence materials or o ering memoranda that contain material non-public information to securities market professionals or
shareholders who are likely to trade on the information."
2
tion extend the results of Hertzel and Smith (1993) and Wu (2004) who, examining just public and private
equity issues, nd support for measures of asymmetric information being important for private placements
of equity. By examining debt and convertible securities in addition to equity, we are able to test for the
impact of asymmetric information across securities and speci cally to test for di erential sensitivity of
security issuance to asymmetric information within public and private markets.
Previous results on the importance of asymmetric information to security issuance have been mixed.
Part of this reason is that many studies examining equity do not distinguish the market in which securities
are sold by public rms.3 Similar to Frank and Goyal (2003) and Fama and French (2005) we nd that
smaller rms, which are likely to be subject to problems of asymmetric information, do issue substantial
amount of equity. This nding seems to contradict the conclusion that asymmetric information is important to security issuance. However, our contribution is to show that those issues of equity by small rms
with high measures of information asymmetry are often privately placed, which signi cantly mitigates the
impact of adverse selection problems.
Our evidence on market timing of security issuance decisions extends the evidence provided by Korajczyk et al. (1991) who examine public equity issues. We nd that there is signi cantly more short-run
issue timing, for all security types, occurring in the public market vis-a-vis the private market.
Our paper is organized as follows. In Section 2 we provide the theoretical background and present our
hypotheses. This section also presents the framework for security-market choice that we use in our tests.
Section 3 gives the details on the data and variables we use in our tests. Section 4 contains the results,
and Section 5 discusses the robustness tests, and Section 6 concludes.
2
Theoretical Background and Framework for Security-Market Choice
A substantial amount of theory has focused on the role of asymmetric information, market timing, and
agency problems as primary determinants of the choice of security and market. In this section we review the
main predictions of these models, and derive their main testable hypotheses. We then formulate a reduced
form econometric model that enables us to test these hypotheses and estimate the implied sensitivity of the
rms' security issuance choices to proxies for asymmetric information, risk, and other important control
variables.
2.1 Asymmetric Information
One major group of studies focuses on problems related to adverse selection due to ex-ante information
asymmetries between managers and investors. The classic article is Myers and Majluf (1984) that shows
that asymmetric information results in a pecking order for external
3
nance - with less informationally
Papers by Mackie-Mason (1990) and Helwege and Liang (1996) do identify private debt issues but still combine public
and private equity issues as one type of security. Hovakimian, Opler, and Titman (2001) as well as Leary and Roberts (2004)
use the rm's statement of cash ows to identi y security issuance and do not identify private equity issues. These papers
do not nd much support for the importance of asymmetric information to security issuance and capital structure.
3
sensitive securities such as debt being chosen rst by rms with asymmetric information. Moreover, this
adverse selection problem may result in underinvestment because undervalued
rms may refrain from
raising nance due to the dilution cost of selling underpriced securities. Several papers that followed study
how security design mitigates or solves the adverse selection problem. In particular, Brennan and Schwartz
(1987) and Brennan and Kraus (1987) demonstrate that convertible securities can be used to solve the
adverse selection problem.
A second group focuses on the incentives of investors to become informed and produce information
about rms. Private placements to one or few investors (as opposed to an o ering to dispersed public
investors) is another mechanism that can resolve the adverse selection problem. Articles include Boyd
and Prescott (1986) and Diamond (1991) for debt o erings and Chemmanur and Fulghieri (1999) and
Maksimovic and Pichler (1999) for equity o erings.
The interaction between the security and market choice and asymmetric information is explored in
Fulghieri and Lukin (2001). Fulghieri and Lukin predict that when the costs of producing private information are relatively low the likelihood of issuing equity relative to debt in the private market will be
positively related to the degree of information asymmetry. However, the classic ordering of a negative
relation between the probability of issuing equity and the degree of asymmetric information will still hold
when the costs of producing private information are high, in which case the rm is more likely to make a
public o ering.
These studies suggest the following testable hypothesis:
Hypothesis ASY 1: Conditional on a public o ering, the probability of issuing equity and convertibles relative to debt will decrease with the degree of asymmetric information. Conditional
on a private o ering, the probability of issuing equity and convertibles relative to debt will
increase with the degree of asymmetric information.
The asymmetric information theories also have implications for the stock price market reaction around
issues, depending on the security-market choice: a positive (negative) stock market returns around private
(public) equity o erings. Empirically, early studies that examine stock returns around o erings are consistent with theory predictions (see survey by Eckbo, Masulis, and Norli (2006)).4 We add to the existing
empirical results on abnormal returns by examining whether the predicted relations between information
asymmetry and returns in each market hold.
Hypothesis ASY 2: The abnormal return around issues should be negatively (positively) related
to the degree of information asymmetry for public (private) o erings of information sensitive
securities such as equity.
4
Wruck (1989), Hertzel and Smith (1993), Allen and Phillips (2000), Chaplinsky and Haushalter (2003), and Brophy et
al. (2004) nd positive stock market returns around traditional private placements of equity and convertibles. These results
are in contrast to the negative returns around public o erings of securities found in Asquith and Mullins (1986), Masulis and
Korwar (1986), and Mikkelson and Parch (1986).
4
2.2 Market Timing
We examine the practice among rms of \equity market timing," i.e., rms issuing equity when their
market values are high relative to past market values. We investigate whether the practice of market timing
takes place among private equity issues. We examine how announcement returns are related to security
issuance, expanding the results of Asquith and Mullins (1986) who examine public equity issues. We also
examine how the probability of various types of security issuance in the public and private market varies
with a rm's lagged stock returns. Given that private investors are likely to be more sophisticated and
produce information, we expect that market timing by rms is less intense for private equity issues than
it is for public equity issues.
Lastly, we extend the results of Korajczyk, Lucas and McDonald (1991) to the private security market.
Korajczyk et. al. show that public equity issues tend to follow earnings releases. We examine whether
the relation between the timing of private o erings and earnings release dates is weaker or disappears in
the private equity market. This outcome is likely if investors in the private markets can better produce
information and/or rms can more easily transmit information to private investors than to dispersed public
investors.
2.3 Risk, Investment Opportunities and Agency Problems between Claimants
Research classi es two types of agency problems between security holders: the asset substitution problem (Jensen and Meckling (1976)) and the debt overhang or underinvestment problem (Myers (1977)).
The simplest solution to these debt-holder and equity-holder agency problems is to issue equity rather
than debt. Moreover, Green (1984) and Brennan and Schwartz (1988) propose that convertibles can
mitigate agency costs of debt as convertibles provide incentives for managers not to undertake projects
with excessive risk.
These theories thus generate the following testable hypothesis:
Hypothesis AG1: The likelihood of rms issuing equity and convertibles increases with risk and investment opportunities, for both private and public markets.
Moreover, private debt is advantageous when the rm enters in nancial distress because public debt
is governed by the Trust Indenture Act of 1939, which makes renegotiation of public debt contracts more
di cult than private debt (see Gorton and Winton (2003) for a recent survey of the literature).
Given private debt contracts are easier to renegotiate than public debt contracts, private placements of
debt are more likely than public debt placements in riskier and high growth rms. Similarly, there is less
sensitivity of the equity-debt decision to risk and investment opportunities in the private security market
than in the public market { this is so because equity issuances in the public versus the private market are
relatively insensitive to risky and growth opportunities, while public debt issuances are not. Formally, we
test the following:
Hypothesis AG2: The sensitivity of the equity-debt decision to risk and investment opportu-
5
nities is more pronounced in the public security market than in the private security market.
Finally, incentives to use debt nancing increase with a rm's marginal tax rate due to deductibility of
interest expenses. So the incremental use of debt (and convertibles) could be driven by tax motives. In our
analysis we include Graham's (1996) marginal tax rate as a control variable to evaluate the importance of
taxes relative to other key variables for issuance decisions in public and private markets.
2.4 Reduced Form Model of Security-Market Issuance
To test the predictions from the hypotheses we formulate, we estimate several di erent econometric
models of security-market issuance decisions.
In our reduced-form econometric model we assume that the rm wants to raise external funds I to invest
in a project with positive net present value (NPV). Let the NPV of a rm that is issuing security j be Vj (x)
net of direct and indirect issuance costs, where x is a vector of exogenous, observable rm characteristics,
and j = e; c; d; E; C; D denotes, respectively, private equity, private convertibles, private debt, public equity,
public convertibles, and public debt. The rm chooses the securities-market J that maximizes rm value:
We model the (unobserved) value function as a linear function of the observed relevant rm characteristics
plus a random noise. We consider several di erent speci cations, both multinomial logit and nested logit
models, for the security issuance decision based on di erent assumptions about the random noise or error.
The multinomial logit model is one of the models we estimate. In this model, the random errors
for each choice are independent and identically distributed with the extreme value distribution. The
multinomial logit model, although appealing in its simplicity, turns out not to be a good model for security
issue decisions.5 In this model we assume that choices between any two alternatives are independent of
the others, i.e., the independence of irrelevant alternatives (IIA) assumption. The IIA assumption says
that if one of the alternatives is removed from the model, the other alternatives will have a proportionate
increase in their probability of being chosen.
Thus, we also estimate a nested logit model, which do not impose the IIA assumption. We estimate
a nested logit model in which unobserved factors a ect security choice conditional on the market, causing
errors to be correlated across securities within markets.6 The model is estimated using the maximum
likelihood estimation method. The multinomial logit model is a particular case of the nested logit model
(when all errors are uncorrelated) and we reject this model. One important advantage of the nested logit
model is that it allows us to estimate di erent conditional probabilities, as in Hypothesis ASY 1.
In this model we estimate the unconditional sensitivity of the probability of choosing a market (public
5
We present the results of the simultaneous choice multinomial model in an appendix. Examination shows that our
conclusions are similar and the results actually stronger than the nested logit models.
6
Another possibility is to use a multinomial probit model with a general correlation structure. We attempted to estimate
this model, however it did not converge. Multinomial probit models are known to be computationally very intensive and
become impractical when the number of choices is above three and there are a large number of observations.
6
or private) to rm and market factors, and the sensitivity, conditional on market type, of the probability
of choosing to issue debt, convertibles, or equity. Thus, we can use this model to test for a probability
ordering of the conditional sensitivity of security issuance decisions to rm and market factors. In this
nested logit model, we assume that the choice between security type conditional on the market (or nest)
is correlated, and that the errors across markets are uncorrelated (see Train (2003)).7 The value of each
choice is given by:
Choice 2
Equity
Convertibles
Debt
Choice 1
Private
Ve = be x + bpriv x + "e
Vc = bc x + bpriv x + "c
Vd =
bpriv x + "d
Public
V E = bE x + " E
V C = bC x + " C
VD =
"D
In the above table bj x is the additional value from choosing a particular security j = e; c; E; C relative
to debt, with bpriv x the additional value a rm gets from making a decision to issue in the private market.
A key property of the model, which involves estimating the predicted choice by using a nested logit
speci cation, is that the odds ratio between grouped choices, say, public equity and public debt, conditional
on the rm issuing publicly, is given by
PE
Pr[Y = Ejpublic]
=
= ebE x :
PD
Pr[Y = Djpublic]
(1)
Speci cally, the coe cients from this model represent an increase in the log odds ratio relative to the
base category. So if the coe cient bkE for public equity for variable xk is positive (negative), then increases
in this control variable xk increase (decrease) the relative log odds ratio of issuing public equity over
P
public debt, conditional on the rm issuing publicly, i.e.,
d ln( PE )
D
dxk
= bkE . Other similar relation hold for
the relative odds of issuing di erent securities in the private market.8
For example, using the coe cients of the nested logit models, we can test the following hypotheses
related to the speci c theories and predictions discussed earlier in this section.
Sensitivity to asymmetric information: Let xk represent the degree of asymmetric information
facing the rm, and let bkj ( j = e; c; E; C ) be the coe cients with respect to asymmetric information
variable k.
Test of Hypothesis ASY1:
bkE < bkC < 0 for the public market, and bke > bkc > 0 for the private market.
7
We assume that the errors have a generalized extreme value distribution (GEV) (see Train (2003)). For any two alternatives
in two di erent nests, say, private debt and public convertibles, the errors are uncorrelated. But for two alternatives in the
same nest, the errors are correlated.
8
The nested logit model implies that the independence of irrelevant alternatives holds within each nest (security choice
given the market). We nd that when we estimate a conditional multinomial logit model using just private or public issues,
the IIA assumption holds.
7
Sensitivity to risk and agency problems: Let xr represent the risk and investment opportunity
variables, and let brj ( j = e; c; E; C ) be the coe cients with respect to risk variable r . The hypotheses
about the importance of agency costs in terms of the coe cients of the nested logit model can be written
as follows:
Test of Hypothesis AG1: brE > brC > 0 and bre > brc > 0 (i.e., the sensitivity of equity issuance to risk
will be greatest for equity followed by convertibles and debt for both public and private markets).
Test of Hypothesis AG2: brE > bre and brC > brc (i.e., the sensitivity of equity and convertible issuance
to risk will be greater in the public than in the private market).
3
Data and Variables
3.1 Data
We study security issuance by public U.S. corporations from January 1995 to December 2003. The data
on securities issuance comes from three di erent databases: the PlacementTracker Database of Sagient
Research Systems and the Securities Data Corporation (SDC) new-issues database, and the DealScan
database of the Loan Pricing Corporation for debt issues.
We exclude secondary o erings in which the company is not issuing new shares, and short-term debt
o erings, those o erings with a maturity of less than one year. We exclude short-term o erings because
these are not typically viewed as part of capital structure.
A private placement is a private sale of unregistered securities by a public company to a selected group
of individuals or institutional investors without general investor solicitation. These sales are typically made
to a small number of investors (the median (mean) number of investors in our private equity o erings is
3 (5.4)) and are generally conducted in accordance to the \safe harbor" provisions of Regulation D of
the 1933 Securities Act.9 Prior to negotiations leading up to the sale of securities privately, investor(s)
conducting negotiations with the rm will sign a con dentially agreement that precludes them from trading
on any information privately revealed (see footnote 2). In fact, the mere fact that they sign the agreement
and learn of the issue classi es them as an insider even if they do not purchase any securities until the
issue has been publicly announced.
The PlacementTracker database is a comprehensive source for information on private placements of
equity-linked securities are also commonly referred to as Private Investments in Public Equity, or PIPEs.
We exclude from our sample a few transactions classi ed as common stock shelf sales and equity line
arrangements, because they typically require a registration statement to be e ective prior to the sale of
the stock, technically making them public o erings. This source for private equity is more comprehensive
than SDC having 2.5 times as many private equity issues for the same period as SDC.
9
Regulation D is an SEC Rule that allows public companies to issue stock privately, without the need for public registration
prior to the sale, to an unlimited number of accredited investors and no more than 35 non-accredited investors.
8
After matching with Compustat and CRSP, and excluding nancial companies and regulated rms,
we have a total of 1,377 private equity issues made by 838 companies and 1,156 private convertible issues
made by 748 companies.
Our sample of private corporate debt is from the DealScan database. We include in our sample only
long-term commercial loans and revolving credit lines. Thus, for example, we drop 364-day facilities and
any other loan with less than one year of maturity. We also drop credit lines whose primary purpose is to
back up commercial paper, since those credit lines are seldom used.
Companies often borrow by using multiple loans or tranches at the same time. In our data set, we
aggregate all tranches into a single transaction or deal, adding up the amount of all long-term loans and
revolving credit lines. Our nal sample of private corporate debt involves 5,609 deals by 2,667 di erent
companies over the 1995-2003 period (mean (median) number of 2.1 (2) private debt o erings per company).
The most common type of private debt is revolving credit lines (78% of the deals) followed by term loans
(18% of the deals). In case of multiple tranches we determine the deal type based on the type of the largest
tranche.
We also include in our data set Rule 144-A convertible and debt issues, which are also private placements
of unregistered securities. We aggregate multiple deals by the same company and of the same type (i.e.,
one of the eight security-market choices) that occur within the same month, because we believe that they
are likely to be di erent tranches of the same deal-the procedure serves to combine mostly multiple debt
issues.
The key distinction we explore between publicly and privately placed securities is that in the latter
there are fewer investors purchasing securities and the private (unregistered) securities they acquire are less
liquid. Private placement investors are then likely to have more incentives to produce information and to
monitor. The institutional details and our data indicate that 144-A issues and public issues are similar, but
144-A and private o erings are quite di erent (see, for example, our results in Table 3). Thus, throughout
most of our analysis, we aggregate 144-A and public o erings. We also consider a full eight-choice model
in which we look separately at the choice of 144-A convertibles and debt, and nd similar results.
We match the data obtained from these sources to Compustat and CRSP, to obtain information on
rm
nancials and stock prices. Following standard practice in the literature, we excluded from our
sample nancial rms (SICs 6000-6999) and regulated utilities (SICs 4900-4999). Matching to CRSP and
Compustat yields a total of 17,634 transactions during the 1995-2003 period. We drop observations with
insu cient stock price information in CRSP (1,506) and without information in Compustat on assets,
debt, or earnings at the scal year ending before the issue date (1,851).
Note that we need data from
Compustat for two years prior to the security issue given the lagged debt ratio is computed as debt ratio
divided by lagged assets. These requirements give us 13,419 transactions. For these transactions, there
are 11,770 observations with data on the marginal tax rate, 10,523 observations with data on corporate
governance and 11,209 observations with IBES analyst data. The intersection of these databases yields
9
8,346 observations used in the regressions.
3.2 The Variables
We include variables to proxy for asymmetric information, risk, investment opportunities, market timing
and market conditions. These variables are obtained and calculated as follows:
3.2.1 Asymmetric Information
We match our dataset to IBES to use analyst earnings forecasts as our main proxy variables for asymmetric information.
The main idea is that dispersion among analysts' forecasts and analysts' earnings
surprises are two measures that are positively correlated with information asymmetry (between managers
and investors). Lang and Lundholm (1996) show that both analysts' forecast accuracy and dispersion
signi cantly decrease when rms make more informative disclosures about future earnings (see also Atjintkya et al. (1991)). Better rm disclosure reduces information asymmetry and thus we expect a positive
relation between both dispersion and earnings surprise and information asymmetry. Note that information
disclosure can also be costly (or not credible because rms want to increase their share price). For example,
competitors are also able to observe publicly disclosed information, so public disclosures can potentially
reduce rm value (James and Wier (1988)).
In our study we use analysts' forecasts for the company's upcoming quarterly earnings release in the
IBES summary history database. We compute a quarterly analyst earnings surprise as the absolute value
of the di erence between the median quarterly earnings estimate and the actual quarterly earnings per
share, normalized by the stock price at the scal quarter end (we also consider the robustness to alternative
normalizations based on the book value of equity per share and earnings per share). A similar approach
is used to construct the quarterly analyst earnings dispersion measure: it is the standard deviation of
outstanding earnings forecasts normalized by the stock price. Note that this measure is only available if
there are at least two outstanding earnings forecasts.
Even though all rms in our sample are public, they may have incentives to disclose more information
prior to a public issue than prior to a private issue. To control for this endogeneity and potential change
in rms' disclosure policy prior to a nancing round, when we build our measures for forecast accuracy
and dispersion we drop the most recent quarter before the issue date, and we use the average of the last
four quarters ending a quarter before the issue date. Thus the earnings surprise and dispersion measure
used for each deal is the mean quarterly earnings surprise and dispersion for the last four quarters ending
a quarter before the issue date. The surprise and dispersion measures are trimmed to remove the most
extreme 1% observations. This serves to remove outliers and potentially misrecorded data.
For robustness we also examine three other measures of asymmetric information. The rst of these
is the insider trading measure used by Lakonishok and Lee (2001). For each issue, we compute the net
purchase ratio calculated as the number of shares purchased minus shares sold by insiders in the last six
10
months before the issuance month, divided by the number of shares purchased and sold during the same
period.
The second measure of asymmetric information is the abnormal stock return to lagged earnings announcements. We compute for each issue the average of the absolute value of the abnormal cumulative
return (using a market model) for ve days (-2 to +2) surrounding the earnings announcement day for the
last 4 quarters prior to the security issuance.
The third measure is a composite measure and comes from stock returns and the volume of stock
trading relative to shares outstanding.
Wu
(2006).10
We calculate this measure following Bharath, Pasquariello and
The di erent stock return and volume measures we use from Bharath, Pasquariello and
Wu (2006) include the following: Roll's (1984) measure using the serial correlation of stock returns, a
stock's turnover measured as the inverse of a stock's average trading volume divided by the number of
shares outstanding, and a stock's return autocorrelation using the methodology of Llorente, Michaely, Saar
and Wang (2002). We form a quintile ranking for these di erent stock return and volume measures and
then average the resulting quintiles.
Quintiles are formed for each of these measures with quintile one
containing stocks with the lowest values of each measure and then we average the quintile measures over
these three volume and return based measures to form an aggregate measure of asymmetric information.
3.2.2 Risk, Investment Alternatives, Taxes and a Firm's Need for Funds
In this section we describe how we calculate a rm's risk and investment opportunities. These variables
are included to proxy for the importance of agency problems to the rm's issuance decisions.
We also
describe how we calculate other control variables that we include in our speci cations.
Risk is measured by the rm's cash
ow volatility calculated as the standard deviation of cash ow
(operating income before depreciation, Compustat data number: data13) using up to twenty scal quarters
prior to the deal date. We require a minimum of four quarters prior to the deal issue date for this measure
to be calculated.
Investment opportunities is measured by the Tobin's q, which is calculated as the market value of the
rm divided by the book value of assets (data6), R&D divided by lagged property plant and equipment,
which is de ned as the total of R&D plus advertising (Compustat data numbers ((data45+data46)/lagged
data8). Pro tability is operating cash ow before depreciation divided by lagged assets (data13/lagged
data6). All of these variables are computed for the last scal year ending before the transaction date. We
also include a nancial distress indicator variable equal to one if Altman's Z-score is less than 1.81 and
zero otherwise. Altman (2000) shows that a Z-score below 1.81 is a good predictor of corporate distress.
Other control variables include a rm's debt/asset ratio, calculated as long term debt divided by book
value of assets (Compustat data numbers: data9/lagged data6), the log of rm value ( log rm size) which
is equal to market value of equity plus book values of preferred stock and total debt (Compustat data
10
We do not use the PIN measure that is used by Bharath, Pasquariello and Wu (2006) as this measure captures asymmetric
information among outside shareholders and, more importantly, is not available for smaller stocks traded on the NASDAQ.
11
numbers: data24*data25 + data9 + data34 + data39), and a rm's marginal tax rate.
The data on a
rm's marginal tax rate was kindly provided to us by John Graham and is described in more detail in
Graham (1996) and Graham and Lemmon (1998).
For our transactions, there are 11,770 observations
with data on the marginal tax rate.11
We also include an instrumented measure of a rm's \need for funds" (its internal funding de cit). This
measure is constructed for the year prior to the issue and is calculated as capital expenditures (Compustat
data number: data128) plus the change in net working capital (-data302 -data303 -data304 -data305 data307 +data274 -data312 -data301) less a rm's cash ow from operations (data13). We include this
measure to control for the possibility that a rm may go to the private market, not because of asymmetric
information or risk, but because it only needs a smaller amount of funds given that there may be a smaller
xed cost of raising capital in the private market. We also recognize that this measure may be endogenous
as a small calculated \need" or de cit may not be indicative of actual need as the rm may also have
been constrained in the past. Thus we instrument the measure of a rm's nancial need with industry
instruments and lagged rm instruments and use the predicted value in our regressions.12
We use as
instruments median industry Tobin's q, median industry capital intensity (capital expenditures divided by
sales), lagged rm size (total assets), lagged rm size squared, and lagged pro tability. These instruments
follow from Maksimovic and Phillips (2007) prediction of external nancial dependence.
For all rm-speci c constructed variables except Tobin's q, marginal tax rate and rm size we eliminate
outliers by dropping the top and bottom one-percent of the sample in each year.13
Given correlation
of variables, this screen a ects only approximately 3 percent of the sample (in addition many of these
observations would be dropped given missing values for some variables). We also eliminate rms whose
lagged book value of assets are less than 1 million dollars and whose Tobin's q is in the 99th percentile or
above.
3.2.3. Market-Timing and Market Conditions
Using CRSP data we calculate a rm's cumulative abnormal return 250 days prior to the deal minus
the excess return relative to a benchmark portfolio of rms in the same size decile at the end of the year
previous to the transaction (we also used risk-adjusted beta decile portfolios for robustness). For each
deal we also compute the abnormal excess return using a 10 trading-day window around each issue- the
parameters of the market model were estimated in the prior 250 trading days ending at the beginning of
the event window.
We include three market variables in our regressions to capture aggregate market conditions in the public
market. We include the Aaa bond yield, a credit spread to capture a distress risk premium, measured as
11
Like Graham (1996), we use the marginal tax rate after deductions for depreciation, interest and leasing expenses.
Note including predicted nancial need or de cit is meant to capture the same idea of the xed cost of raising capital that
the issue size would capture without the endogeneity problems that would arise from including a choice variable.
13
Instead of eliminating these observations, we also winsorized observations. We set positive (negative) outliers to the 99th
(1st) percentile. Results were una ected by this change.
12
12
the Baa less the Aaa bond yield- we use the value of these variables as of the end of the previous month
before the issue date. To capture conditions in the public equity market we include the cumulative market
return over the 250 days prior to the security issue date. Finally to control for industry-speci c factors
we include Fama and French industry dummies (17 industry categories) in all regressions we estimate.
B4. Corporate Governance
Agency problems between managers and shareholders can also create signi cant distortions and the
security and market choice could be chosen to address corporate governance problems. For example,
the importance of debt as a mechanism to mitigate agency problems has been argued by many, notably
Jensen (1986).
The threat of takeover or loss of control is an alternative (or substitute) mechanism to
the use of debt in curbing managerial distortions. Indeed Jensen and Ruback (1983), and Shleifer and
Vishny (1989) argue that agency problems among shareholders and managers are particularly severe when
managers can resist hostile takeovers. In addition, monitoring by large investors is another mechanism
to deal with managerial excess considered in the literature (e.g., Shleifer and Vishny (1989) or Kahn and
Winton (1998)). A private placement of a block of shares to an investor that naturally becomes a large
shareholder is a direct way to improve monitoring and concentrate ownership.
We include corporate governance provisions in our speci cations to examine empirically whether these
provisions impact security issuance di erentially in public and private markets. Our proxy for the degree
of agency costs of equity is the quality of corporate governance as re ected by the provisions adopted
by rms in their charters and bylaws. We follow the approach used by Daines and Klausner (2001) to
build a corporate governance measure. They focus on four key antitakeover provisions on the charter
and bylaws that erect signi cant barriers to a hostile acquisition: (1) dual-class shares; (2) a classi ed
(or staggered) board; (3) prohibition of shareholders voting by written consent; and (4) prohibition of
shareholders calling a special shareholder meeting. Daines and Klausner (2001) argue that (2) and (3) are
almost perfect substitutes so there is a shareholder voting restriction if and only if (3) and (4) are both in
place.
We construct a rank level ordering measuring the quality of corporate governance following Daines
and Klausner (2001, pg.116): 1 (worst), if the rm has dual-class shares or has a classi ed board and a
shareholder voting restriction; 2, if the rm has a classi ed board but no shareholder voting restriction
or dual-class shares; 3, if there is a shareholder voting restriction but not a classi ed board or dual class
shares; and 4 (best), if the rm has none of the restrictive provisions above.14
Our data on corporate governance provisions are from three di erent sources: the Investor Responsibility Research Center (IRRC) dataset on takeover defenses, SharkRepellent.net dataset, and, for a randomly
selected sample of 2,000 deals not matched to any of the two datasets, we hand collected the information
14
Daines and Klausner (2001) also make a further re nement based on whether the charter require a 90 days or more
advance notice for the nomination of board candidates. We chose not to use this provision because it is not available in the
IRRC dataset (also we believe this provision is not as relevant as the other ones).
13
from the rm's charter and bylaws. The information we use to construct the governance measure is based
on the provisions prevailing in the charters and bylaws before the deal date.15 The use of takeover defenses
in our sample is similar to the results reported in Daines and Klausner (2001), Field and Karpo (2002),
and Gompers et al. (2003). The distribution of the corporate governance measure is, in increasing order,
31% (worst), 29%, 6%, and 34% (best), for the 10,523 deals with complete information.
4
Results
4.1 The Sample
Table 1 summarizes our sample of public rms and their issue decisions by year and for the entire
period. We present data for eight di erent security types: public equity, convertibles and debt, private
equity, convertibles and debt, and Rule 144-A debt and convertibles. The total amount raised from 1995
to 2003 was over $2.9 trillion and the mean (median) amount raised by each deal is also large, representing
23% (13%) of the total rm value. There are a total of 4,267 di erent rms in our nal sample, and the
median rm nanced 2 times during the period (most of the multiple issues are multiple debt o erings by
the same company).
Insert Table 1 here
Table 1 shows that private equity and private convertible issues are a substantial fraction of securities
issued by public companies. This fraction has also been increasing over time with the number of private
equity issues exceeding public equity issues from the year 2000 to 2003, the last year of our database.
Second, the number of private convertibles is greater than the number of public convertibles for all years
since 1995. The table shows that while private debt issues are larger than public debt issues, private equity
issues are smaller and represent a smaller fraction of rm value. Third, the size of private equity issues
and the size of issuers has also grown sharply in the later years.
In later years the size of private equity
issues on average is almost 25% of the size of an average public equity issue. Finally, Table 1 shows that
Rule 144-A debt and convertible issues are closer in size to public debt and convertible issues than private
issues.
Insert Table 2 here
Table 2 summarizes the sample by rm size.
lagged pre-issue assets.
We split rms into quartiles by the amount of their
The table shows that small public rms disproportionately issue private equity
and private debt. The table shows that 98.8 (97.7, 62.6) percent of the debt (convertible, equity) securities
15
IRRC data is available for 1990, 1993, 1995, 1998, 2000, and 2002. SharkRepellent.net does not record historical information, so we used the current information for 2,700 deals matched to SharkRepellent.net. However, since rms seldom change
provisions in charters and bylaws, we believe that this procedure is not likely to introduce signi cant measurement errors.
14
issued by small rms are in the private market. The private debt statistics are probably not that surprising
given that our sample includes bank loans.
and public issues as very striking.
However, we view the comparison between the private equity
Firms in the second size quartile also issue more public equity and
less private equity than the rst size quartile but more private equity than rms in the third or fourth
quartiles. Comparing across all size groups, the rms in the smallest size quartile issue 67.8 percent of the
private convertibles and 68.6 percent of the private equity issues. Public rms issuing private securities
are disproportionately in the rst and second size quartiles.
Table 3 summarizes the major rm- and market-speci c variables that we examine. In Panel A, we
present summary statistics in this table for the whole sample and also for each of the eight security
categories.
We present means, standard deviations and the number of observations for each variable.
Panel B of Table 3 presents t-statistics testing whether the means and Mann-Whitney tests of whether the
medians from Panel A are di erent across issue types.
Insert Table 3 here
Table 3 show several interesting and signi cant patterns across the variables.
First, columns one and
two of Panel A show our measures of asymmetric information, analyst earnings surprise and dispersion,
are both signi cantly higher (test statistics for signi cant di erences in means and medians are presented
in Panel B) for securities issued in the private market than in the public market, consistent with the view
that there is more asymmetric information for companies involved in private deals. Note that the surprise
measure is available for 11,209 of the transactions (85% of total) and the dispersion measure for 9,793 (75%
of total). The dispersion measure is available for fewer deals as we require at least two earnings forecasts
for this measure.
Table 3 also show that private rms are smaller, have higher cash ow volatility (our measure of risk),
higher R&D ratios and higher Tobin's qs versus private securities of the same security type. Firms that
issue in the private market, however, have lower pro tability and higher measure of nancial distress despite
having less debt.
While private convertible issuers are sharply di erent from public issuers, issuers of
convertibles in the 144-A market are not signi cantly di erent for most variables from public issuers. They
are also closer to public debt issuers than they are to private debt issuers.
The picture that emerges from these summary statistics is that public rms issuing in the private market
are smaller, highly valued, and less pro table versus public issuers.
They also have higher measures of
our proxies for asymmetric information than do rms issuing in the public market.
irrespective of the security type.
This conclusion holds
Finally, issuers in the public equity and convertible markets issue after
a period of high cumulative abnormal returns - reinforcing the conclusions of Asquith and Mullins (1986)
about market timing. Abnormal returns prior to private security issues are much lower than the abnormal
returns prior to public security issues. Also especially interesting, and consistent with the classic trade-o
15
theory, issuers of debt are more pro table - especially when we compare issuers of private debt to issuers
of private equity and private convertibles - who have signi cantly negative operating cash ows.
4.2 Stock Market Response
Table 4 presents the results from cross-sectional regressions of the cumulative abnormal returns on issue
type and issuer characteristics. We run regressions for equity, convertibles and debt separately to examine
the di erences across markets, conditional on security type.
Insert Table 4 here
Inspection of Table 4 models (1), (3), and (5) reveals results consistent with previous event studies.
We regress the 10 trading-day CAR around the issue on the private and public dummies and other control
variables. The market reaction to public equity, convertibles and debt are negative while the market reaction
to private equity is signi cantly positive, consistent with Wruck (1989), Hertzel and Smith (1993), and
Allen and Phillips (2000). For private convertibles and private debt coe cients are insigni cantly di erent
from zero.
In models (2), (4), and (6) we add the earnings surprise interacted with the private-public dummies.
The signi cant positive interaction variable between earnings surprise and private issues in the equity
markets is consistent with our hypothesis ASY2 for private equity.
Finally, the results also show that
rms that issue equity after a large runup in the stock price su er a negative reaction, consistent with the
market believing that equity issuers are timing the market.
4.3 Does the Public-Private Distinction Matter?
Before we present our models which recognize the public-private market explicitly, we rst examine
results where we do not control for the market. In Table 5 we present results of a logit model where we
combine the private and public equity and also the private and public debt. In this model the dependent
variable is equal to one if the rm issues equity and zero if the rm issues debt. We also combine the
convertible preferred stocks into the equity category and the convertible bonds into the debt category.
This approach closely resembles what one would get using the
rm's statement of cash
ows to infer
security issuance when one does not know the market in which the security is sold.
Insert Table 5 here
Examination of the results in Table 5 shows that when we combine public and private equity and
public and private debt, neither of our two asymmetric information variables is signi cant. The nding of
insigni cance for the asymmetric information variables when we do not identify whether securities are sold
in the public or private market is consistent with the results of previous studies.
4.4 Security Choice within Markets
In this section we present and discuss our nested models of security issuance which explicitly identify
the market in which the security is sold. Table 6 presents the results of our nested logit model, which allows
16
correlation within security type (debt, convertibles, equity).16 Using this model, we test our hypotheses
on the security choice conditional on the private or public market. The model also gives us unconditional
estimates of the value of issuing in the private and public market for all security types.
Table 6 uses
analyst earnings surprise as our measure of asymmetric information.17
Insert Table 6 here
The results on market choice reported in column 1 of Table 6 show that
rms with a high degree
of asymmetric information and high cash ow volatility are more likely to sell securities in the private
market. Small rms, with high Tobin's q, with high R&D, with lower one year abnormal returns and low
pro tability are also more likely to choose to issue securities privately.
Columns 2 through 5 report the results conditional on the market. We see that conditional on issuing
in the public market, the probability of issuing public debt (equity) increases (decreases) with asymmetric
information. We test Hypothesis ASY1 formally and nd that the coe cient for public equity (which shows
the sensitivity versus public debt) is signi cantly lower than public convertibles. Our results show that
rms' probability of issuing informationally sensitive securities decreases with asymmetric information in
the public market.
Conditional on issuing in the private market we see a partial reversal of this sensitivity of security
issuance to asymmetric information. In addition, rms' issuance decisions are much less sensitive overall
to asymmetric information. Hypothesis ASY1 predicting a reversal of the sensitivity to asymmetric information for the private market is partially supported, as coe cients for asymmetric information for both
private convertibles and equity are statistically greater than zero - however we do show a larger coe cient
for private convertibles versus private equity. Distress is the another variable that shows a di erent pattern
for public and private markets. Firms issuing privately are more likely to issue equity and convertibles
if they have high measures of nancial distress and a lower marginal tax rate.
There is no signi cant
sensitivity of security issuance in the public markets to distress.
With respect to risk and our tests of Hypothesis AG1 for risk, we nd that the ordering of sensitivity
to risk holds in the public market; it is highest for equity, next highest for convertibles, and lowest for debt
and the di erences are statistically signi cant. In the private market both equity and convertibles have
a higher sensitivity to risk versus the benchmark of private debt, but the sensitivities of private equity
and private convertibles are not statistically di erent from each other.
Thus we nd a strict ordering for
sensitivity to risk holds in the public market as speci ed by Hypothesis AG1, while a weak ordering holds
16
All the inclusive value parameters, which measure the correlation between unobserved shocks, are in the interval 0-1,
which shows that the nested logit models are consistent with value maximization.
17
Examining the coe cients of the multinomial logit model presented in Appendix A1 and comparing them to the nested
logit model (in Tables 6), we nd that while there are di erences in magnitude between the multinomial and the nested logit
models (the coe cients and marginal e ects from the multinomial model are actually larger in magnitude than the ones from
the nested logit model), the signs and signi cance across models are similar.
17
in the private market. Lastly, the sensitivity of equity and convertibles relative to risk is greater in the
public market than it is in the private market - consistent with Hypothesis AG2.
Table 7 presents the economic signi cance of the results in Table 6. To compute the economic e ects
we use the estimated model and associated coe cients from our results in Table 6. We rst present the
marginal signi cance of our primary nested logistic speci cations and then we graphically show the overall
signi cance of our results in the next subsection. For each variable, we compute the predicted probability
of each of the six rm-level choices at two points, one-half standard deviation above and below, around
each individual sample values. All other variables are held at their observation values. We then average
these probabilities over all rms in the sample.
Insert Table 7 here
The rst two columns of Table 7 show that the marginal probability of issuing in the private market is
8.8 percentage points higher as our measure of asymmetric information increases. This pattern are also
stronger for rms that have less than the median market capitalization, as shown in the second row of the
table. The subsequent columns of Table 7 shows that the sensitivity of security issuance to asymmetric
information is highest in the public market, where the probability of issuing rms issuing public equity
(debt) declines (increases) with our measure of asymmetric information. If we increase our measure of
asymmetric information, analyst earnings surprise, by one standard deviation, the predicted probability of
issuing public debt rises by 6.8 percentage points and the probability of issuing public equity declines by
11 percentage points.
We see a weak reverse ordering of probabilities in the private market.
Conditional on issuing in
the private market the probability of issuing convertibles and equity increases slightly with asymmetric
information and decreases for debt.
However, the magnitudes are much smaller than the probabilities
in the public market and show a markedly di erent pattern consistent with information being revealed
to private investors or with private investors having better information before the issue. This table thus
shows partial support for Hypothesis ASY1.
Security choice is also highly sensitive to risk and investment opportunities. Risk, R&D to net xed
assets and Tobin's q have a large e ect on the predicted probabilities, especially in the public market
as predicted by Hypothesis AG2.
If we increase our risk and investment opportunity measures by one
standard deviation, the predicted probability of issuing public debt declines by 7.4 as risk increases one
standard deviation and declines by 14 percentage points as Tobin's q increases one standard deviation.
Market timing, measured by the cumulative abnormal stock return, also has a large e ect on market
choice and security issuance in the public market but less so in the private market. The rst two columns
of Table 7 show that rms are 8.9 percentage points more likely to issue in the public markets (and 8.9
percentage points less likely to issue in the private markets) after a one standard deviation increase in
the rm's cumulative abnormal stock return.
The e ect is magni ed in the public markets for public
18
equity.
Public equity is an additional 3.7 percentage points more likely to be issued versus a decline
of 5.4 percentage points for public debt after a one standard deviation increase in the rm's cumulative
abnormal stock return. This relation is weaker in the private market, with a 1.9 percentage point increase
for private equity and 1.3 percentage point decline for private debt. Thus the overall e ect is that public
equity is more that 10 percentage points more likely to be issued after a one standard deviation increase
in the rm's cumulative abnormal stock return.
Trade-o variables (debt, taxes and pro tability) have a signi cant economic impact in both public
and private security markets. We see a fairly large e ect of these variables on the probability of security
issuance in the private market with increases in pro tability and the marginal tax rate and decreases in
nancial distress making rms more likely to issue private debt.
Finally, corporate governance has a limited economic impact on security issuance. These results are
consistent with the view that managers have discretion over security and market choice decisions are not
likely to choose debt or a private monitor in order to improve corporate governance.18
Empirically, Hertzel and Smith (1993) and Wu (2004) do not nd evidence that private placements
are motivated by monitoring. Recently, Barclay, Holderness and Sheehan (2003) examine long-run equity
returns following private placements and nd evidence consistent with the conclusion that discounts to
private equity are compensation to private blockholders for passively allowing management to become more
entrenched. Our interpretation of the current theory and evidence is that the predictions for security and
market issuance are mixed depending on whether managers with poor current governance have discretion
over the security-market choices.
The overall message that emerges from these tables is that e ect of asymmetric information and market
timing is quite di erent in the public and private markets.
The results reinforce the conclusion that in
order to gauge the e ect of information on security issuance decisions, it is crucial that one does not
combine private and public security issues.
Table 8 contains measures of goodness of t measures for our model. It shows how well the nested
logit model from Table 6 does in predicting the actual observed security choice.
The table contains the
observed security choice in the rows and the predicted choice in each column. For each observation, the
predicted security choice is the choice with maximum probability among the six choices using the coe cient
estimates from Table 6.
The rst row of each cell gives the number predicted to choose the security given
in the column header. The second row gives the percentage predicted to choose that security versus the
actual security choice. The third row gives the percentage of observed, predicted pairs divided by the
overall number predicted to issue that security.
Insert Table 8 here
18
The leverage decisions and the use of debt or monitoring itself may be plagued by agency con icts. The more antitakeover
defenses the rm has the lower can the debt level and the lower the probability of issuing debt securities as modeled by Zwiebel
(1996) and Novaes (2002). Similar considerations are likely also to impact the likelihood of using a monitor.
19
Table 8 shows that the model from Table 6 does very well in predicting security issues for most securities.
The model does very well in predicting public debt (61 percent predicted correctly), private debt (78
percent predicted correctly) and private equity (53 percent predicted correctly). Perhaps not surprisingly
the model does less well in predicting convertible securities as they are a blend of equity and debt.
4.5 Alternative Measures of Asymmetric Information
As discussed earlier, we also examine our results using alternative measures of asymmetric information.
Table 9A presents results from reestimating the nested logit model of Table 6 with di erent measures
of asymmetric information.
In this table, we just present the coe cient estimates on the alternative
measures of asymmetric information, and do not report the coe cient estimates on the other variables, as
the results were very similar to those of Table 6.
Insert Table 9A here
Comparing the results with the di erent measures of asymmetric information to the results of Table 6,
we see that the qualitative results are similar to those of Table 6. For three of the four measures of asymmetric information, the coe cient on private market choice versus public market in column 1 is positive
and signi cant. The one case where this coe cient on the private versus public choice is insigni cant is
for the volume and return based measure (one that ex ante we consider a worse measure of asymmetric
information as it is also a possible proxy for liquidity).
Examining the coe cients for security choice
conditional on market in columns 2 through 5, we see that the coe cient in column 2 for public equity is
negative and signi cant for all measures of asymmetric information. This result reinforces the conclusion
that probability of issuing public equity versus public debt declines with asymmetric information as predicted by Hypothesis ASY1. For analyst earnings dispersion we also nd positive signi cant coe cients for
private equity and convertibles, indicating that rms probability of issuing equity-type securities increases
with asymmetric information.
However the results within the private market are generally not signi cant
for the other three measures of asymmetric information (with the exception of private convertibles for the
abnormal stock return to earnings announcements). These results are again consistent with asymmetric
information playing a limited role in security issuance in the private markets but a large role in the public
markets.
Table 9B presents the economic signi cance of these results. First we see that the probability of issuing
public equity (public debt) decreases (increases) with all 4 measures of asymmetric information.
Thus
our conclusion is that the result of decreased probability of issuing informationally sensitivity securities
in public markets as asymmetric information increases is very robust. Examining columns 4 through 6,
we also note that the sensitivity of security issuance to asymmetric information in the private markets
is generally at with low (analyst earnings dispersion) or no sensitivity to the measures of asymmetric
information. Thus we conclude that asymmetric information impacts security choice in the public market
and also impacts choice of public versus private markets but does not have a large impact on security
20
choice within private markets. The results in private markets are consistent with these investors having
su cient information or rms sharing information to private investors.
4.6 Graphical Presentation of our Results
Graphical presentation of our results allows us to more systematically show the impact of asymmetric
information and risk on security choice. We show how rms in di erent size classes (Figure 1) and rms
issuing each of the six di erent types of securities (Figure 2) are predicted to change their issuance behavior
as we vary our two primary variables, asymmetric information and risk. We plot the issuance choice with
the maximum probability (recall that there is a predicted probability for each of the six securities for each
observation, not just for the security actually issued).
Figure 1 shows the predicted probability of security issuance using the coe cient estimates from our
model in Table 6.
We present graphs for
rms of di erent sizes, given the importance of size in the
model. We construct three di erent size groups, small, below the 33rd percentile, medium, between the
33rd and 66th percentile and large, above the 66th percentile. We plot the predicted security issued (that
security that has the maximum probability of issuance) as we move our asymmetric information and risk
variables plus and minus ten standard deviations away from their size-based mean values, keeping all other
variables at their mean values for each size group.
Risk (volatility of cash ows) is on the y-axis and
asymmetric information (earnings surprise relative to analyst forecasts) is on the x-axis. PuE (PrE) is
public (private) equity, PuC (PrC) is public (private) convertibles, PuD (PrD) is public (private) Debt.
Dark (light) shading within regions represent the fact that the security predicted to be issued has predicted
probability greater than 50 percent (between 0-50 percent higher) than the next highest security.
The graphical presentation of our results adds information to the previous economic e ects shown as
the logistic distribution has an S-shape and the marginal e ects can be mostly concentrated on the tails of
the distribution with sharp increases around the cut-o levels. Thus the average marginal e ects of Table
7 may be underestimating the extent of the impact of changes on rm characteristics on the nancing
choices.
Insert Figure 1 here
Figure 1 clearly shows that as asymmetric information increases rms are more likely to issue privately.
Small rms with both high risk and asymmetric information are more likely to issue private equity and
convertibles.
Medium size
rms are more likely to issue private debt for high levels of asymmetric
information and low levels of risk, and more likely to issue private convertibles for both high levels of
asymmetric information and risk. As shown in the graphs for medium and large rms,
rms with the
highest degree of asymmetric information and low risk are more likely to issue public debt. However,
as risk increases, the security choice is more nuanced.
Firms with the median level of risk but high
asymmetric information are likely to issue private debt while
rms with the highest levels of risk and
asymmetric information issue private convertibles for all three size classes.
21
In Figure 2 we present graphs of the predicted probability of security issuance for rms that actually
issued each one of the six securities. For example, in the last of the six graphs in this gure, we take all rms
that issue private equity and then examine how their predicted choice changes as we vary our asymmetric
information and risk variables plus and minus ten standard deviations away from their security-based mean
values, keeping all other variables at the mean values for private equity.
Insert Figure 2 here
Inspection of the graphs in Figure 2 reveal that predicted probability of security issuances are markedly
di erent as risk and asymmetric information varies - for each set of rms issuing di erent types of securities.
Considering the
rst graph for public debt issuers, we can see that the model predicts public
debt fairly accurately with public debt predicted to be issued at the means of the data. However, as we
move risk and asymmetric information away from their mean values, we get public equity predicted to
be chosen for low earnings surprise (asymmetric information) and private debt predicted to be chosen for
high earnings surprise, consistent with informationally sensitive securities likelihood of issuance decreasing
with asymmetric information. Private convertibles are predicted to be chosen for high levels of risk and
asymmetric information. Examining the graphs in the middle (graphs 2 and 5) for both public and private
convertibles, we can see that the model in Table 6 does not predict these securities very well, as at the
mean levels of the variables (the middle of each graph) private debt is predicted to be issued for rms
issuing public convertibles and private equity is predicted to be issued by rms actually issuing private
convertibles. Examining the fourth and sixth graphs, we can see that the model does very well predicting
private debt and private equity. What also is especially interesting is that rms that issue private equity
and convertibles are rarely predicted to issue debt securities. For high levels of our asymmetric information
variable, private equity issuers are predicted to issue private equity and private convertibles.
Overall, it is clear from all graphs in Figure 2 that rms with both high asymmetric information and
high risk issue private convertibles and private equity.
Firms with lower risk but still high asymmetric
information issue private debt. Firms with high risk but low asymmetric information are more likely to
issue public equity. All of the six graphs quite clearly show that rms likelihood of issuing public equity
decreases as asymmetric information increases.
G. The Timing of Private and Public Security Issues Relative to Earnings Releases
We examine if security issues are clustered symmetrically before and after earnings announcements for
private as well as public issues. To investigate this hypothesis, we generalize the analysis in Korajczyk
et al. (1991) for public equity to all six security-market combinations of our paper. In order to facilitate
comparison with Korajczyk et al. (1991) we perform tests similar to their Table 3. The null hypothesis
is that security-market issues are equally likely to precede earnings announcements as they are to follow
earnings announcements. The variable of interest is de ned as the number of days between an issue and
the closest earnings release. This variable is positive (negative) if the preceding earnings release is closer
22
to (farther from) the security issue than the subsequent release. A positive (negative) statistic in Table 10
indicates that the security issues are more likely to follow (precede) earnings releases. In Panel A of Table
10 we perform the test separately for all six security-market combinations and also test whether timing
decisions are di erent in private than in the public market. Panel B contains a test that timing decisions
are similar across securities within a given market.
Insert Table 10 here
The results in Panel A of Table 10 show that the Korajczyk et al. result for public equity also holds
for public convertibles and public debt. All public issues seem to more closely follow an earnings release
than to precede it. These results are strong for all quarters combined and for the annual earnings reports.
However, we nd di erent results for private equity markets.
There is no signi cant relation between
the date of the security issue and the date of the earnings report. We cannot reject the hypothesis that
the timing of the private security issues are symmetrically distributed around the date of the earnings
releases.
Moreover, the hypothesis that the timing of issues in the public and private markets have
the same distribution is signi cantly rejected in the last column of Panel A (Mann-Whitney two-sample
statistics tests) in 12 of the 18 di erent speci cations - and at the one-percent level for all quarters combined
for all security types (z-values of 3.45, 3.49, and 3.40).
In Panel B of Table 10 we examine whether the timing distribution for di erent securities within
markets is similar. Panel B reports the Mann-Whitney two-sample statistics for tests of similar samples.
The hypothesis that any security-choice pair, for a given market, has the same distribution is not rejected
except for public equity and public debt in 5 cases and in only two cases at the ten-percent level for private
equity versus private debt. Firms seems to be timing public equity issues more than public debt securities
but all other securities in a given market seem to have issue dates that are distributed similarly around
their earnings release dates.
The overall results con rm our earlier security choice analysis of Table 6 that rms time public security
issues but that there is limited or no evidence that rms time their private market issues of securities.
5
Robustness of Results
As discussed earlier in Section 4.5, our results are robust to alternative measures of asymmetric information.
In this section, we discuss further robustness tests we performed.
5.1 Rule 144-A Market
We examine the robustness of results to the categorization of 144-A debt and convertible issues as
public securities and create additional categories for these types of securities.
In Table 11, we expand
the number of markets to estimate separate coe cients for Rule 144-A debt and convertibles issues. We
23
present these results for the earnings surprise measure of asymmetric information - similar results hold for
analyst earnings estimate dispersion as well.
Insert Table 11
The results in Table 11 for previous security categories are overall very similar to those presented in
Table 6. The results for 144-A securities in Column 2 show that the coe cient on analyst earnings surprise
is positive. This result is consistent with the previous explanation that rms probability of choosing to issue
in the private market - including the 144-A market - increases with measures of asymmetric information.
Other results of interest include the positive coe cient on predicted nancial need - rms whose need for
funds increase have an increased probability of issuing in this market. This result is perhaps not surprising
given that average issue size is large in this market. The results also show that rms whose stock price
performance has been positive prior to issue are less likely to issue in this market - consistent with the
previous market timing results where rms with positive stock price performance are more likely to issue
public equity. Lastly, the nal column of this table shows that there are not many signi cant di erences
in factors that impact the decision to issue 144-A convertibles and 144-A straight debt securities.
5.2 Floating and Fixed Rate Convertibles
Chaplinsky and Haushalter (2003) and Brophy et al. (2004) also examine separately price-protected or
oating rate convertibles from traditional private securities without price-protection conversion features.
Price-protected security issues provide investors with additional securities if the stock price decreases after
the closing. In oating rate issues, the conversion price is reduced and investors receive more common
shares upon conversion, while in the traditional or
xed rate convertibles the conversion rate is
xed.
They nd the excess returns to these price-protected issues are negative.
All results reported in the paper include both oating and xed rate convertibles. For robustness we
thus perform all tests excluding oating rate convertible issues.
Compustat and CRSP there were 487 oating rate issues.
In the sample of rms we matched to
Of the nal sample in our regression tables
there were 175 issues out of 8,346 total issues. When dropping these 175 issues, the key results on the
security and market choice do not change signi cantly.19 The market reaction result (Table 3) does change
(and gives stronger support of our Hypothesis ASY 2) when we exclude oating rate convertibles from the
sample: the reaction to xed rate convertible issues is now positive and signi cant at the 1% level, but
the coe cients for other variables do not signi cantly change. This result is consistent with the ndings
of Chaplinsky and Haushalter (2003) and Brophy et al. (2004), which indicate that the market reaction
to announcements of oating ( xed) rate or price protected issues is negative (positive).
19
The reason that there are only 175 issues of these types of securities is that issuers of price-protected securities are smaller
and frequently do not have analyst coverage. For conciseness we do not report those results but they are available from the
authors upon request.
24
5.3 Other Robustness Checks
The most common type of private debt is revolving credit lines followed by term loans (respectively,
78% and 18%). It may be argued that the revolving credit lines do not represent actual loans given that
the rm does not have to borrow under these lines. Thus, we also examine the robustness of our results
to the exclusion of revolving credit lines. After excluding revolving credit lines from our nal sample, we
are left with 5,722 issues out of 8,346 originally. Our results do not change signi cantly when we exclude
revolving credit lines from the analysis.
6
Conclusions
In this paper we analyze public and private security issuance decisions by public companies.
Using
a comprehensive database of public and private security issues we examine the impact of asymmetric
information and agency problems on security issuance decisions. We show that private equity issues are
signi cant in number, especially for smaller rms that potentially have more asymmetric information and
higher risk.
Our results show that private equity and private convertible issues are a substantial fraction
of equity and convertibles issued by public companies. Private equity and convertibles issued by public
rms comprise 58 percent of their equity and convertibles issues. In addition, 81% of small public rms
( rms in the lowest size quartile) issuing equity and convertibles choose to issue privately.
We analyze the factors that are related to the probability of a rm issuing public and private securities.
We have three main results on security issuance decisions:
1. Asymmetric information a ects rm issuance decisions di erently in the public and private markets.
Conditional upon issuing in the public market, we nd support for a probability ordering of security
issuance:
the predicted probability of issuing equity declines with asymmetric information, while
it increases for public debt.
However, conditional on issuing in the private security market, we
nd a partial reversal of this ordering:
rms' predicted probability of issuing debt decreases with
measures of asymmetric information and increases slightly for convertibles and equity. When we do
not distinguish between the market in which securities are sold, we nd no evidence that asymmetric
information is important to security issuance.
2. Our results on market timing indicate that the sensitivity of security issuance in the private market
to a rm's stock return in the past year is much lower than the sensitivity in the public market. We
also show that security issuance in the public but not in the private security market more closely
follows earnings reports. These results are consistent with limited market timing of security issuance
to private investors as they are likely to have more information about rm prospects or better access
to information than public investors.
3. We nd that rms' likelihood of issuing equity and convertibles increases with risk and Tobin's q
25
in both public and private markets. However, this sensitivity is signi cantly stronger in the public
security market than in the private security market - consistent with agency problems being mitigated
when securities are sold to private investors.
Our results establish that private markets are quite di erent from public markets on many di erent
dimensions. In particular, the sensitivity of security issuance by public rms to asymmetric information is
fundamentally di erent in public and private markets. Economic signi cance of the results indicates that
asymmetric information is one of the most signi cant and economically important factors that in uences
security issuance decisions in the public but not in the private security market. The results are consistent with several explanations that emphasize the di erences between public and private investors. The
explanations include private issues being sold to investors with better ability to evaluate rm prospects
or stronger incentives for information production, and with private investors being better able to mitigate
agency problems than public investors.
The results indicate that multiple factors drive security issuance choice and securities are issued in
di erent markets to solve multiple problems. The results also point to a potentially important unexplored
dimension of capital structure - the public-private funding ratio in addition to the debt-equity ratio.
26
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Table 1
Number and Gross Proceeds of Securities Issued by Year
Table 1 shows the number of issues, the total gross proceeds raised in millions of dollars, and the mean amount raised as a percent of
firm value (%FV) for each year and security-market choice. We obtain our information on all public issues and 144-A debt issues from
SDC, on private debt from DealScan, and on private equity and convertibles and 144-A convertibles from PlacementTracker. We
include securities if the issuing company is matched to Compustat and CSRP. We exclude financials and regulated utilities.
Year
1995
N
$MM
%FV
Debt
210
38,735
8%
Public
Convertibles
25
3,277
27%
Equity
217
13,791
24%
Debt
46
6,328
36%
1996
N
$MM
%FV
233
53,354
10%
32
6,053
19%
274
16,943
26%
71
11,643
45%
1997
N
$MM
%FV
224
59,355
8%
26
3,792
21%
224
14,011
24%
1998
N
$MM
%FV
289
89,008
6%
18
4,496
11%
1999
N
$MM
%FV
184
69,356
8%
2000
N
$MM
%FV
2001
144-A
Convertibles
21
2,480
18%
Debt
500
154,573
33%
Private
Convertibles
30
456
17%
Equity
50
656
13%
Total
1,099
220,295
25%
41
5,397
25%
659
198,719
32%
108
1,660
21%
64
628
16%
1,482
294,398
26%
186
37,009
32%
69
11,433
26%
729
246,692
32%
155
2,560
13%
66
1,135
13%
1,679
375,987
25%
146
14,509
20%
181
49,079
31%
46
10,776
15%
640
142,502
37%
130
1,020
14%
78
664
11%
1,528
312,054
24%
21
11,265
9%
173
22,442
22%
118
46,908
22%
36
9,808
15%
603
131,333
37%
148
4,534
16%
170
2,211
14%
1,453
297,855
25%
139
58,039
4%
22
11,723
11%
174
30,893
24%
40
32,320
19%
64
20,287
14%
602
172,311
34%
178
9,690
15%
221
7,121
13%
1,440
342,383
23%
N
$MM
%FV
191
104,940
5%
29
13,557
7%
136
16,434
14%
140
69,197
19%
91
39,370
11%
619
146,627
31%
154
3,873
16%
250
5,878
14%
1,610
399,875
20%
2002
N
$MM
%FV
190
82,772
4%
11
8,030
6%
129
16,256
11%
88
24,446
20%
50
17,299
10%
613
145,998
29%
136
4,320
12%
209
3,012
11%
1,426
302,134
18%
2003
N
$MM
%FV
160
80,685
5%
17
10,165
7%
169
18,484
21%
147
44,040
19%
179
42,627
18%
644
154,405
29%
117
2,574
19%
269
4,296
20%
1,702
357,275
22%
1,820
636,245
7%
3%
201
72,357
14%
9%
1,642
163,762
22%
15%
1,017
320,968
27%
16%
597
159,477
17%
13%
5,609
1,493,159
33%
22%
1,156
30,686
15%
9%
1,377
25,601
15%
9%
13,419
2,902,255
23%
13%
N
$MM
%FV
%FV (med)
Total
Table 2
Security Issuance by Size Quartiles
Table 2 shows the number of issues and the percentage of issues by size category. Size categories are quartiles
based on lagged assets. The percentage of issues of security type is the number of issues of a particular security
type for a size quartile divided by total issues of that same type. The percentage of issues of total issues is the
number of security issues of a particular type for a size quartile divided by total number of issues. The percentage
issues of Private divided by Public plus Private is the number of private security issues of a particular security type
divided by the public and private issues of that same security type for a given size quartile.
Size Quartiles (by lagged assets)
Debt
Public
Convertibles
Equity
144-A
Debt
Convertibles
Debt
Private
Convertibles
Equity
Smallest Firms
Number of issues
11
18
% of issues of security type
0.60%
8.96%
% of issues of total issues
0.08%
0.13%
% Issues Private /(Public + Private in size quartile)
564
34.35%
4.20%
51
5.01%
0.38%
44
7.37%
0.33%
938
16.72%
6.99%
98.84%
784
67.82%
5.84%
97.76%
945
68.63%
7.04%
62.62%
Second Size Quartile
Number of issues
42
36
% of issues of security type
2.31%
17.91%
% of issues of total issues
0.31%
0.27%
% Issues Private /(Public + Private in size quartile)
574
34.96%
4.28%
211
20.75%
1.57%
152
25.46%
1.13%
1,773
31.61%
13.21%
97.69%
257
22.23%
1.92%
87.71%
310
22.51%
2.31%
35.07%
Third Size Quartile
Number of issues
295
56
% of issues of security type
16.21%
27.86%
% of issues of total issues
2.20%
0.42%
% Issues Private /(Public + Private in size quartile)
369
22.47%
2.75%
412
40.51%
3.07%
225
37.69%
1.68%
1,819
32.43%
13.56%
86.05%
92
7.96%
0.69%
62.16%
87
6.32%
0.65%
19.08%
Largest Firms
Number of issues
1,472
91
% of issues of security type
80.88%
45.27%
% of issues of total issues
10.97%
0.68%
% Issues Private /(Public + Private in size quartile)
135
8.22%
1.01%
343
33.73%
2.56%
176
29.48%
1.31%
1,079
19.24%
8.04%
42.30%
23
1.99%
0.17%
20.18%
35
2.54%
0.26%
20.59%
Total Issues
1,642
1,017
597
5,609
1,156
1,377
1,820
201
Table 3: Summary Statistics
Panel A of this table shows summary statistics by security-market choice in the year prior to the issue. Panel B tests for differences across and within markets. Analyst earnings
surprise is the absolute value of actual earnings less median analyst forecast divided the price per share. Analyst earnings dispersion is the standard deviation of analyst earnings
estimates divided the price per share. We scale corporate governance, where one equals worst and four equals best, based on whether the firm has dual-class voting stock,
classified board, restrictions on shareholders to call special meeting, or on action by written consent. We divide R&D by lagged property, plant, and equipment. Cash flow volatility
is the standard deviation of operating cash flow using up to 20 quarters prior to the issue. Profitability is operating income before depreciation divided by lagged assets. Financial
distress is Altman's Z-score less than 1.81. Tobin's q is market-to-book value. Cumulative abnormal return (CAR) is the excess return relative to a portfolio of firms in the same
size decile. Debt-to-asset ratio is long-term debt divided by book value of assets. The corporate marginal tax rate is from Graham (1996). Firm value is market value of equity plus bo
Security/Market
Public
Debt
Analyst
Earnings
Surprise
Analyst
Cash flow
Earnings
Volatility
Dispersion
Panel A: Summary Statistics by Security-Market Choice
R&D / Tobin's q Debt/Asset
Marginal
Profitability
lagged
ratio
Tax Rate (%) (OCF/ lagged
PPE
assets)
Financial
Distress
Cumulative Corporate Firm Value
Ab. Return Governance ($ Millions)
prior 250 days
Mean
Med
Stdev
N
0.7%
0.3%
1.9%
1,756
1.2%
0.2%
5.3%
1,717
2.4%
1.9%
2.8%
1,820
13.3%
2.5%
29.5%
1,820
1.6
1.3
1.1
1,820
26.8%
25.2%
14.9%
1,820
25.1%
35.0%
14.5%
1,705
18.0%
17.4%
8.2%
1,820
10.1%
0.0%
30.2%
1,820
6.8%
1.4%
42.3%
1,820
3.3
3.0
1.2
1,712
24,561
7,841
45,161
1,820
Public
Mean
Convertibles Med
Stdev
N
1.8%
0.6%
4.5%
187
1.9%
0.4%
4.7%
180
4.2%
2.4%
5.5%
201
32.6%
0.0%
102.2%
201
2.0
1.4
2.0
201
27.5%
27.0%
17.4%
201
18.3%
17.7%
16.0%
180
12.6%
14.2%
18.9%
201
21.4%
0.0%
41.1%
201
43.4%
18.0%
101.4%
201
3.2
3.0
1.3
175
8,152
2,346
19,600
201
Mean
Med
Stdev
N
1.9%
0.6%
5.4%
1,491
1.1%
0.3%
3.3%
1,326
8.0%
4.5%
13.4%
1,642
110.4%
4.3%
233.5%
1,642
2.7
1.8
2.3
1,642
22.4%
17.6%
22.2%
1,642
18.1%
21.2%
16.1%
1,337
11.1%
16.0%
26.8%
1,642
13.1%
0.0%
33.7%
1,642
83.5%
44.7%
134.1%
1,642
3.4
3.0
1.2
1,167
1,449
367
5,358
1,642
144-A
Mean
Convertibles Med
Stdev
N
2.9%
0.7%
10.0%
930
2.0%
0.5%
5.9%
851
3.9%
2.5%
4.9%
1,017
12.9%
0.0%
44.1%
1,017
1.4
1.1
1.1
1,017
37.6%
35.8%
22.0%
1,017
17.9%
18.3%
15.8%
915
15.3%
14.6%
14.0%
1,017
30.9%
0.0%
46.2%
1,017
18.8%
4.0%
75.2%
1,017
3.2
3.0
1.2
814
5,340
1,162
17,638
1,017
Public
Equity
144-A
Debt
Mean
Med
Stdev
N
2.4%
0.5%
9.2%
571
1.7%
0.3%
4.7%
551
6.2%
3.7%
10.6%
597
100.6%
12.2%
216.9%
597
2.4
1.6
2.4
597
23.5%
20.3%
21.7%
597
15.1%
3.7%
15.8%
502
10.6%
12.2%
21.2%
597
17.8%
0.0%
38.2%
597
50.9%
17.5%
152.9%
597
3.5
3.0
1.2
524
4,258
1,255
9,413
597
Private
Debt
Mean
Med
Stdev
N
3.6%
0.7%
11.7%
4,784
1.7%
0.4%
5.4%
4,166
4.8%
3.1%
7.1%
5,609
29.5%
0.9%
89.8%
5,609
1.5
1.1
1.2
5,609
23.6%
20.7%
19.8%
5,609
20.5%
30.9%
15.6%
4,993
15.5%
15.1%
14.8%
5,609
14.0%
0.0%
34.7%
5,609
4.9%
-5.9%
66.5%
5,609
3.3
3.0
1.2
4,058
2,777
468
10,934
5,609
Private
Mean
Convertibles Med
Stdev
N
16.2%
5.6%
27.4%
638
5.8%
1.8%
10.5%
428
17.0%
11.5%
21.3%
1,156
161.9%
56.7%
255.0%
1,156
2.7
1.7
2.7
1,156
16.5%
7.5%
21.3%
1,156
4.5%
0.7%
10.0%
976
-22.0%
-17.3%
34.4%
1,156
32.9%
0.0%
47.0%
1,156
1.8%
-30.4%
131.4%
1,156
3.8
4.0
1.2
905
374
65
1,752
1,156
Private
Equity
Mean
Med
Stdev
N
13.4%
3.9%
24.8%
852
5.3%
1.5%
10.3%
574
17.6%
11.3%
22.6%
1,377
244.7%
111.6%
333.5%
1,377
3.0
2.1
2.8
1,377
12.3%
3.6%
18.6%
1,377
4.5%
0.8%
9.8%
1,162
-25.1%
-21.4%
35.8%
1,377
26.2%
0.0%
44.0%
1,377
24.5%
-10.6%
131.2%
1,377
3.8
4.0
1.2
1,168
486
79
3,234
1,377
Total
Mean
Med
Stdev
N
4.2%
0.7%
13.5%
11,209
1.9%
0.4%
6.0%
9,793
7.2%
3.5%
13.0%
13,419
72.7%
3.7%
187.2%
13,419
1.9
1.3
1.9
13,419
23.2%
20.0%
20.6%
13,419
17.5%
15.1%
16.1%
11,770
7.6%
13.6%
26.4%
13,419
17.8%
0.0%
38.3%
13,419
20.2%
0.9%
99.2%
13,419
3.4
3.0
1.2
10,523
5,468
520
20,590
13,419
Table 3 (Continued)
Panel B: Tests of Differences in Markets
The first row presents the t-statistics for the equality of means of each variable in Table 2A by market, and the second row presents the Mann-Whitney two-sample statistics.
Statistics for
difference in Market
Debt
Analyst
Earnings
Surprise
Analyst
Earnings
Dispersion
Private Debt
vs. Public Debt
10.3
22.0
a
Private Debt
vs. 144-A Debt
1.5
0.7
b
144-A Debt
vs. Public Debt
Convertibles
9.1
15.0
a
Private Convertibles
vs. Public Convertibles
7.1
14.3
a
Private Convertibles
vs. 144-A Convertibles
11.4
20.6
a
144-A Convertibles
Public Convertibles
Equity
0.9
-0.2
a
a
a
a
2.9
13.0
-1.7
-3.9
Cash flow
Volatility
a
14.0
25.2
a
a
4.2
7.5
a
a
9.8
11.1
a
8.4
16.7
a
11.6
21.1
a
2.6
5.5
a
3.5
12.4
a
4.9
9.0
a
8.3
13.6
a
-0.5
-0.8
R&D /
lagged
PPE
a
a
a
a
a
a
a
a
a
Private Equity
17.2 a
13.2 a
14.4 a
a
a
a
vs. Public Equity
23.7
17.4
23.8
a, b,c- represent significance levels of one, five, and ten percent.
Tobin's q
7.6
-2.0
a
5.8
5.5
a
-0.3
-6.9
b
-3.3
-8.6
Debt/
Assets
a
-6.4
-10.1
a
-20.4
-19.3
a
15.5
13.3
a
-6.9
-9.2
a
-6.5
-7.8
a
c
b
c
-2.3
-3.7
-13.4
-13.9
a
a
a
1.2
-0.1
-3.6
-6.4
a
a
3.2
3.1
a
2.3
1.8
b
7.1
9.8
a
5.0
6.2
a
4.3
6.1
a
13.0
18.1
a
a
a
a
a
1.8
2.1
3.9
2.1
Marginal Profitability
Tax Rate (OCF/lagged
assets)
a
a
a
a
a
a
a
a
a
a
a
-10.5
-11.1
a
4.6
4.2
a
-11.6
-10.7
a
-15.3
-11.3
a
-15.7
-14.9
a
-2.4
-1.7
b
-25.2
-21.3
a
a
a
a
a
a
c
a
-6.9
-9.3
a
a
-13.5
-13.3
a
14.4
13.9
a
3.3
3.2
a
6.8
6.7
a
a
c
-1.1
-1.1
-6.6
-8.0
a
-13.9
-15.8
a
-21.2
-21.5
a
-31.7
-30.7
Cumulative Corporate
Ab. Return Governance
prior 250 days
4.3
4.3
a
0.5
1.2
-1.2
-1.9
Financial
Distress
a
a
a
a
9.3
9.1
a
a
a
a
a
-1.1
-7.6
a
-6.0
-6.9
a
5.5
1.8
a
-4.3
-9.7
a
-7.0
-14.6
a
a
a
a
a
0.6
0.0
a
a
-12.2
-21.1
a
a
Firm Value
($ Millions)
2.3
1.8
b
2.6
2.7
a
c
a
-0.8
-1.3
5.8
5.7
a
4.9
4.8
a
2.4
2.7
b
7.8
7.6
a
a
a
a
a
-33.2
-49.2
a
-6.2
-16.9
a
-13.0
-27.3
a
-13.2
-18.9
a
-13.6
-29.7
a
-3.7
-3.2
a
-5.8
-26.6
a
a
a
a
a
a
a
Table 4
Market Reaction to Security Issuance
Table 4 presents a regression of ten trading-day cumulative abnormal returns around security issues on the variables
defined in Table 3. The analyst earnings surprise variable appears interacted with the public and private market dummy.
We normalize all explanatory variables (except the dummy variables) by their standard deviation. We include industry
fixed effects (Fama and French 17-industry categories) in all regressions. We denote t-statistics below the coefficients.
a,b,c - Significantly different from zero at the 1%, 5%, or 10% level of significance.
Equity Issues
(1)
(2)
Public Market
-1.62%
b
-2.54
Private Market
2.77%
2.16
b
Measures of Asymmetric Information
Analyst Earnings Surprise*Public Market
c
-2.31%
a
-2.53%
Debt Issues
(5)
(6)
a
-0.89%
b
-0.95%
-1.82
-2.65
-2.65
-1.97
-1.83
1.76%
1.29
-0.35%
-0.24
1.83%
1.14
-0.07%
-0.19
-0.02%
-0.06
-3.60%
-1.25
Analyst Earnings Surprise*Private Market
Risk Measure
Cash Flow Volatility
-1.60%
Convertible Issues
(3)
(4)
0.96%
1.80
-3.68%
-4.15
c
a
-0.22%
-0.20
-0.81%
-1.10
1.10%
1.25
0.06%
0.11
0.26%
0.50
-0.19%
-0.21
-0.68%
-0.69
0.65%
1.31
0.72%
1.32
0.49%
0.94
0.12%
0.20
0.81%
1.09
1.12%
1.25
-1.14%
-1.36
-1.11%
-1.25
-0.18%
-0.30
-0.27%
-0.48
0.57%
0.76
0.06%
0.08
-0.54%
-1.42
-0.48%
-1.22
-0.40%
-0.78
-0.59%
-1.19
-0.56%
-0.78
-1.65%
-2.26
0.31%
1.44
0.24%
1.07
Marginal Tax Rate
`
-0.55%
-0.91
-0.07%
-0.11
0.35%
0.46
-0.02%
-0.02
-0.11%
-0.58
-0.06%
-0.30
Profitability
(Operating cash flow/ lagged assets)
-0.40%
-0.60
-1.53%
-2.13
b
-0.55%
-0.60
-1.43%
-1.33
-0.31%
-0.61
-0.19%
-0.36
4.08%
1.63
1.09%
1.53
0.89%
1.30
Investment Opportunities Measures
R&D / lagged PPE
Tobin's q
Debt, Taxes and Profitability
Debt/Asset Ratio
(Industry Adjusted)
b
3.43%
1.90
c
2.98%
1.66
c
6.21%
2.90
Cumulative Ab. Stock Return
(250 prior days)
-1.69%
-3.66
a
-1.38%
-2.81
a
-0.79%
-1.05
0.70%
0.77
-2.36%
-6.50
a
-2.50%
-6.92
a
Cumulative Market Return
(Prior year)
Size and Corporate Governance
Corporate Governance
0.84%
1.20
0.77%
1.13
-1.10%
-1.63
-0.54%
-0.69
-0.41%
-1.97
b
-0.48%
-2.26
b
0.50%
0.87
0.16%
0.28
-0.07%
-0.10
0.07%
0.09
0.07%
0.38
0.01%
0.08
Log Size
(firm value)
-0.23%
-0.26
0.74%
0.90
-1.30%
-1.18
-0.90%
-0.77
0.12%
0.44
0.14%
0.50
Number of observations
F-value
2
Adjusted R
1,959
5.85
4.40%
Financial Distress
(Z-score < 1.81)
Market Timing
1,593
4.01
4.51%
1,374
2.47
2.74
a
c
1,102
2.94
3.38%
5,305
4.90
2.14%
4,981
4.65
2.70%
Table 5
Choice of Security: Debt versus Equity
Debt and Equity Aggregated Across Markets
Table 5 presents the coefficient estimates from binomial logit regressions that combine security issues into equity
and debt groups with no indication of choice of market or choice of convertible securities. The dependent variable
equals one for equity issues and zero for debt issues. All firm-specific variables are lagged. All market-specific
variables represent three months prior to the security issuance. For the measure of asymmetric information, column
1 uses the analyst earnings forecast surprise calculated as the absolute value of the median forecast less the actual
earnings divided by the price per share. Column 2 uses analyst earnings dispersion calculated as the standard
deviation of the analyst forecasts divided by price per share. Predicted financial need (internal funding deficit) is the
instrumented amount of capital expenditures plus increase in net working capital less operating income before
depreciation. All other explanatory variables are as defined in Table 3. We normalize all variables (except the
dummy variable for financial distress) by their standard deviation. The table includes industry fixed effects (Fama-F
Explanatory Variables
Measures of Asymmetric Information
Risk Measure
Cash Flow Volatility
Analyst
Earnings
Surprise
0.001
(.050)
Analyst
Earnings
Dispersion
-0.028
(-.840)
0.130 a
(2.510)
0.183 a
(2.870)
0.108 b
(2.380)
0.093 c
(1.870)
0.384 a
(7.830)
0.359 a
(6.910)
0.091 a
(2.550)
0.109 a
(2.810)
Marginal Tax Rate
-0.153 a
(-3.710)
-0.126 a
(-2.900)
Profitability
(Operating cash flow/ lagged assets)
-0.361
(-6.860)
a
-0.372 a
(-6.170)
0.219 b
(2.140)
0.225 b
(2.030)
Investment Opportunities Measures
R&D / lagged PPE
Tobin's q
Debt, Taxes and Profitability
Debt/Asset Ratio
(Industry Adjusted)
Financial Distress
(Z-score < 1.81)
Size and Corporate Governance
Predicted Financial Need
0.106
(1.350)
0.079
(.880)
Log Firm Size
(firm value)
7.250 a
(.000)
6.710
(.000)
Corporate Governance
0.026
(.760)
0.016
(.460)
Market Timing & Market Characteristics
Cumulative Abnormal Stock Return
(250 prior days)
a
0.288
(7.250)
a
0.301
(6.710)
Cumulative Market Return
(Prior year)
0.093
(2.780)
a
0.047
(1.250)
Aaa Bond Rate
0.187
(4.880)
a
0.234
(5.620)
Credit Spread: Baa - Aaa
0.204
(4.910)
a
0.212 a
(4.720)
Number of issues
Pseudo R-squared
8,346
27.7%
a,b,c - Significantly different from zero at the one-percent (five, ten) level of significance.
7,536
25.6%
a
a
Table 6
Security Choice Conditional on Public versus Private Markets
Table 6 presents coefficient estimates from a nested logit regression that tests the impact of explanatory variables on
public and private security choice by public firms. Column 1 presents market choice coefficients representing sensitivity
relative to the public market. Columns 2 through 5 present security choice conditional on market, with coefficients
representing sensitivity versus debt issuance. All firm-specific variables are lagged. Explanatory variables are as defined
in Table 2A. We normalize the explanatory variables (except for the dummy variable financial distress) by their standard
deviation. Analyst earnings surprise is the absolute value of actual earnings less median analyst forecast divided the price
per share. Predicted financial need (internal funding deficit) is the instrumented amount of capital expenditures plus
increase in net working capital less operating income before depreciation. The chi-squared statistic for test of overall
significance is 11693 (p-value 0.001). Our sample comprises 8,346 security issues. The table includes industry fixed
effects for each security type. Robust Z-statistics appear in parentheses.
Explanatory Variables
Asymmetric Information Measure
Analyst Earnings Surprise
Market Choice
Private
(vs. Public
Market)
0.215 a
(3.480)
Risk Measure
Cash Flow Volatility
Investment Opportunities
R&D / lagged PPE
Tobin's q
Debt, Taxes and Profitability
Debt/Asset Ratio
(Industry Adjusted)
Security Choice Conditional on Market
Public
Public
Private
Private
Equity
Convertibles
Equity
Convertibles
(vs. Public Debt)
(vs. Private Debt)
a
c
a
-0.773
-0.026
0.082
0.118
(-4.730)
(-.280)
(1.940)
(2.880)
0.206
(1.730)
c
0.538
(4.600)
a
0.441
(3.530)
a
0.308
(4.300)
a
0.334
(4.590)
a
0.360
(2.070)
b
0.725
(4.630)
a
0.736
(4.640)
a
0.230
(3.590)
a
0.141
(2.060)
b
0.491
(4.690)
a
0.997 a
(11.690)
-0.052
(-1.470)
0.134
(2.680)
0.023
(.660)
0.001
(.020)
Profitability
(Operating cash flow/ lagged assets)
-0.145
(-1.490)
-0.632
(-6.300)
Financial Distress
(Z-score<1.81)
-0.431
(-4.250)
Marginal Tax Rate
Size and Corporate Governance
Predicted Financial Need
Log Size
(Firm Value)
Corporate Governance
a
0.003
(.050)
-1.397
(-14.750)
a
-0.222
(-1.440)
0.234
(2.390)
a
a
0.875 a
(10.190)
-0.014
(-.270)
0.113
(1.940)
-0.142
(-2.430)
b
-0.769
(-7.320)
a
-0.083
(-.520)
b
-1.778 a
(-20.300)
0.184
(3.820)
a
-0.497 a
(-6.590)
c
-0.434 a
(-5.360)
0.634 a
(8.970)
0.179
(2.970)
-0.958
(-11.770)
a
-0.827
(-9.930)
a
0.413
(2.560)
a
0.563
(3.430)
a
-0.800
(-5.130)
a
-0.436
(-1.480)
-1.402 a
(-13.430)
-1.489 a
(-13.530)
0.143 a
(2.560)
0.082
(1.390)
0.328 a
(5.450)
0.305 a
(5.200)
0.041
(.580)
0.142
(2.520)
a
-0.021
(-.350)
0.174
(2.560)
a
0.227
(3.010)
0.007
(.140)
Market Timing & Market Characteristics
Cumulative Abnormal Stock Return
(250 prior days)
-0.333 a
(-5.930)
0.387 a
(6.720)
Cumulative Market Return
(Prior year)
-0.073
(-1.950)
c
0.102
(1.940)
c
0.028
(.480)
Aaa Bond Rate
0.298
(7.250)
a
0.364
(5.970)
a
-0.140
(-2.240)
Credit Spread: Baa - Aaa
0.318 a
(6.920)
b
0.169 b
(2.340)
a,b,c - Significantly different from zero at the one-percent (five, ten) level of significance.
a
-0.381 a
(-4.640)
0.067
(1.300)
0.030
(.910)
0.383 a
(5.590)
0.656 a
(9.650)
0.500 a
(7.200)
a
0.144 c
(1.880)
Table 7
Economic Significance: Changes in Predicted Probability of Security Issuance
Table 7 illustrates the economic significance of our results using the coefficients from the nested logit model of Table 7. We vary
each specific variable by +/- 1/2 of its standard deviation, and evaluate the change in each predicted probability of security
issuance, keeping all other variables fixed at their actual observation values. For the asymmetric information and risk variables,
we also compute these predicted marginal effects for firms above and below the median market value of all firms issuing
securities in our sample.
Prob. of Issuing in:
Conditional on Public Market
Conditional on Private Market
Public
Private
Probability of Issuing
Probability of Issuing
Market Market
Debt
Convertibles Equity
Debt Convertibles Equity
Asymmetric Information Measure
Analyst Earnings Surprise: all firms
-8.8%
8.8%
6.8%
4.2%
-11.0%
-0.6%
0.5%
0.1%
firms <= median market value
-10.8%
10.8%
8.2%
6.7%
-14.9%
-0.9%
0.9%
0.1%
firms > median market value
Risk Measure
Cash Flow Volatility: all firms
-6.8%
6.8%
5.3%
1.8%
-7.1%
-0.3%
0.2%
0.1%
-0.5%
0.5%
-7.4%
2.2%
5.2%
-2.3%
1.2%
1.1%
firms <= median market value
0.8%
-0.8%
-7.5%
1.0%
6.6%
-3.4%
1.8%
1.6%
firms > median market value
Investment Opportunities
R&D / lagged PPE
-1.9%
1.9%
-7.2%
3.4%
3.8%
-1.2%
0.5%
0.7%
-1.2%
1.2%
-10.8%
4.7%
6.1%
-1.3%
0.2%
1.1%
-3.1%
3.1%
-14.0%
4.8%
9.2%
-4.6%
2.0%
2.6%
1.3%
-1.3%
-1.1%
-1.0%
2.0%
-1.0%
0.8%
0.3%
0.3%
-0.3%
0.9%
-1.7%
0.9%
2.9%
-1.1%
-1.8%
-0.5%
0.5%
10.2%
-5.7%
-4.6%
6.4%
-2.3%
-4.1%
5.4%
-5.4%
0.4%
0.3%
-2.7%
-3.6%
2.4%
1.2%
8.9%
-8.9%
-5.4%
1.7%
3.7%
-1.3%
-0.6%
1.9%
-0.7%
0.7%
-0.5%
0.8%
-0.3%
-0.8%
0.1%
0.7%
Tobin's q
Debt, Taxes and Profitability
Debt/Asset Ratio
Marginal Tax Rate
Profitability
Financial Distress
Market Timing & Corporate Governance
Cumulative Abnormal Stock Return
Corporate Governance
Table 8: Goodness of Fit
Predicted versus Actual Choices
For each choice made by firms, this table shows the predicted choices made using the model and coefficients
of Table 6. The predicted choice is the maximum probability over the six possible choices in Table 6. For
each type of security issued, the first row gives the number predicted to choose the security given in the
column header. The second row gives the percentage predicted to choose that security versus the actual
choice. The third row gives the percentage of observed, predicted pairs divided by the overall number
predicted to issue that security.
Predicted Choice
Observed
Public
Public
Public
Private
Private
Private
Observed
Choice
Debt Convertibles Equity
Debt
Convertibles
Equity
Count
Public Debt
1,382
61%
62%
17
1%
15%
24
1%
5%
840
37%
18%
1
0%
0%
2
0%
0%
2,266
Public Convertibles
155
27%
7%
37
6%
33%
70
12%
16%
305
52%
7%
0
0%
0%
16
3%
2%
583
Public Equity
83
9%
4%
21
2%
19%
211
23%
48%
528
57%
11%
7
1%
3%
78
8%
12%
928
Private Debt
589
17%
26%
23
1%
21%
74
2%
17%
2,621
78%
57%
32
1%
13%
43
1%
6%
3,382
Private Convertibles
11
2%
0%
5
1%
4%
23
4%
5%
170
33%
4%
129
25%
51%
180
35%
27%
518
Private Equity
17
3%
1%
9
1%
8%
38
6%
9%
166
25%
4%
85
13%
33%
354
53%
53%
669
2,237
112
440
4,630
254
673
8,346
Predicted Count
Predicted Market
Observed
Observed Market
Public
Private
Security
Public
2,000
72%
1,777
32%
Debt
Private
789
17%
28%
3,780
83%
68%
Predicted Security
Debt
Convertibles
Equity
5,432
79%
73
20%
143
13%
Convertible
641
58%
9%
171
16%
47%
289
26%
26%
Equity
794
50%
12%
122
8%
33%
681
43%
61%
Table 9A: Alternative Measures of Asymmetric Information
Table 9A presents the coefficient estimates using different measures of asymmetric information using
the same specification as Table 6. The variables used for other variables are the same as Table 6. We
replace the asymmetric information variable with the alternative measure indicated. We do not present
the coefficient estimates from other variables. Analyst earnings dispersion is the standard deviation of
outstanding earnings forecasts normalized by the stock price for the quarter prior to the security
issuance. We calculate insider trading prior to security issuance as the number of buys less the number
of sells in the past year divided by shares outstanding. Abnormal stock return to lagged earnings
announcements is the abnormal stock return using a market model averaged over the past four quarterly
earnings announcements. The volume and return based measure is the average of quintiles of the Roll
(1984) measure, the Llorente et al. (2002) measure, and the inverse of trading volume divided by the
number of shares outstanding.
Panel A: Coefficient Estimates on Different Measures of Asymmetric Information
Market Choice
Private
vs. Public
Security Choice Conditional On Market
Public Convertible
Private
Private
Equity
s
Equity
Convertibles
(vs. Public Debt)
(vs. Private Debt)
Analyst Earnings Estimate Dispersion
-0.350a
0.103a
(3.430)
(-3.74)
Insider Trading (Signed) Prior to Security Issuance
-0.009
(-0.15)
0.129a
(2.530)
0.189a
(3.890)
-0.291a
0.109a
(3.970)
(-5.15)
Abnormal Stock Return to Earnings Announcements
-0.148a
(-2.47)
0.026
(0.460)
0.054
(0.930)
0.101a
(3.750)
Volume and Return Based Measure
-0.124a
(-3.19)
-0.078
(-1.61)
0.038
(0.880)
0.129a
(2.800)
0.025
(0.770)
-0.120a
(-2.48)
-0.028
(-0.53)
0.002
(0.040)
0.030
(0.570)
a,b,c - Significantly different from zero at the one-percent (five, ten) level of significance.
Table 9B: Economic Significance of Asymmetric Information Measures
Table 9B illustrates the economic significance of different measures of asymmetric information using
the same specification as Table 6. We vary the asymmetric information measures by +/- 1/2 of their
standard deviation, and evaluate the change in each predicted probability of security issuance, keeping
all other variables fixed at their actual observation values.
Debt
Analyst Earnings Estimate Dispersion
All Firms
2.95
Small firms
3.85
Large firms
2.02
Public
Convertibles Equity
1.82
2.93
0.68
Debt
Private
Convertibles
Equity
-4.77
-6.77
-2.71
-1.04
-1.51
-0.55
0.67
1.07
0.26
0.37
0.44
0.29
Insider Trading (Signed) Prior to Security Issuance
All Firms
3.24
0
Small Firms
3.31
0.82
Large Firms
3.17
-0.8
-3.24
-4.14
-2.37
0.27
0.41
0.13
-0.26
-0.45
-0.09
-0.01
0.04
-0.05
Abnormal Stock Return to Earnings Announcements
All Firms
1.51
-0.21
Small Firms
1.44
0.15
Large Firms
1.58
-0.54
-1.3
-1.58
-1.04
-0.64
-0.95
-0.34
0.79
1.35
0.28
0.16
0.4
0.07
Volume and Return Based Measure
All Firms
4.67
Small Firms
4.06
Large Firms
5.24
-1.6
-1.65
-1.55
0.05
0.07
0.03
0.12
0.22
0.02
-0.17
-0.29
-0.06
-3.07
-2.41
-3.69
Table 10
The Timing of Private and Public Security Issues Relative to Earnings Releases
Table 10 illustrates the timing of security issues. For each security-market combination, we test whether the
number of days between an issue and the closer earnings release (positive if the preceding earnings release
is closer to the issue date than the subsequent earnings release) is symmetrically distributed around zero
(Wilcoxon matched-pairs signed-rank test). The public-private column reports the Mann-Whitney two-sample
statistics for the hypothesis that for a given security type, the timing of issues in the public and private
markets has the same distribution. Panel B reports the Mann-Whitney two-sample statistics for the
hypothesis that any security choice pair, for a given market, have the same distribution. We use a 40-day
window around the issue date for quarterly earnings release and an 180-day window for annual earnings
release.
Market
Public
N
z-value
Security
Panel A: Tests of Issuance Timing in and across Markets
all quarters
1,929
5.25 a
1st qtr
527
3.20 a
Common
2nd qtr
491
-1.67 c
3rd qtr
434
7.37 a
4th qtr
477
1.95 c
annual
2,030
2.97 a
all quarters
1st qtr
2nd qtr
3rd qtr
4th qtr
annual
801
225
202
189
185
912
3.93
1.88
0.72
3.79
1.67
2.51
a
all quarters
1st qtr
2nd qtr
3rd qtr
4th qtr
annual
2,872
806
678
648
740
3,204
2.78
1.40
-2.33
4.76
1.81
3.31
a
2.70
1.89
0.27
2.97
0.47
0.52
a
all quarters
1st qtr
2nd qtr
3rd qtr
4th qtr
annual
1.85
1.3
1.33
0.67
0.34
0.66
c
all quarters
1st qtr
Common - Convertible 2nd qtr
3rd qtr
4th qtr
annual
0.22
0.09
-1.12
1.65
-0.09
-0.32
Convertibles
Debt
Panel B: Tests of Issuance Timing within Markets
Common - Debt
all quarters
1st qtr
2nd qtr
3rd qtr
4th qtr
annual
Convertible - Debt
c
a
c
b
b
a
c
a
c
a
c
Private
N
Public-Private
z-value
z-value
1,615
416
400
466
333
1,909
0.43
0.84
-0.93
0.46
0.56
1.04
3.45
1.69
-0.41
4.86
0.91
1.65
a
1,296
377
283
387
249
1,512
-0.41
-0.04
0.25
-0.34
-0.71
2.78
3.49
1.82
0.30
3.08
1.91
0.52
a
5,492
1,513
1,351
1,376
1,252
6,293
-1.77
-1.50
-1.88
2.31
-2.65
5.48
3.40
2.00
-0.61
2.57
2.98
-0.47
a
1.25
1.40
0.07
-0.78
1.89
-1.79
0.55
0.63
1.02
-1.36
0.81
-0.08
0.51
0.62
-0.83
0.46
0.80
-1.36
a
c
c
b
a
a
c
c
c
a
c
c
a
c
b
a
a
Table 11
Public and Private Security Issuance including 144-A Issued Securities
Table 11 presents coefficient estimates from a nested logit regression that tests the impact of asymmetric information and agency costs on public and private security issues by
public firms. The first stage is the decision of whch market in which to issue with coefficients representing tendency relative to public market. The second stage is the choice of
security conditional on the market, with coefficients representing tendency versus public market issuance. All firm-specific variables are lagged. Explanatory variables (except
predicted financial need) are as defined in Table 3. We normalize all variables (except the dummy variable financial distress) by their standard deviation. Predicted financial
need (internal funding deficit) is the instrumented amount of capital expenditures plus increase in net working capital less operating income before depreciation. The chi-squared
statistic for test of overall significance is 13946 (p-value 0.001). Our sample comprises 8,354 security issues. The table includes industry fixed effects for each security type.
Robust Z-statistics appear in parentheses.
Explanatory Variables
Measures of Asymmetric Information
Analyst Earnings Dispersion
Risk Measure
Cash Flow Volatility
Investment Opportunities
R&D / lagged PPE
Tobin's q
Debt, Taxes and Profitability
Debt/Asset Ratio
(Industry Adjusted)
Marginal Tax Rate
Market Decision
Private Market
144-A Market
(vs. Public)
(vs. Public)
a
0.609
0.838
(6.900)
(4.800)
0.209
(1.750)
c
-0.124
(-1.810)
0.185
(4.070)
a
0.103
(2.850)
a
c
0.143
(.730)
0.337
(4.650)
a
0.364
(4.960)
a
0.103
(.510)
-0.075
(-1.420)
0.359
(5.790)
a
0.056
(.280)
0.264
(3.980)
a
0.170
(2.400)
b
0.325
(1.640)
0.043
(.940)
0.592
(10.900)
a
0.410
(3.970)
0.773
(11.780)
a
0.748
(10.850)
a
0.123
(1.180)
a
-0.049
(-.520)
0.117
(2.030)
b
0.182
(3.050)
a
0.129
(1.250)
-0.079
(-.810)
-0.432
(-5.350)
a
-0.378
(-4.620)
a
-0.135
(-1.200)
-0.960
(-12.800)
a
-0.830
(-10.620)
a
-0.054
(-.340)
0.324
(2.030)
b
0.481
(2.960)
a
-0.297
(-.990)
a
0.192
(4.560)
-0.025
(-.780)
-0.194
(-4.520)
a
-0.021
(-.440)
0.108
(1.820)
c
-0.444
(-6.750)
0.480
(4.240)
b
0.089
(.660)
Financial Distress
(Z-score <1.81)
-0.149
(-1.560)
c
Private Conv. 144-A Conv.
(vs. Private Debt) (vs. 144-A Debt)
a
0.137
0.025
(3.240)
(.120)
a
0.141
(3.600)
-0.085
(-1.920)
Security Decision
Public Conv.
Private Equity
(vs Public Debt) (vs. Private Debt)
c
-0.208
0.081
(-1.120)
(1.870)
0.338
(4.820)
0.016
(.500)
Profitability
-0.085
(Operating cash flow/ lagged assets)
Size and Corporate Governance
Predicted Financial Need
a
Public Equity
(vs Public Debt)
a
-0.986
(-6.330)
a
-0.498
(-3.260)
a
a
0.411
(1.570)
0.145
(3.210)
a
0.202
(4.380)
a
0.283
(4.050)
a
0.327
(3.730)
a
-0.615
(-4.100)
a
-0.234
(-.810)
-0.961
(-20.650)
a
-0.166
(-2.920)
a
-0.745
(-12.270)
a
0.670
(5.350)
a
-1.700
(-16.660)
a
-1.774
(-16.400)
0.065
(2.250)
b
0.060
(1.560)
0.155
(2.790)
a
0.095
(1.620)
0.092
(.910)
-0.572
(-16.450)
a
-0.107
(-2.980)
a
0.615
(14.660)
a
0.538
(6.580)
0.235
(4.260)
a
-0.025
(-.360)
0.006
(.070)
-0.175
(-5.490)
a
-0.218
(-5.230)
a
0.152
(3.470)
a
0.048
(.470)
0.128
(2.290)
b
-0.035
(-.580)
0.018
(.160)
Aaa Bond Rate
0.116
(3.220)
a
-0.329
(-7.060)
a
0.133
(2.590)
a
0.041
(.350)
0.221
(3.280)
a
0.276
(3.670)
a
-0.469
(-3.680)
Credit Spread: Baa - Aaa
0.185
(4.700)
a
-0.106
(-1.990)
b
0.147
(2.740)
a
-0.189
(-1.440)
0.578
(8.360)
a
0.220
(2.880)
a
0.209
(1.430)
Log Size
(Firm Value)
Corporate Governance
Market Timing & Market Characteristics
Cumulative Abnormal Stock Return
(250 prior days)
Cumulative Market Return
(Prior year)
a,b,c - Significantly different from zero at the one-percent (five, ten) level of significance.
-0.010
(-.240)
-0.017
(-.190)
a
c
-0.117
(-1.320)
a
-0.362
(-2.670)
a
a
Table A1
Choice of Security Issuance in Public and Private Markets
Table A1 presents coefficient estimates from a multinomial logit regression testing the impact of asymmetric
information and risk on firm public and private security by public firms. Coefficents represent impact on
probability relative to public debt issuance. All firm-specific variables are lagged. All market-specific variables
represent three months prior to the security issuance. Analyst earnings surprise represents the difference
between actual earnings and median analyst forecast per share. Explanatory variables are as defined in Table
2 and they have all been normalized by their standard deviation (except the indicator variable financial
distress). Chi-squared statistic for test of overall significance is 2662 (p-value .001). Sample is 8346 security
issues. Pseudo R-squared is 28.2 percent. Industry fixed effects are included for each security. Robust Zstatistics are presented in parentheses.
Security Issuance Decision
Explanatory Variables
Public
Private
Public
Private
Private
Equity
Equity
Convertibles Convertibles
Debt
Measure of Asymmetric Information
a
a
a
Analyst Earnings Surprise
-0.774
0.272
-0.021
0.329
0.211 a
(-3.220)
(4.450)
(-.290)
(5.650)
(4.460)
Risk Measure
Cash Flow Volatility
Investment Opportunities Measures
R&D / Net Fixed Assets
(Z-score < 1.81)
Tobin's q
Profitability
(Operating Cash Flow)
Financial Distress
Corporate Governance
Size Measures
Log Firm Size
(firm value)
Predicted Financial Need
Debt and Taxes
Debt/Asset Ratio
(Industry Adjusted)
Marginal Tax Rate
Market Timing & Market Characteristics
Cumulative Abnormal Stock Return
(250 prior days)
0.538
(3.690)
a
0.724
(-1.180)
0.537
(3.480)
a
0.439
(2.840)
0.623
(-.060)
a
0.735
(-.450)
0.563
(3.650)
a
0.533
(.640)
0.223
(1.750)
c
0.391
(-3.590)
a
c
0.992
(2.960)
a
1.183
(2.560)
a
0.871
(3.040)
a
1.160
(2.190)
b
0.518
(1.790)
-0.627
(-5.120)
a
-1.132
(-8.580)
a
-0.764
(-6.080)
a
-1.001
(-7.610)
a
-0.170
(-1.620)
-0.212
(8.120)
a
-0.013
(9.020)
a
-0.079
(7.270)
a
0.138
(8.710)
a
-0.434
(5.070)
0.175
(2.390)
b
0.068
(1.140)
0.008
(.150)
0.115
(1.500)
-1.751
(-20.110)
a
-2.821
(-18.350)
a
-0.485
(-6.530)
a
-2.906
(-17.300)
0.242
(2.820)
a
-0.803
(-5.040)
a
0.186
(3.600)
a
-0.439
(-1.430)
0.135
(2.280)
b
0.064
(.910)
0.000
(-.010)
-0.411
(-3.960)
-0.012
(-.210)
a
a
0.030
(.750)
a
-1.417
(-15.630)
a
-0.001
(-.010)
0.129
(1.790)
c
-0.048
(-1.120)
-0.144
(-2.170)
b
-0.358
(-3.560)
a
0.022
(.510)
a
-0.286
(-2.520)
a
-0.330
(-5.700)
a
-0.069
(-1.810)
c
0.376
(5.430)
a
-0.022
(-.260)
0.318
(4.580)
Cumulative Market Return
(Prior year)
0.106
(2.010)
b
0.075
(1.130)
0.029
(.510)
Aaa Bond Rate
0.360
(6.290)
a
0.476
(6.620)
a
-0.141
(-2.330)
b
0.530
(6.780)
a
0.301
(7.960)
a
Credit Spread: Baa - Aaa
0.379
(5.770)
a
0.827
(10.400)
a
0.168
(2.460)
b
0.471
(5.430)
a
0.324
(7.110)
a
a,b,c - Significantly different from zero at the one-percent (five, ten) level of significance.
-0.088
(-1.250)
Figure 1. Predicted Security-Market Choices by Size Groups. The figure shows the security with the maximum predicted
probability of issuance using the coefficients of Table 6 as we vary risk and earnings surprise for three size groups: small-below 33rd
percentile, medium-between 33rd and 66th –percentile, and large-above 66th percentile. Risk (volatility of cash flows) is on the y-axis
and asymmetric information (earnings surprise relative to analyst forecasts) is on the x-axis. We hold all data at security means for the
respective size group and then vary risk and asymmetric information proxies from +/- 10 standard deviations away from the mean
value for each size group. PuE (PrE) is public (private) equity, PuC (PrC) is public (private) convertibles, PuD (PrD) is public
(private) Debt. Dark and light shading within regions represents predicted probability of that security greater than 50% and 0-50%
higher than the next highest security.
Figure 2. Predicted Security-Market Choices: The figure shows the security with the maximum predicted probability of issuance using the
coefficient estimates from Table 6 as we vary risk and asymmetric information (earnings surprise) for each of the six actual security choices. Risk
(volatility of cash flows) is on the y-axis and asymmetric information (earnings surprise relative to analyst forecasts) is on the x-axis. We hold all
data at security means and then vary risk and asymmetric information proxies from +/- 10 standard deviations away from the mean value for each
security type. PuE (PrE) is public (private) equity, PuC (PrC) is public (private) convertibles, PuD (PrD) is public (private) Debt. Dark and light
shading within regions represents predicted probability of that security greater than 50% and 0-50% higher than the next highest security.