Description
Empirical studies in the capital structure find a positive relationship between firm size and leverage. Suggested explanations in the literature include: large firms tend to have more leverage perhaps because they are more transparent; have lower asset volatility; more diversified; naturally sell large enough debt issues so that the fixed costs of public borrowing are not prohibitive; have lower probability of default and less financial distress costs.
Financial Flexibility, Leverage, and Firm Size
1
by
Soku Byoun
Hankamer School of Business
Baylor University
One Bear Place 98004
Waco, TX 76798
Tel: (254) 710–7849
Fax: (710) 710-1092
Email: Soku [email protected]
January 2007
1
We would like to thank the GAMF. We appreciate the support for this project that was provided
by the Hankamer School of Business at Baylor University.
Financial Flexibility, Leverage, and Firm Size
Abstract
We ?nd that small ?rms have lower leverage ratios, not because of internally generated
funds or additional debt ?nancing (as implied by the pecking order theory) but because of
additional equity ?nancing (consistent with our ?nancial ?exibility hypothesis). This ?nd-
ing can be explained by neither of the pecking order theory and the tradeo? theory—the
pecking order may be reversed for small ?rms that prefer external equity to debt ?nancing
while the tradeo? theory may miss out some important aspects of capital structure deci-
sions. We argue that small ?rms maintain low leverage by issuing equity and building up
cash holdings for ?nancial ?exibility. Debt covenant often carry restrictions on ?nancing
and investment decisions that are especially cumbersome for small, growing ?rms. Equity
?nancing allows small ?rms to raise cash without impeding ?nancial ?exibility. Consistent
with this argument, we ?nd small ?rms build up cash holdings in order to preserve ?nancial
?exibility through external equity. Once we account for ?nancial ?exibility, the positive
relationship between ?rm size and leverage found in previous studies is unclear.
JEL Classi?cation: G32
Keywords: Financial Flexibility; Trade-o? theory; Pecking-order theory
I. Introduction
Empirical studies in the capital structure ?nd a positive relationship between ?rm size
and leverage.
1
Suggested explanations in the literature include: large ?rms tend to have
more leverage perhaps because they are more transparent; have lower asset volatility; more
diversi?ed; naturally sell large enough debt issues so that the ?xed costs of public borrowing
are not prohibitive; have lower probability of default and less ?nancial distress costs. On the
other hand, small ?rms incur higher costs of issuing debt or equity since they are subject to
severe asymmetric information problems and default risk, more likely to be growing ?rms
with volatile cash ?ows and hence have less access to external funds than do large ?rms.
Further, the costs of ?nancial distress are likely to be particularly severe for small ?rms
because much of their value comes from growth options whose value depreciates rapidly if
the ?rm experiences ?nancial distress. In addition, small ?rms have a large fraction of their
assets that are ?rm speci?c or intangible, limiting their value as collateral.
Given that small ?rms grow faster than large ?rms (Evans (1987)), there are two alter-
natives for small ?rms to have lower leverage; by ?nancing their growth either exclusively
through retained earnings or through external equity. Most explanations for the positive
relationship between ?rm size and leverage assume implicitly or explicitly that external
equity is prohibitively expensive for small ?rms and hence small ?rms’ ?nancing should
come exclusively from internal funds.
2
There is also evidence that ?rms prefer internal
?nancing to external ?nancing.
3
According to the pecking order theory (Myers and Ma-
jluf (1984)), adverse selection costs of external equity are much greater than those of debt.
1
For example, see Titman and Wessels (1988), Rajan and Zingales (1995), Graham,
Lemmon, and Schallheim (1998), Hovakimain, Opler, and Titman, (2001), Booth et al.
(2001) and Fama and French (2002). However, Faulkender and Petersen (2006) ?nd a weak
or negative relationship between the leverage and ?rm size.
2
See, for example, Frank and Goyal (2003), Leary and Roberts (2005), Strebulaev (2006),
and Kurshev and Strebulaev (2006) for such arguments.
3
See Hovakimian, Opler, and Titman (2001) and Hovakimian, Hovakimian, and Tehra-
nian (2004).
1
Issuance costs are also much greater for equity than for debt.
4
Facing such high adverse
selection/transaction costs, small ?rms should avoid issuing equity by all means. Hence
the literature has paid little attention to the potential role of external equity in relaxing
?nancing constraints of small ?rms in debt ?nancing.
We suggest the desire for “?nancial ?exibility” as an alternative explanation for small
?rms’ low leverage and yet their reliance on external equity ?nancing. Recently, the survey
results of Graham and Harvey (2001), Bancel and Mittoo (2004), and Brounen et al. (2004)
show that corporate managers explicitly express that they are mostly concerned about
“?nancial ?exibility” in their capital structure decisions. We ?rst examine the concept of
?nancial ?exibility closely, paying special attention to those features of ?exibility brought
to light by recent management and organization literatures. The term is very broad and has
many legitimate uses that need not be forced under a single de?nition. At the same time
it will be necessary to de?ne the term more clearly so as to avoid the confusion from its
various uses in the ?nance literature. Thus, we ?rst develop a concept of ?nancial ?exibility
and then investigate the relevance of ?nancial ?exibility to capital structure decisions.
We de?ne ?nancial ?exibility as the degree of capacity and speed at which the ?rm can
mobilize its ?nancial resources in order to take reactive, preventive and exploitive actions
to maximize the ?rm value. We are persuaded that all of the uses of ?exibility pertinent to
the ?nance literature are encompassed by its reactive, preventive and exploitive nature.
In view of ?nancial ?exibility, change in pro?t (especially loss) can be important determi-
nant of leverage. Speci?cally, ?rms with negative retained earnings (from the accumulation
of losses) are likely to have little ?nancial ?exibility and debt capacity but ample needs
for additional cash. Our main hypothesis is that ?rms with negative retained earnings are
more likely to issue equity to build up cash holdings in order to preserve ?nancial ?exibility
and hence have low leverage. The corollary to this hypothesis is that cash holdings will be
negatively associated with leverage. We also examine if small ?rms’ lower leverage can be
4
Altinkilic and Hansen (2000) ?nd that equity issuing costs are on average 5.38% of the
issue proceeds while debt issuing costs are on average 1.09%. Leary and Roberts (2005)
also report signi?cantly larger equity issuance costs.
2
explained by the consideration of ?nancial ?exibility focusing on the relationship between
?rm size and leverage.
We ?nd that large ?rms retain much more earnings than small ?rms and that low lever-
age for small ?rms results from external equity ?nancing rather than internal funds. While
small ?rms avoid debt ?nancing, they are much more active in tapping into external equity
capital. Firms with negative retained earnings have lower leverage ratios and issue several
times more equity than ?rms with positive retained earnings. We also ?nd that small ?rms
have negative retained earnings with more cash holdings than other ?rms. Thus, our ?nd-
ings are consistent with the argument that small ?rms build ?nancial ?exibility through cash
holdings and equity ?nancing to cope with their “abnormal” periods of earnings shortfalls
(DeAngelo and DeAngelo (2006)).
We further show that ?rm size has an overall strong and signi?cant positive association
with leverage ratios. However, the positive relationship between ?rm size and leverage ra-
tios are substantially weakened or reversed for large ?rms when we divide ?rms re-estimate
regressions for ?rms divided into small/large and positive/negative retained earnings. Also,
negative retained earnings dummy variables are associated with signi?cant and positive
coe?cient estimates, suggesting lower leverage ratios for ?rms with negative retained earn-
ings. On the other hand, when we include retained earnings as a continuous variable in
the subgroup regressions, positive retained earnings are signi?cantly and negatively asso-
ciated with leverage ratios, whereas negative retained earnings show less economically and
statistically signi?cant association with leverage ratios. Thus, our results show that ?rms
with negative retained earnings build up cash holdings through equity ?nancing, lowering
leverage ratios, whereas ?rms with more positive retained earnings also have lower leverage
ratios through the accumulation of earnings (as a means of building ?nancial ?exibility).
Overall, the relationship between leverage and ?rm size is not clear.
Our study brings new evidence to bear on an important issue in the capital structure
literature. The literature has wrestled with the problem of sorting out the e?ects of adverse
section costs of asymmetric information on capital structure.
5
On the one hand, the liter-
5
For example, see Myers and Majluf (1984), Viswanath (1993), Chang and Dasgupta
3
ature ?nds that larger ?rms tend to issue more debt relative to equity than smaller ?rms
and hence appear to provide a better ?t for the pecking order theory (Shyam-Sunder and
Myers (1999) and Frank and Goyal (2002)). On the other hand, our results show that small
?rms issue equity and raise up cash holdings despite having low leverage. Lemmon and
Zender (2004) provides a justi?cation for equity issuances that equity issuers are prevented
from issuing debt because of concerns over ?nancial distress or to preserve ?nancial slack
for future investment. Further, Fama and French (2002) and Leary and Roberts (2005a)
show that ?rms are more likely to use equity ?nancing as investment increases and/or cash
?ow decreases but the majority of equity ?nancings occur when ?rms still have su?cient
debt capacity to ?ll their investment needs. However, small ?rms in our sample appear to
issue equity and build up cash holdings in order to cope with abnormal earnings shortfalls
rather than to preserve ?nancial slack.
As an alternative explanation for violating the ?nancing hierarchy, Fama and French
(2005) and Leary and Roberts (2005a) suggest that ?rms are able to issue securities in
a manner that avoids the adverse selection costs associated with information asymmetry.
Alternatively, managers may time the market when information asymmetry, and the cor-
responding costs, are low so that deviations from the hierarchy do not incur a signi?cant
penalty.
6
Our ?ndings suggest that the external ?nancing hierarchy suggested by the peck-
ing order theory is revered due to the concern for ?nancial ?exibility. Consistent with our
evidence, Byoun (2006a) ?nds that small debt-free ?rms raise much external equity while
reducing debt and paying large dividend. Thus, ?nancial ?exibility can bear more impor-
tant relevance to capital structure decisions than the adverse selection costs of asymmetric
(2003), and Lemmon and Zender (2004) under the pecking order framework, and Frank
and Goyal (2003), Fama and French (2002), Barclay and Smith (2005), Leary and Roberts
(2005), Leary and Roberts (2005a), Strebulaev (2006) and Byoun (2006) under the tradeo?
framework.
6
Rajan and Zingales (1995), Jung, Kim, and Stulz (1996), Pagano, Panetta, and Zingales
(1998), Hovakimian, Opler, and Titman (2001), Baker and Wurgler (2002), and Leary
and Roberts (2005a)) examine managers’ market-timing attempts. The survey results in
Graham and Harvey (2001) suggest that managers issue equity following an increase in
stock price.
4
information.
Our ?ndings suggest that small ?rms have lower leverage ratios, not because of internally
generated funds or additional debt ?nancing (as implied by the pecking order theory) but
because of additional equity ?nancing (consistent with our ?nancial ?exibility hypothesis).
Small ?rms build up cash holdings in order to preserve ?nancial ?exibility through external
equity. Overall, asymmetric information falls short of providing a complete explanation for
motivation behind ?rms’ external ?nancing decisions. An alternative explanation should
include the bene?ts and costs of ?nancial ?exibility, which may require a substantial al-
teration to the tradeo? argument which is based only on traditional costs and bene?ts of
taxes, bankruptcy costs, agency costs, and transaction costs.
II. The Concept of Financial Flexibility: A Literature Review
The pecking order theory by Myers and Majluf (1984) assumes that ?rms desire
to maintain “?nancial slack” to avoid the need for external funds. However, ?nding that
managers value ?nancial ?exibility is not su?cient to prove that the pecking-order model
is the true description of capital structure choice (Opler et al., 1999). Graham and Harvey
(2001) make this point explicit:
The most important item a?ecting corporate debt decisions is management’s
desire for “?nancial ?exibility,”... However, the importance of ?exibility in the
survey responses is not related to informational asymmetry (size or dividend
payout) or growth options in the manner suggested by the pecking-order theory.
In fact, ?exibility is statistically more important for dividend-paying ?rms, op-
posite the theoretical prediction (if dividend-paying ?rms have relatively little
informational asymmetry). Therefore, a deeper investigation indicates that the
desire for ?nancial ?exibility is not driven by the factors behind the pecking-
order theory.
Despite managers’ contention that ?nancial ?exibility is an important factor in the
decision-making process of managers, the capital structure literature has to date remained
aloof to recognize and incorporate ?nancial ?exibility. Frank and Goyal (2005) reason, “the
5
stress on ?nancial ?exibility is interesting, but potentially open to a variety of interpre-
tations. In our view the survey evidence is of interest, but it is best regarded as being
interesting and suggestive, rather than providing de?nitive tests.” In addition to consid-
erable ambiguity in the use of the term, judgments about ?exibility are subjective and
informal and ?exibility levels are rarely monitored or even measured. Accordingly, dealing
with ?nancial ?exibility may be criticized as being less than practical and based on specu-
lation on the ability of a ?rm to respond to hypothetical future events. It is therefore not
surprising that there is relatively little systematic study of ?nancial ?exibility in the capital
structure literature.
7
Graham Harvey (2001) see ?nancial ?exibility as “preserving debt capacity to make
future expansions and acquisitions” or “minimizing interest obligations, so that they do not
need to shrink their business in case of an economic down turn.” Gamba and Triantis (2005),
in their attempt to model the value of ?nancial ?exibility, de?ne, ?nancial ?exibility as “the
ability of a ?rm to access and restructure its ?nancing with low transaction costs.” They
further elaborate by adding “?nancially ?exible ?rms are able to avoid ?nancial distress in
the face of negative shocks, and to fund investment at low cost when pro?table opportunities
arise.” Donaldson (1969, 1971) uses “?nancial mobility” to describe “the capacity to redirect
the use of ?nancial resources in a manner consistent with the evolving goals of management
as it responds to new information about the company and its environment.” Donaldson
particularly relates ?nancial mobility to capital structure decisions where the goal is to ?nd
the optimal mix of ?nancing sources.
Heath (1978) describes ?nancially ?exible company as one that can take corrective action
that will eliminate an excess of required cash payments over expected cash receipts quickly
and with minor adverse e?ect on its present and future earnings or on the market value of
its stock. The American Institute of Certi?ed Public Accountants (AICPA, 1993) adopts
Heath’s view by de?ning ?nancial ?exibility as “the ability to take action that will eliminate
7
In contrast, a branch of real options literature has been developed to deal with “in-
vestment ?exibility.” Gamba and Triantis (2005) note that most real options models are
designed to measure the value of “investment ?exibility” under the assumption of perfect
“?nancial ?exibility.”
6
an excess of required and expected cash payments over expected resources.” The Financial
Accounting Standards Board’s (FASB) de?nes ?nancial ?exibility as “the ability of an
entity to take e?ective actions to alter amounts and timing of cash ?ows so it can respond
to unexpected needs and opportunities.” Most of the treatments of ?nancial ?exibility in
the ?nance literature are more or less about the ability of a ?rm to meet its expected future
needs through large cash ?ow, large unused borrowing capabilities, or large liquid assets.
The importance of ?exibility in a ?rm is well recognized in management and organization
literature. Bueno-Campos (1992), Ahmed et al. (1996), Albizu-Gallastegui (1997), Hitt et
al. (1998) and Volberda (1998) de?ne “?exibility” as the ability to deliver cost-e?cient
responses quickly to changes in the business environment and to adapt and anticipate
changes that a?ect the goals of ?rms. There are other views from di?erent functional
areas of business (See Koornhof (1998) for a more detailed review on this). For example,
Pasmore (1994) view humans are the drivers of organization ?exibility. Harrigan (1985)
use the term “strategic ?exibility” to refer to a ?rm’s ability to reposition itself in markets,
change its game plan or dismantle its current strategies. Trigeorgis (1993) and Kulatilaka
(1993) use the term “operating ?exibility” to describe the ability of managers to revise
operating decisions in response to favorable opportunities or deteriorating conditions. This
includes switching from one project to another. Such operating options are critical when
the environment is highly volatile and technology is ?exible, thus permitting managerial
intervention at little cost.
Bernstein (1993) de?nes ?exibility as the ability of an enterprise to take steps to counter
unexpected interruptions in the ?ow of funds for reasons however unexpected. In this view,
?nancial ?exibility means the ability to borrow from a variety of sources, to raise equity
capital, to sell and redeploy assets, and to adjust the level and the direction of operations in
order to meet changing circumstances. Koornhof (1998) de?nes ?exibility as an ability to
take actions to reposition the resources and functions of the organization to new information
and environment in a manner consistent with the evolving vision, strategies and goals of
management.
The de?nitions of ?exibility as addressed in the management and organization litera-
7
tures recognize the “reactive” and “preventive” nature of ?exibility while failing to include
the “exploitive” nature of ?exibility for uncertain competitiveness or environment. The
combination of reactive, preventive, and exploitive nature of ?exibility is more evident in
Volberda (1998) who views ?exibility in two di?erent perspectives: internal ?exibility as
the ?rm’s capacity to adapt to the demands of the environment, while external ?exibility
as the ?rm’s capacity to in?uence their environment and thereby reduce their vulnerability.
Following the Volberda’s (1998) notion of ?exibility, we propose to regard the ?nancial
?exibility not as the passive accumulation of resources but as the degree of capacity and speed
at which the ?rm can mobilize its ?nancial resources in order to take reactive, preventive and
exploitive actions to maximize the ?rm value. The choice of ?nancial ?exibility is pragmatic
and avowedly relativistic; it is chosen because of its ability to bring the diverse uses of
?exibility into meaningful comparative relationships. Actions initiated ahead of time are
typically taken in anticipation of certain events, or in an attempt to change the rules of the
game. When expectations are not met, or when events occur that have not been predicted,
a ?rm may require ?exibility after the fact. In these cases, attempts are made to correct a
mistake or to capitalize on an unexpected opportunity. The point to note is that actions
taken ahead of time, even in the absence of a speci?c goal, can create options that can be
used at a later stage. When a new product unexpectedly becomes an industry standard (e.g.,
Apple’s iPod), resulting in a rapid expansion of the market demand, exploitive maneuvers
are important to focus resources and to rapidly capitalize on spontaneous opportunities. The
speed is critical. According to our de?nition, ?nancial ?exibility is a function of uncertainty;
not just about future cash ?ows but also about organization and environment. If the
business environment is more turbulent and competitive (development stage in the life
cycle), there will be more demand for ?exibility to cope the uncertainty. Flexibility arises
from a formal decision problem in which the choice from future options are a?ected by the
choice made now (Gerwin, 1993). In other words, the decision on ?exibility made in the
present impacts on the options management will have available in the future in response
to unforeseeable change. Financial ?exibility is future oriented. It would be fundamentally
inappropriate of a CFO of a company to say that his or her job is to maximize ?exibility for
8
the organization. Thus, maximizing the ?rm value should be the ultimate goal of optimizing
?nancial ?exibility.
It is apparent that certain aspects of ?nancial ?exibility have been addressed in the
literature. For example, Goldstein, Ju, and Leland (2001) note that a ?rm with low leverage
today preserves the subsequent option to increase leverage. Byoun (2006) ?nd evidence that
?rms preserve borrowing capacity to ?nance future investment or growth opportunities.
Graham (2000) shows that ?rms preserve debt capacity to make future expansions and
acquisitions. Motyka, Leuca, and Fawson (2005) also ?nd that ?nancial institutions hold
excess liquidity to cope with the unpredictable nature of loss (infrequent but high impact
risk) in order to achieve a competitive advantage for aggressive pricing and better margins.
III. Financial Flexibility and Leverage: the Hypotheses
DeAngelo and DeAngelo (2006) note that ?rms can develop potential sources of
future ?nancial ?exibility through cash accumulation, the preservation of debt capacity, and
equity payouts. According to their argument, in “normal” periods, mature ?rms maintain
low leverage and high payouts, thus preserving the ?rm’s option to borrow or issue equity in
the future while limiting agency costs on cash balances. In “abnormal” periods characterized
by unanticipated earnings shortfalls or pro?table new investment opportunities, the ?rm
issues securities, either debt or equity, depending on the trade-o? between bene?ts and
costs of issuing now versus preserving the option for the future. Thus, in view of ?nancial
?exibility, change in pro?t (especially loss) can be important determinant of leverage.
We identify ?rms in those “abnormal” periods of unanticipated earnings shortfalls ac-
cording to retained earnings. Retained earnings are accumulation of ?rms’ reinvested pro?ts
over time. Negative retained earnings re?ect ?rms’ earnings shortfalls over time. Even a
little debt may cause ?rms with negative retained earnings to be in ?nancial distress. The
limitation on debt issuance that results from the risk of asset substitution (Jensen and
Meckling (1976)) are more important for ?rms with negative retained earnings. Firms with
negative retained earnings lack investible funds for their pro?table investments and hence
sources of free cash ?ow tend to be relatively less for them, and thus reducing the ben-
9
e?t of debt that limits the scope of overinvestment and perquisites by managers (Jensen
(1986), Stulz (1990) and DeAngelo and DeAngelo (2006)). Hence the bene?ts of debt are
less helpful both in terms of the sources and uses of free cash ?ow. Another bene?t to the
use of leverage is its signal to the market about the quality or riskiness of the ?rm (Ross
(1977), Leland and Pyle (1977), and Heinkel (1982)). However, debt ?nancing renders ?rms
with negative earnings vulnerable to predatory strategies such as price wars by established
?rms to exhaust vulnerable ?rms ?nancially (Poitevin (1989)), thus deteriorating ?nancial
?exibility. In addition, debt covenant often carry restrictions on ?nancing and investment
decisions that are especially cumbersome for small, growing ?rms. Accordingly, small ?rms
with negative retained earnings have little incentive to use leverage to signal their quality.
Overall, small ?rms with negative retained earnings are likely to have little ?nancial
?exibility and debt capacity but ample needs for additional cash. On the other hand,
equity issues neither require collateral or restrictive covenants, nor accentuate moral hazard
problems that are associated with leverage, nor raise the probability of ?nancial distress.
Thus, our main hypothesis is that ?rms with negative retained earnings are more likely to
issue equity than debt and have low leverage than ?rms with positive retained earnings.
We also hypothesize that small ?rms’ lower leverage can be explained by ?nancial ?exibility
consideration.
A ?rm can also develop ?nancial ?exibility through cash accumulation (DeAngelo and
DeAngelo (2006)). On the one hand, cash holdings increase ?nancial ?exibility. On the
other hand, it increases agency costs. Leverage can mitigate agency costs, but leverage
in turn reduces future ?nancial ?exibility. As noted above, ?rms with negative earnings
are likely to be in need of ?nancial ?exibility while constrained in borrowing and with
little concern for agency costs and thus they can accumulate cash holdings through equity
?nancing in order to preserve ?nancial ?exibility. Accordingly, we expect that cash holdings
are negatively associated with leverage ratios.
II. Data
The initial sample consists of all available U.S. ?rms for the period of 1971–2005
from the annual Compustat ?les. Following previous studies, we exclude ?nancial ?rms and
10
regulated utilities from the sample.
8
We also require ?rms to have positive total assets,
book and market value of equity and net sales. These variables are used to de?ate other
variables and it is di?cult to interpret the results when they have non-positive values.
We also delete observations with missing or non-positive values for the number of shares
outstanding (Compustat item 25) and stock price at the end of the ?scal year (item 199).
Accordingly, we drop bout 8 % of ?rm-year observations in the sample that have non-positive
total assets market value of equity or net sales. After these requirements are applied, the
sample consists of 179,418 ?rm-year observations.
While Shyam-Sunder and Myers (1999) and Myers (1984) argue that there are rational
reasons for managers to specify debt targets in terms of book values, Titman and Wessels
(1988) and Welch (2004) are inclined toward the use of debt level measured at market value.
Accordingly, we estimate the models using total (item 9 + item 34) and long-term (item 9)
debt ratios measured with both book and market value of total assets.
III. Estimation and Results
A. Firm Size and Leverage
In order to examine the relationship between ?rm size and leverage, we divide the sam-
ple into size deciles each year and report the leverage ratios measured in long-term and total
debt to book/market value of assets. The market value of assets equals total assets (item 6)
minus total equity (item 216) minus balance sheet deferred taxes and investment tax credit
(item 35) plus the market value of common equity (price (item 199) times shares outstand-
ing (item 54)) plus preferred stock liquidating value (item 10, replaced by the redemption
value of preferred stock (Item 56) when missing).
9
We delete all observations with leverage
8
Financial ?rms are represented by SIC codes 6000-6799 and utilities by SIC codes 4800-
4999. These ?rms have very di?erent capital structures and their ?nancing decisions may
not convey the same information as non-?nancial and non-regulated ?rms. For example, a
relatively high leverage ratio is normal for ?nancial ?rms, but the same high leverage ratio
for non-?nancial ?rms may indicate possible ?nancial distress.
9
The results does not change when we exclude deferred taxes and investment tax credit
or include convertible debt (item 79) in the de?nition of book equity as in Alti (2006) and
Kayhan and Timan (2006).
11
ratios less than zero or greater than one.
10
We de?ne size in three di?erent ways based on
book value of total assets (item 6), market value of total assets and net sales (item 12), but
the results are similar and we report only those based on the book value of total assets.
Table I
Panel A of Table I shows that regardless of the various de?nitions of leverage ratios,
there is a positive relationship between ?rm size and leverage ratio especially for smaller
size deciles. However, the positive relationship between ?rm size and leverage is not clear
for ?rms in the largest three deciles. We also report the percentage of zero-debt ?rms in
each size decile. Small ?rms are associated with much more zero-debt ?rms than large ?rms.
Byoun (2007) suggests that zero-debt ?rms are constrained by debt market while uncon-
strained by equity market. In order to examine whether the negative relationship between
?rms size and leverage is driven by these zero-debt ?rms, we report the results excluding
zero-debt ?rms in Panel B of Table I. Even though the leverage ratios of small ?rms increase
without the zero-debt ?rms, the positive relationship between size and leverage ratio are
still present for smaller size deciles. Thus, our results con?rm that there exists fairly strong
positive relationship between ?rm size and leverage except for ?rms in the largest three
deciles in which the positive relationship is weakened or reversed.
Table II
Faulkender and Petersen (2006) argue that market frictions may cause ?rms to be
rationed by their lenders, leading some ?rms to appear under-levered relative to uncon-
strained ?rms. Thus, when estimating a ?rm’s leverage, it is important to include not only
10
Without this requirement, the average book leverage ratio of the sample ?rms in the
?rst size decile are greater (but market leverage ratios are smaller) than ?rms in larger size
deciles since there are a few ?rms with book leverage ratios greater than one in the ?rst
size decile. When we winsorize leverage ratios at 99 percentile, there still exist ?rms with
leverage ratios greater than one.
12
determinants of its desired leverage (the demand side) but also variables that measure the
constraints on a ?rm’s ability to increase its leverage (the supply side). Following Faulkender
and Petersen (2005) and Lemmon and Zender (2004) we use ?rms’ long-term credit ratings
(item 280) as a measure of accessibility to the public debt markets. Rating information is
available only from 1985. Accordingly we divide the sample into two subperiods into before
and after 1985, which also allows us to examine any discernable change in the relationship
between ?rm size and leverage. For the period of 1971-1984, the relationship between ?rm
size and leverage is positive and monotonic, whereas the relationship is weak or negative for
?rms in the largest three deciles for the period of 1985-2005. The results show that small
?rms rarely have long-term credit ratings and most ratings are concentrated in the largest
three deciles. The lack of available credit ratings for small ?rms may indicate that these
?rms have relatively less debt capacity and hence lower leverage.
Our results explain why Faulkender and Petersen (2006) ?nd a negative relationship
between leverage and ?rm size. The sample in Faulkender and Petersen (2006) includes
only ?rms with credit ratings that are mainly from the largest size deciles for the period
since 1985 and these ?rms show a weak or negative association between ?rm size and
leverage.
B. Firm Size, Cash Holdings, Retained Earnings and External Financing Ac-
tivities
In order to examine weather the lower leverage for small ?rms results from accumulated
internal equity (as suggested by the pecking order theory) or external equity (as suggested
by the ?nancial ?exibility hypothesis), we report retained earnings (item 36), net long-term
debt issue (item 111 - item 114), net total debt issue (item 111 ? item 114 ? item 301
if item 318 = 1 and item 111 ? item 114 + item 301, otherwise)
11
and net new equity
issue (item 108 - item 115) as proportions of total assets. We also examine the ratio of
11
Changes in current debt (item 301) represent an increase in working capital for format
code 1 but a decrease in working capital for format codes.
13
cash and marketable securities to total assets ([item 162 + item 193] / item 6)
12
. We drop
observations with missing values in any of the reported variables.
Table III
Table III reports the results. The results in Panel A show that small ?rms tend to
have more cash holdings while having less retained earnings than large ?rms. In fact, the
average retained earnings are negative for ?rms in smaller size deciles. Thus, small ?rms’
growth is not likely to come mainly from internal equity. Small ?rms’ long-term or total
debt ?nancing is miniscule compared to that of large ?rms. On the other hand, small ?rms’
equity ?nancing is phenomenal. The ?rms in the ?rst and second size deciles issue equity
on annual average 25% and 12% respectively of total assets.
Our results can be driven by IPO ?rms that are more likely to be in small size deciles. In
order to examine the IPO e?ects, we identify the IPO date from Compustat and designate
the ?rst ?scal year ending after the IPO date as a IPO year. We also identify the ?rst year
appearing in the Compustat for those that do not have IPO dates but the Computat begins
its coverage during our sample period and treat it like the IPO year. The results excluding
these IPO years are reported in Panel B. They show that the magnitude of external equity
raised by small ?rms become smaller without IPO years, but it is still signi?cantly greater
than that raised by larger ?rms.
Another possibility is that the results could be driven by a few outliers especially in
small size deciles. To address this concern we reproduce results with winsorization of the
equity ?nancing variable at 1st and 99th percentiles. Again the results in Panel C show
the same result that the small ?rms heavily rely on external equity with little debt. The
pattern remains intact but only with less magnitudes when we winsorize the variable with
greater cuto? percentiles.
Overall, ?rm size is negatively associated with cash and debt ?nancing whereas positively
12
Including accounts receivable (item 2) in addition to cash and marketable securities
produces almost identical results.
14
associated with retained earnings, equity issue and dividend payout ratio. Thus, small ?rms
appear to have lower leverage ratios, not because of internally generated funds or additional
debt ?nancing but because of additional equity ?nancing. Small ?rms also build up cash
holdings in order to preserve ?nancial ?exibility through external equity.
C. Firm Size, Retained Earnings and Leverage
In order to disentangle the relationship between ?rm size and leverage ratios while
accounting for the strong association of ?rm size with retained earnings, we ?rst examine
the leverage ratios for ?rms divided into negative and positive retained earnings groups
within each size decile.
Panel A of Table IV shows cash holdings, dividend, and leverage ratios for each group.
Interesting is the ?nding that the smaller ?rms (in size deciles below 6) with negative
retained earnings hold more cash balances than similar size ?rms with positive retained
earnings probably as a means of preserving ?nancial ?exibility. On the other hand, large
?rms with negative retained earnings tend to carry less cash balances with higher leverage
ratios than large ?rms with positive retained earnings. The market value leverage ratios
for ?rms with negative retained earnings are always smaller than book value leverage ratios
because negative retained earnings increase market value of total assets when we subtract
total equity from total assets to replace with the market value of equity. Since the portion
of negative retained earnings relative to total assets are signi?cantly greater for small decile
?rms, smaller ?rms (in 1 to 4 size deciles) with negative retained earnings have higher book
leverage ratios whereas lower market-value leverage ratios than ?rms with positive retained
earnings in the same size deciles. Thus, ?rms with negative retained earnings appear to
have higher book leverage ratios because of less total assets stemming from negative retained
earnings. The results suggest that the relationship between ?rm size and leverage within
smaller size deciles (less than decile 5) can depend on whether the leverage is measured
in terms of book or market value because of the signi?cant number of ?rms with negative
retained earnings. Firms with positive retained earnings pay higher dividend than ?rms
with negative retained earnings. Thus, there are important di?erences between positive
15
and negative retained earnings groups.
Panel B of Table IV shows that ?rms with negative retained earnings issue much more
equity than those with positive retained earnings. The larger equity issues of small ?rms
are driven by ?rms with negative retained earnings as they issue equity to raise cash while
maintaining ?nancial ?exibility. This ?nding is consistent with our hypothesis that small
?rms with negative retained earnings issue equity rather than debt to preserve ?nancial
?exibility. Larger ?rms with negative retained earnings tend to issue both debt and equity,
but their equity issues are signi?cantly greater than those of large ?rms with positive re-
tained earnings.
Table IV
D. Regression Results
We ?rst estimate regressions with variables typically used in previous cross-sectional
studies as well as additional variables we expect to have signi?cant impacts on leverage
ratios. The following ?rm and industry characteristic variables are included:
Retained = retained earnings divided by total assets;
NegRet = dummy variable equal to one for the year with negative retained earnings and
zero otherwise;
Zero = dummy variable equal to one for the year with zero debt and zero otherwise;
IPO = dummy variable equal to one for IPO year and zero otherwise;
Cash = Cash and equivalents divided by total assets;
Med = industry median debt ratio (based on two-digit SIC or Fama and French (2002)
industry groupings). According to Frank and Goyal (2004), the industry median
leverage is an important determinant of a ?rm’s leverage ratio, acting as a proxy for
several factors, including intangibility, regulation, stock variance, uniqueness, pur-
chasing manager’s sentiment index, etc.;
16
Tax = marginal tax rate equal to the statutory tax rate if the ?rm reports no net operating
loss carryforwards (item 52) with positive pretax return (item 170) and zero otherwise.
The statutory taxes are 48% from 1971 to 1978, 46% from 1979 to 1986, 40% in 1987,
34% from 1988 to 1992, and 35% from 1993 to 2003. Plesko (2003) shows that this
binary measure captures the marginal tax e?ects;
OI = operating income (item 13) divided by total assets (item 6). A ?rm with higher
earnings could prefer to operate with either lower or higher leverage. Lower leverage
might occur, as higher retained earnings mechanically reduce leverage, or if the ?rm
limits leverage to protect the franchise responsible for producing these high earnings.
Higher leverage might re?ect the ?rm’s ability to meet debt payments out of its
relatively high earnings cash ?ow;
MB = market-to-book ratio of assets.
13
A higher MB is generally taken as a sign of more
attractive future growth options, which a ?rm tends to protect by limiting its leverage;
LnA = log of total assets (item 6) as a measure of ?rm size. Larger ?rms tend to: have more
leverage (perhaps because they are more transparent); have lower asset volatility; or
naturally sell large enough debt issues so that the ?xed costs of public borrowing are
not prohibitive;
14
DEP = depreciation and amortization (item 14) as a proportion of total assets. Firms
with more depreciation expenses have less need for the interest deductions associated
with debt ?nancing;
FA = ?xed assets (item 8) divided by total assets. Firms operating with greater tangible
assets have a higher debt capacity;
13
The results do not change when we exclude deferred taxes and investment tax credit
or include convertible debt (item 79) in the de?nition of book equity (as in Alti (2006) and
Kayhan and Titman (2006)).
14
The results are not a?ected whether the size is de?ned in terms of market value of
assets or of net sales (item 12).
17
RND = research and development expenditures (item 46) divided by net sales (item 12).
RND can be taken as a proxy for future expected investment (Fama and French
(2002)). They also serve as an additional proxy for non-debt tax shields. We set
missing values as zero and include a dummy variable;
D RND = dummy variable that equals one for ?rms with missing RND and zero otherwise;
DIV = common stock dividends (item 127) divided by total assets. DIV controls for
possible trade-o? between debt and dividend in reducing agency costs of free cash
?ow (Fama and French (2002)); and
AZ = Altman’s Z-score modi?ed by MacKie-Mason (1990): (3.3EBIT (item 178) + sales
(item 12) + 1.4 retained earnings (item 36) + 1.2 working capital (item 4 - item 5))
divided by total assets. Altman’s Z-score measures the ex ante probability of distress
(Graham (1996, 2000)).
We winsorize all the variables de?ated by total assets at the 1st and 99th percentiles
except for industry median (Med), dividend (DIV ), and R&D (RND) which are winsorized
only at the 99th percentile because many ?rms have a value of zero for these variables.
Table V reports two sets of estimation results for each dependent variable, with and
without variables NegRet, Zero, IPO, and Cash. These additional variables are not
frequently used in previous studies and we want to see if the results are di?erent when they
are included. The coe?cient estimates on ?rm size (LnA) are highly signi?cant and positive
in all regressions. Thus, there is a fairly strong positive relationship between leverage and
?rm size even after controlling for the additional variables. All the other coe?cient estimates
are signi?cant with the same signs found in previous studies. When we include NegRet,
Zero, IPO and Cash, the coe?cient estimates on these variables are negative. This result
suggests that ?rms with negative retained earnings have signi?cantly lower leverage. Also,
?rms holding more cash balances tend to have lower leverage.
In order to further examine the e?ect of retained earnings on the relationship between
?rm size and leverage, we divide the ?rm into four groups: large/small ?rms (deciles greater
than/less than or equal to 5) with positive/negative retained earnings. The reasons we
18
divide ?rms this way are that the e?ect of negative retained earnings could be di?erent
between small and large ?rms and that in our previous results the relationship between
leverage and ?rm size is rather ambiguous for larger ?rms. We run the same regressions as
in Table V for these subgroups except that we replace the negative retained earnings dummy
variable with retained earnings (Retained) winsorized at the 1st and 99th percentiles.
The estimation results are reported in Table VI. The results show that the coe?cient
estimates on size (LnA) tend to be positive for small ?rms (in Panels A and B) but negative
or insigni?cant for large ?rms (in Panels C and D). Thus, the positive relationship between
?rm size and leverage holds true only for small ?rms. This ?nding is consistent with
the univariate results that show lower leverage ratios for the largest decile ?rms. The
coe?cient estimates on retained earnings (Retained) are highly signi?cant and negative for
?rms with positive retained earnings (in Panels A and C), whereas they are economically or
statistically insigni?cant for ?rms with negative retained earnings (in Panels B and D). As
we observed in Table IV, the e?ects of negative retained earnings are di?erent between book
and market value leverage ratios: negative retained earnings lower the book leverage, which
results in small negative coe?cient estimates on retained earnings in book-value-leverage-
ratio regressions; and negative retained earnings increase the market value leverage, which
results in small positive or insigni?cant coe?cient estimates on retained earnings in market-
value-leverage-ratio regressions.
Overall, our results suggest that the positive relationship between leverage and ?rm size
hold for small ?rms but not for large ?rms when we control for retained earnings which
measures the degree of ?nancial ?exibility. The ?rm size up to a certain level appears
to be important for leverage but its importance disappears once ?rms outgrow that level.
Small ?rms’ lower leverage ratios appear to result from their concern for ?nancial ?exibility
(issuing equity and building up cash holdings) and large ?rms with positive retained earnings
also have lower leverage as they accumulate internal funds to preserve ?nancial ?exibility
or to ?nance growth opportunities. Thus, the relationship between leverage and ?rm size
appears to be positive for small ?rms but negative for large ?rms.
19
VI. Summary and Conclusions
We examine the relationship between ?rm size and leverage in the view of ?nancial
?exibility. We de?ne ?nancial ?exibility as the degree of capacity and speed at which the
?rm can mobilize its ?nancial resources in order to take reactive, preventive and exploitive
actions to maximize the ?rm value. We hypothesize that ?rms with negative retained
earnings are likely to have little ?nancial ?exibility and debt capacity but ample needs
for additional cash. Accordingly, ?rms with negative retained earnings are more likely to
issue equity to build up cash holdings (a means of ?nancial ?exibility) and hence have low
leverage. The corollary to this hypothesis is that cash holdings will be negatively associated
with leverage. We also examine if we can explain the positive relationship between ?rm size
and leverage in the view of ?nancial ?exibility, given that many small ?rms have negative
retained earnings and are in need of ?nancial ?exibility.
Consistent with our hypothesis, ?rms with negative retained earnings issue several times
more equity than ?rms with positive retained earnings. While small ?rms avoid debt ?-
nancing, they are much more active in tapping into external equity capital. We also ?nd
that small ?rms often have negative retained earnings with no less cash holdings than other
?rms and that small ?rms with negative retained earnings have lower leverage than ?rms
with positive retained earnings.
We further show that ?rm size has an overall strong and signi?cant positive associa-
tion with leverage. However, the positive relationship between ?rm size and leverage are
substantially weakened or reversed for large ?rms when we control for retained earnings.
Our regression results, coupled with univariate results, suggest that small ?rms with neg-
ative retained earnings build up cash holdings through equity ?nancing, lowering leverage
ratios, whereas large ?rms with positive retained earnings accumulate earnings (as a means
of building ?nancial ?exibility), resulting in lower leverage ratios. Thus, the relationship
between leverage and ?rm size is unclear—we need more research on this issue. Overall,
small ?rms appear to have lower leverage ratios, not because of internally generated funds
or additional debt ?nancing but because of additional equity ?nancing. Small ?rms also
build up cash holdings in order to preserve ?nancial ?exibility through external equity.
20
This ?nding can be explained by neither of the pecking order theory and the tradeo?
theory—the pecking order may be reversed for small ?rms that prefer external equity to debt
?nancing while the tradeo? theory may miss out some important aspects of capital structure
decisions. In conclusion, the bene?ts and costs associated with ?nancial ?exibility in?uence
?rms’ capital structure decisions—but not in the manner hypothesized by the traditional
trade-o? theory. Thus, a substantial alteration may be required to the tradeo? argument
which is based only on traditional costs and bene?ts of taxes, bankruptcy costs, agency
costs, and transaction costs.
21
References
Almeida, Heitor and Murillo Campello, 2005, Firm ?nancing-investment interactions: Ev-
idence from debt and equity issues, New York University and University of Illinois
Working paper.
Alti, Aydogan, 2006, How persistent is the impact of market timing on capital structure,
Journal of Finance 61, 1681-1710.
Altinkilic O. and R.S. Hansen, 2000, Are there economies of scale in underwriter fees?
Evidence of rising external ?nancing costs, Review of Financial Studies 13(1), 191–
218.
Asquith, Paul and David W. Mullins, Jr., 1986, Equity issues and o?ering dilution, Journal
of Financial Economics 15, 61–89.
Baker, Malcolm and Je?rey Wurgler, 2002, Market timing and capital structure, Journal
of Finance 57, 1–32.
Baltagi, Badi H., 2001, Econometric Analysis of Panel Data, 2nd edition, John Wiley &
Sons.
Barclay, Michael J. and Cli?ord W. Smith, 2005, The capital structure puzzle: The evi-
dence revisited, Journal of Applied Corporate Finance 17(1), 8–17.
Berger, Phillip, Eli Ofek, and David Yermack, 1997, Managerial entrenchment and capital
structure decisions, Journal of Finance 52, 1411–1438.
Bharath, Sreedhar T., Paolo Pasquariello, Guojun Wu, 2006, Does asymmetric information
drive capital structure decisions?, University of Michigan working paper.
Byoun, Soku, 2006, How do ?rms adjust their capital structures? Baylor University Work-
ing Paper.
Byoun, Soku, 2006a, Why do some ?rms go debt-free? Baylor University Working Paper.
22
Calomiris, C.W. Hubbard, R.G., 1990, Firm Heterogeneity, Internal Finance and Credit
Rationing, Economic Journal 100, 90–104.
Calomiris, C., Himmelberg, C. P., and Wachtel, P., 1995, Commercial paper, corporate
?nance, and the business cycle, Carnegie-Rochester Conference Series on Public Policy
42 (June), 203-50.
Cantillo, M., and J. Wright, 2000, How do ?rms choose their lenders? An empirical
examination, Review of Financial Studies 13, 155-190.
Chang, X. and S. Dasgupta, 2003, Capital structure theories: Some new tests, Hong Kong
University of Science and Technology working paper.
DeAngelo H. and L. DeAngelo, 2006, Capital Structure, Payout Policy, and Financial
Flexibility, University of Southern California working paper.
Evans, D. 1987, Tests of alternative theories of ?rm growth, Journal of Political Economy
95, 657674.
Fama, E. F. and French, K. R., 2002, Testing trade-o? and pecking order predictions about
dividends and debt, Review of Financial Studies 15(1), 1–33.
Fama, Eugene F. and Kenneth R. French, 2005, Financing decisions: Who Issues Stock?,
Journal of Financial Economics 76, 549–582.
Fama, E. F. and MacBeth, J. D., 1973, Risk, return, and equilibrium: Empirical tests,
Journal of Political Economy 81, 607–636.
Faulkender, Michael, and Mitchell A. Petersen, 2006, Does the source of capital a?ect
capital structure?, forthcoming, Review of Financial Studies 19, 45–79.
Flannery, Mark J. and Kasturi P. Rangan, 2006, Partial Adjustment Toward Target Cap-
ital Structures, Journal of Financial Economics Forthcoming.
Frank, M. Z. and Vidhan K. Goyal, 2003, Testing the pecking order theory of capital
structure, Journal of Financial Economics 67(2), 217–248.
23
Frank, M. Z. and Vidhan K. Goyal, 2004, Capital structure decisions: Which factors are
reliably important? University of British Columbia working paper.
Frank, M. Z. and Vidhan K. Goyal, 2005, Trade-o? and Pecking Order Theories of Debt,
B. Espen Eckbo(ed.), Handbook of Corporate Finance: Empirical Corporate Finance
(Handbooks in Finance Series, Elsevier/North-Holland), Chapter 7.
Goldstein, H., 1995, Multilevel Statistical Models, Halsted Press, New York.
Goldstein, R. N. Ju, and H. Leland, 2001, An EBIT-based Model of Dynamic Capital
Structure, Journal of Business 74, 483–512.
Graham, John R., 1996, Debt and the marginal tax rate, Journal of Financial Economics
41, 41–73.
Graham, John R., 2000, How big are the tax bene?ts of debt? Journal of Finance 55,
1901–1941.
Graham, John R. and Campbell R. Harvey, 2001, The theory and practice of corporate
?nance: evidence from the ?eld, Journal of Financial Economics 61, 187–243.
Heinkel, R., 1982, A theory of capital structure relevance under imperfect information,
Journal of Finance 37, 1141-1150.
Hovakimian, Armen, Tim C. Opler, and Sheridan Titman, 2001, The debt-equity choice:
An analysis of issuing ?rms, Journal of Financial and Quantitative Analysis 36(1),
1–24.
Hovakimian, Armen, Gayane Hovakimian and Hassan Tehranian, 2004, Determinants of
target capital structure: The case of dual debt and equity issues, Journal of Financial
Economics 71, 517–540.
Jensen, M.C., 1986, Agency costs of free cash ?ow, corporate ?nance and takeovers, Amer-
ican Economic Review 76, 323-339.
24
Jensen, M.C. and W. Meckling, 1976, Theory of the ?rm: Managerial behavior, agency
costs, and capital ttructure, Journal of Financial Economics 3, 305-360.
Jung, Kooyul, Yong-Cheol Kim, and Rene M. Stulz, 1996, Timing, investment oppor-
tunities, managerial discretion, and the security issue decision, Journal of Financial
Economics 42, 159–185.
Kashyap, Anil K., Owen A. Lamont and Jeremy C. Stein, 1994, Credit Conditions and the
Cyclical Behavior of Inventories, Quarterly Journal of Economics 109 (3), 565-592.
Kayhan, Ayla and Sheridan Titman, 2006, Firms’ histories and their capital structures,
Journal of Financial Economics, forthcoming.
Leary, Mark T. and Michael R. Roberts, 2005, Do ?rms rebalance their capital structures?
Journal of Finance 60, 2575–2619.
Leary, Mark T. and Michael R. Roberts, 2005a, The Pecking Order, debt capacity, and
information asymmetry, Duke University and University of Pennsylvania working pa-
per.
Lee, Inmoo, Scott Lochhead, Jay Ritter, and Quanshui Zhao, 1996, The costs of rasing
capital, Journal of Financial Research 19 (1), 59-74.
Leland, H. and D. Pyle, 1977, Information asymmetries, ?nancial structure, and ?nancial
intermediation, Journal of Finance 32, 371-388.
Lemmon, Michael L. and Jaime F. Zender, 2004, Debt capacity and tests of capital struc-
ture theories. University of Utah and University of Colorado working paper.
Lemmon, Michael L., Michael Roberts, and Jaime F. Zender, 2006, Back to the beginning:
Persistence and the cross-section of corporate capital structure, University of Utah,
University of Pennsylvania and University of Colorado working paper.
Lewellen, Katharina , 2003, Financing Decisions When Managers Are Risk Averse, MIT
Sloan School of Management Working paper.
25
MacKie-Mason, J.K., 1990, Do taxes a?ect corporate ?nancing decisions? Journal of
Finance 45, 1471–1494.
Modigliani, Franco and Merton H. Miller, 1958, The cost of capital, corporation ?nance
and the theory of investment, American Economic Review 53, 261–297.
Myers, S.C., 1984, The Capital structure puzzle, Journal of Finance 39, 575–592.
Myers, S.C. and N.S. Majluf, 1984, Corporate ?nancing and investment decisions when
?rms have information that investors do not have, Journal of Financial Economics
13, 187–221.
Pagano, Marco, Fabio Panetta, and Luigi Zingales, 1998, Why do companies go public?
An empirical analysis, Journal of Finance 53, 27–64.
Petersen, Mitchell A., 2005, Estimating standard errors in ?nance panel data sets: Com-
paring approaches, Northwestern University working paper.
Plesko, George A., 2003, An evaluation of alternative measures of corporate tax rates,
Journal of Accounting and Economics 35, 201–226.
Poitevin, M., 1989, Financial signalling and the deep-pocket argument, Rand Journal of
Economics 20, 26-40.
Rajan, R.G. and L. Zingales, 1995, What do we know about capital structure? Some
evidence from international data, Journal of Finance 50, 1421–1460.
Ross, S., 1977, The determination of ?nancial structure: The incentive signalling approach,
Bell Journal of Economics 8, 23-40.
Shyam-Sunder, L. and S.C. Myers, 1999, Testing static trade-o? against pecking order
models of capital structure, Journal of Financial Economics 51, 219–244.
Strebulaev, Ilya, 2006, Do tests of capital structure theory mean what they say? Journal
of Finance, forthcoming.
26
Stulz, R., 1990, Managerial discretion and optimal ?nancing policies, Journal of Financial
Economics 26, 3-27.
Titman, S. and R. Wessels, 1988, The determinants of capital structure choice, Journal of
Finance 43, 1–19.
Viswanath, P. V., 1993, Strategic considerations, the pecking order hypothesis, and market
reactions to equity ?nancing, Journal of Financial and Quantitative Analysis 28, 213–
234.
Welch, Ivo, 2004, Capital structures and stock returns, Journal of Political Economy 112,
106–131.
Wooldridge, Je?rey W., 2002, Econometric Analysis of Cross Section and Panel Data,
Cambridge: The MIT Press.
27
Table I. Firm Size Deciles and Leverage Ratios
The data consists of 179,418 firm-year observations for the period 1971-2005. Observations with missing values in any of
the reported variables are deleted. Size is size deciles based on total assets. Book /Market Long-term/Total Debt is long-
term/total debt over book/market value of total assets. The market value of assets equals total assets minus total equity
minus balance sheet deferred taxes and investment tax credit plus the market value of common equity plus preferred stock
liquidating value. % of Firms with Zero Debt is the percentage of firms relative to the total number of firms in each size
decile. A zero-debt firm is a firm with no debt.
A. All firm-year observations (179,418)
Size Decile Total Assets
Book Long-
term Debt
Book Total
Debt
Market Long-
term Debt
Market Total
Debt
% of Firms
with Zero
Debt
1 3.62 0.0974 0.2074 0.0590 0.1164 0.2035
2 10.39 0.1241 0.2184 0.0943 0.1647 0.1578
3 21.66 0.1356 0.2186 0.1137 0.1828 0.1487
4 40.62 0.1452 0.2170 0.1295 0.1936 0.1480
5 71.75 0.1651 0.2286 0.1482 0.2062 0.1293
6 128.62 0.1916 0.2493 0.1687 0.2217 0.0994
7 240.64 0.2188 0.2725 0.1890 0.2378 0.0744
8 496.17 0.2437 0.2942 0.2089 0.2537 0.0445
9 1354.40 0.2476 0.2968 0.2125 0.2552 0.0299
10 15673.95 0.2387 0.3017 0.2138 0.2679 0.0063
B. Non-zero-debt firm-year observations (155,435)
Size Decile Total Assets
Book Long-
term Debt
Book Total
Debt
Market Long-
term Debt
Market Total
Debt
1 3.67 0.1223 0.2604 0.0741 0.1462
2 10.26 0.1474 0.2593 0.1120 0.1955
3 21.17 0.1593 0.2568 0.1335 0.2147
4 39.21 0.1704 0.2547 0.1520 0.2273
5 68.78 0.1896 0.2626 0.1702 0.2368
6 123.99 0.2127 0.2768 0.1873 0.2461
7 237.02 0.2364 0.2944 0.2042 0.2569
8 490.26 0.2550 0.3079 0.2187 0.2655
9 1347.74 0.2553 0.3060 0.2190 0.2630
10 15694.31 0.2402 0.3036 0.2151 0.2696
Table II. Firm Size Deciles and Leverage Ratios for Sub-periods Divided into Before and After 1985
The data consists of firm-year observations for the period 1971-2005. Observations with missing values in any of the
reported variables are deleted. Size is size deciles based on total assets. Book /Market Long-term/Total Debt is long-
term/total debt over book/market value of total assets. The market value of assets equals total assets minus total equity
minus balance sheet deferred taxes and investment tax credit plus the market value of common equity plus preferred stock
liquidating value. % of Firms with Zero Debt is the percentage of firms with no debt relative to the total number of firms
in each size decile. % of Firms with Bond Rating is the percentage of firms with long-term credit ratings relative to the
total number of firms in each size decile.
A. For 1971 – 1984 Period (53,702 Obs)
Size Decile
Total
Assets
Book Long-
term Debt
Book Total
Debt
Market
Long-term
Debt
Market
Total Debt
% of Firms
with Zero
Debt
1 4.19 0.1132 0.2046 0.0873 0.1525 0.1734
2 9.75 0.1481 0.2350 0.1345 0.2123 0.1034
3 17.06 0.1727 0.2552 0.1658 0.2453 0.0812
4 27.68 0.1923 0.2695 0.1939 0.2719 0.0594
5 44.14 0.2035 0.2750 0.2031 0.2754 0.0540
6 71.33 0.2193 0.2873 0.2189 0.2880 0.0352
7 122.58 0.2315 0.2941 0.2293 0.2926 0.0374
8 239.36 0.2326 0.2893 0.2322 0.2884 0.0239
9 631.22 0.2470 0.3008 0.2488 0.3016 0.0121
10 4276.30 0.2505 0.3044 0.2638 0.3172 0.0019
B. For 1985 – 2005 Period (119,813)
Size Decile
Total
Assets
Book Long-
term Debt
Book Total
Debt
Market
Long-term
Debt
Market
Total Debt
% of Firms
with Zero
Debt
% of Firms
with Credit
Rating
1 3.36 0.0903 0.2087 0.0463 0.1003 0.2170 0.0000
2 10.67 0.1134 0.2110 0.0763 0.1433 0.1822 0.0004
3 23.72 0.1190 0.2023 0.0903 0.1548 0.1790 0.0006
4 46.41 0.1241 0.1934 0.1006 0.1586 0.1877 0.0022
5 84.14 0.1479 0.2078 0.1236 0.1751 0.1631 0.0128
6 154.28 0.1792 0.2323 0.1461 0.1920 0.1282 0.0551
7 293.57 0.2131 0.2628 0.1709 0.2133 0.0910 0.1533
8 611.28 0.2486 0.2963 0.1985 0.2382 0.0538 0.3279
9 1678.72 0.2479 0.2950 0.1962 0.2343 0.0379 0.5758
10 20778.29 0.2334 0.3005 0.1914 0.2458 0.0083 0.7800
Table III. Firm Size Deciles, Cash Holdings, Retained Earnings and External Financing Activities
The data consists of firm-year observations for the period 1971-2005. Observations with missing values in any of the
reported variables are deleted. Size deciles are based on total assets. All the variables are reported as a proportion of total
assets.
A. All firm-year observations (173,515)
Size Decile
Cash and
Equivalents
Retained
Earnings
Net Long-
term Debt
Issue
Net Total
Debt Issue
Net New
Equity Issue Dividend
1 0.4141 -3.8807 0.0023 -0.0004 0.2527 0.0077
2 0.4012 -0.8725 0.0024 0.0027 0.1164 0.0068
3 0.3989 -0.4103 0.0007 0.0025 0.0852 0.0078
4 0.3958 -0.1390 0.0013 0.0024 0.0777 0.0083
5 0.3725 0.0244 0.0044 0.0059 0.0604 0.0093
6 0.3475 0.0961 0.0103 0.0113 0.0453 0.0097
7 0.3157 0.1656 0.0174 0.0183 0.0273 0.0117
8 0.2784 0.1940 0.0219 0.0229 0.0158 0.0136
9 0.2469 0.1995 0.0219 0.0227 0.0082 0.0170
10 0.2195 0.2102 0.0163 0.0172 0.0017 0.0193
B. Non-IPO firm-year observations (154,156)
Size Decile
Cash and
Equivalents
Retained
Earnings
Net Long-
term Debt
Issue
Net Total
Debt Issue
Net New
Equity Issue Dividend
1 0.4033 -4.4562 0.0010 -0.0016 0.1744 0.0083
2 0.3945 -0.9800 0.0015 0.0019 0.0771 0.0069
3 0.3910 -0.4492 0.0007 0.0030 0.0495 0.0074
4 0.3797 -0.1444 0.0038 0.0056 0.0357 0.0073
5 0.3615 0.0281 0.0066 0.0084 0.0283 0.0082
6 0.3426 0.1029 0.0125 0.0140 0.0230 0.0092
7 0.3146 0.1742 0.0174 0.0183 0.0153 0.0111
8 0.2791 0.2003 0.0218 0.0228 0.0096 0.0132
9 0.2473 0.2047 0.0212 0.0219 0.0046 0.0164
10 0.2187 0.2120 0.0160 0.0168 0.0004 0.0193
C. Non-IPO firm-year observations with winsoriation at 1 and 99 percentiles (151,058)
Size Decile
Cash and
Equivalents
Retained
Earnings
Net Long-
term Debt
Issue
Net Total
Debt Issue
Net New
Equity Issue Dividend
1 0.3976 -3.4280 0.0025 0.0017 0.0743 0.0086
2 0.3880 -0.8900 0.0019 0.0027 0.0541 0.0067
3 0.3870 -0.4281 0.0010 0.0040 0.0432 0.0073
4 0.3776 -0.1393 0.0037 0.0057 0.0346 0.0072
5 0.3599 0.0276 0.0064 0.0084 0.0289 0.0081
6 0.3411 0.1017 0.0119 0.0134 0.0248 0.0091
7 0.3140 0.1723 0.0168 0.0177 0.0177 0.0110
8 0.2784 0.1979 0.0214 0.0224 0.0122 0.0131
9 0.2469 0.2032 0.0206 0.0212 0.0073 0.0163
10 0.2181 0.2111 0.0156 0.0164 0.0021 0.0193
Table IV. Firm Size Deciles, Retained Earnings, Leverage, Financing Activities
The data consists of firm-year observations for the period 1971-2005. Observations with missing values in any of the
reported variables are deleted. Size deciles are based on total assets. Firms are divided into positive and negative retained
earnings groups within each size decile. All the variables are reported as a proportion of total assets.
A. Cash Holdings and Leverage
Size
Decile
Retained
Earnings
Cash and
Equivalents Dividend
Book Long-
term Debt
Book Total
Debt
Market
Long-term
Debt
Market
Total Debt
1 -5.2296 0.4144 0.0039 0.1014 0.2276 0.0521 0.1098
1 0.3082 0.4132 0.0195 0.0850 0.1447 0.0806 0.1370
2 -1.7479 0.4062 0.0051 0.1365 0.2508 0.0872 0.1619
2 0.3014 0.3944 0.0091 0.1074 0.1748 0.1039 0.1684
3 -1.2568 0.4267 0.0065 0.1439 0.2463 0.1021 0.1770
3 0.2991 0.3748 0.0089 0.1286 0.1952 0.1235 0.1877
4 -0.8691 0.4397 0.0043 0.1518 0.2370 0.1162 0.1832
4 0.2892 0.3688 0.0106 0.1412 0.2051 0.1374 0.1998
5 -0.6213 0.4221 0.0053 0.1872 0.2702 0.1468 0.2152
5 0.2934 0.3510 0.0111 0.1558 0.2111 0.1488 0.2023
6 -0.5084 0.3784 0.0039 0.2442 0.3198 0.1915 0.2548
6 0.2899 0.3371 0.0115 0.1745 0.2264 0.1612 0.2109
7 -0.4025 0.3146 0.0071 0.3214 0.3939 0.2471 0.3074
7 0.2968 0.3159 0.0127 0.1944 0.2437 0.1752 0.2213
8 -0.3103 0.2600 0.0087 0.3723 0.4357 0.2898 0.3442
8 0.2903 0.2823 0.0146 0.2177 0.2656 0.1926 0.2354
9 -0.3077 0.2327 0.0105 0.3787 0.4394 0.2920 0.3434
9 0.2747 0.2492 0.0180 0.2274 0.2748 0.2002 0.2415
10 -0.1789 0.1896 0.0097 0.3590 0.4179 0.2878 0.3378
10 0.2459 0.2226 0.0202 0.2271 0.2905 0.2067 0.2612
Total
B. External Financing Activities
Size
Decile
Retained
Earnings
Net Long-term
Debt Issue
Net Total Debt
Issue
Net New
Equity Issue
Number of
Obs
1 -5.2296 0.0029 0.0008 0.3227 12324
1 0.3082 0.0004 -0.0041 0.0348 3989
2 -1.7479 0.0027 0.0038 0.1766 9318
2 0.3014 0.0020 0.0012 0.0353 6891
3 -1.2568 -0.0039 -0.0008 0.1446 7426
3 0.2991 0.0045 0.0052 0.0348 8575
4 -0.8691 -0.0051 -0.0045 0.1465 6013
4 0.2892 0.0050 0.0065 0.0370 9764
5 -0.6213 -0.0049 -0.0033 0.1255 4744
5 0.2934 0.0083 0.0098 0.0330 10931
6 -0.5084 0.0039 0.0029 0.1051 3937
6 0.2899 0.0124 0.0141 0.0259 11657
7 -0.4025 0.0160 0.0168 0.0706 3059
7 0.2968 0.0177 0.0186 0.0170 12270
8 -0.3103 0.0196 0.0185 0.0483 2665
8 0.2903 0.0224 0.0239 0.0092 12551
9 -0.3077 0.0356 0.0344 0.0310 2102
9 0.2747 0.0197 0.0209 0.0047 12897
10 -0.1789 0.0209 0.0172 0.0165 1397
10 0.2459 0.0159 0.0172 0.0003 13324
Total 155834
Table V
Parameter Estimates from Cross-sectional/Panel Regressions on Determinants of Leverage Ratio
The sample consists of 146,553 firm-year observations with relevant Compustat data from 1971 to 2005. The dependent
variable is the total/long-term debt?? (TD/LD) divided by book/market value of assets (BA/MA). The independent variables
are as follows: dummy variable equal to one if the firm has negative retained earnings and zero otherwise (NegRet);
dummy variable equal to one if the firm has zero debt and zero otherwise (Zero); dummy variable equal to one for IPO
year and zero otherwise (IPO); cash and equivalents divided by total assets (Cash); industry median debt ratio (Med);
marginal tax rate equal to the statutory tax rate if the firm reports no net operating loss carryforwards with positive pretax
return and zero otherwise (Tax); operating Income divided by total assets (OI); market-to-book ratio of assets (MB); log of
book value of total assets (LnA); depreciation and amortization divided by total assets (DEP); fixed assets divided by total
assets (FA); research and development expenditures divided by total assets (RND); a dummy variable for missing values
in RND (D_RND); and common stock dividends divided by total assets (DIV). T-statistics p-values are in the parentheses.
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.0684 0.1967 0.2055 0.3904 0.0956 0.1840 0.2272 0.3544
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
NegRet -0.0599 -0.0782 -0.0241 -0.0301
(0.0001) (0.0001) (0.0001) (0.0001)
Zero -0.1101 -0.1790 -0.0750 -0.1232
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0017 -0.0071 -0.0107 -0.0187
(0.2081) (0.0001) (0.0001) (0.0001)
Cash -0.1797 -0.2575 -0.1354 -0.1925
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.2816 0.2246 0.3232 0.2405 0.2803 0.2411 0.3221 0.2653
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax -0.0527 -0.0062 -0.0994 -0.0390 -0.0218 -0.0023 -0.0569 -0.0325
(0.0001) (0.0075) (0.0001) (0.0001) (0.0001) (0.2704) (0.0001) (0.0001)
OI -0.0248 0.0318 -0.1068 -0.0298 -0.0359 -0.0084 -0.0834 -0.0461
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0008) (0.0001) (0.0001)
MB -0.0119 -0.0076 -0.0184 -0.0113 -0.0310 -0.0269 -0.0466 -0.0403
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0155 0.0140 0.0073 0.0044 0.0116 0.0095 0.0052 0.0019
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
DEP -0.2086 -0.4138 -0.0395 -0.3319 -0.4373 -0.5609 -0.4252 -0.6026
(0.0001) (0.0001) (0.0264) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
FA 0.2106 0.1348 0.1792 0.0665 0.2069 0.1475 0.1812 0.0939
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.2185 -0.0390 -0.4682 -0.1984 -0.1514 -0.0188 -0.3325 -0.1345
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0049) (0.0001) (0.0001)
D_RND 0.0095 0.0159 0.0096 0.0191 0.0095 0.0143 0.0115 0.0185
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
DIV -2.2344 -1.9337 -2.4436 -2.0101 -1.9972 -1.8326 -2.3792 -2.1390
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Adjusted-R
2
0.2595 0.3412 0.2288 0.3715 0.3483 0.3916 0.3494 0.4229
Table VI
Parameter Estimates from Cross-sectional/Panel Regressions on Determinants of Leverage Ratio Subsamples
Divided by Firm Size and Postive/Negative Retained Earnings
The sample consists of Compustat firms from 1971 to 2005. The dependent variable is the total/long-term debt?? (TD/LD)
divided by book/market value of assets (BA/MA). The independent variables are as follows: retained earnings over total
assets (Retained); dummy variable equal to one if the firm has zero debt and zero otherwise (Zero); dummy variable equal
to one for IPO year and zero otherwise (IPO); cash and equivalents divided by total assets (Cash); industry median debt
ratio (Med); marginal tax rate equal to the statutory tax rate if the firm reports no net operating loss carryforwards with
positive pretax return and zero otherwise (Tax); operating Income divided by total assets (OI); market-to-book ratio of
assets (MB); log of book value of total assets (LnA); depreciation and amortization divided by total assets (DEP); fixed
assets divided by total assets (FA); research and development expenditures divided by total assets (RND); a dummy
variable for missing values in RND (D_RND); and common stock dividends divided by total assets (DIV). T-statistics p-
values are in the parentheses.
A. Small Firms with Positive Retained Earnings (Large = 0; posret = 1) (Obs = 35494)
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.0639 0.1805 0.2076 0.3939 0.0850 0.1896 0.2349 0.4052
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Retained -0.2159 -0.3101 -0.1779 -0.2526
(0.0001) (0.0001) (0.0001) (0.0001)
Zero -0.0760 -0.1270 -0.0638 -0.1073
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0137 -0.0178 -0.0212 -0.0303
(0.0001) (0.0001) (0.0001) (0.0001)
Cash -0.1197 -0.2076 -0.1118 -0.2002
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.1210 0.0690 0.1855 0.1007 0.1582 0.1136 0.2351 0.1608
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax 0.0095 0.0399 -0.0337 0.0095 0.0225 0.0487 -0.0157 0.0212
(0.0075) (0.0001) (0.0001) (0.0113) (0.0001) (0.0001) (0.0004) (0.0001)
OI -0.0207 0.0405 -0.0948 -0.0070 -0.0861 -0.0350 -0.1905 -0.1179
(0.0072) (0.0001) (0.0001) (0.3860) (0.0001) (0.0001) (0.0001) (0.0001)
MB -0.0167 -0.0139 -0.0242 -0.0185 -0.0339 -0.0306 -0.0508 -0.0442
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0132 0.0116 0.0040 0.0013 0.0150 0.0130 0.0081 0.0046
(0.0001) (0.0001) (0.0001) (0.0859) (0.0001) (0.0001) (0.0001) (0.0001)
DEP -0.6190 -0.5234 -0.7032 -0.5489 -0.5646 -0.4934 -0.6532 -0.5365
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
FA 0.3011 0.2059 0.2641 0.1047 0.2716 0.1867 0.2302 0.0847
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.2564 -0.1022 -0.5093 -0.2502 -0.2618 -0.1287 -0.5144 -0.2863
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
D_RND -0.0024 0.0018 0.0005 0.0084 -0.0028 0.0015 0.0008 0.0089
(0.1009) (0.1784) (0.7769) (0.0001) (0.0616) (0.2796) (0.6852) (0.0001)
DIV -1.8208 -0.5368 -2.6551 -0.7151 -1.7131 -0.6541 -2.4987 -0.9023
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Adjusted-R
2
0.2619 0.3992 0.2370 0.4635 0.3048 0.3960 0.3161 0.4602
B. Small Firms with Negative Retained Earnings (Large = 0; posret = 0) (Obs = 31550)
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.0690 0.1541 0.2211 0.3763 0.0679 0.1299 0.1884 0.3001
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Retained -0.0054 -0.0039 -0.0001 0.0040
(0.0001) (0.0001) (0.8748) (0.0001)
Zero -0.1025 -0.1929 -0.0588 -0.1129
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0066 -0.0208 -0.0120 -0.0283
(0.0150) (0.0001) (0.0001) (0.0001)
Cash -0.1582 -0.2705 -0.1094 -0.1836
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.1838 0.1322 0.2584 0.1674 0.1476 0.1149 0.1968 0.1396
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax 0.0072 0.0164 -0.0730 -0.0592 0.0091 0.0144 -0.0526 -0.0450
(0.5932) (0.2014) (0.0001) (0.0001) (0.3538) (0.1300) (0.0001) (0.0001)
OI 0.0399 0.0498 0.0019 0.0077 0.0425 0.0425 0.0318 0.0232
(0.0001) (0.0001) (0.7298) (0.1329) (0.0001) (0.0001) (0.0001) (0.0001)
MB -0.0058 -0.0021 -0.0135 -0.0063 -0.0163 -0.0135 -0.0316 -0.0261
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0075 0.0110 -0.0081 -0.0030 0.0092 0.0107 0.0033 0.0050
(0.0001) (0.0001) (0.0001) (0.0023) (0.0001) (0.0001) (0.0001) (0.0001)
DEP -0.0270 -0.2348 0.3195 -0.0171 -0.1033 -0.2199 0.0456 -0.1372
(0.3101) (0.0001) (0.0001) (0.5882) (0.0001) (0.0001) (0.0686) (0.0001)
FA 0.2320 0.1467 0.2174 0.0644 0.1658 0.1060 0.1581 0.0522
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.1222 -0.0032 -0.3443 -0.1239 -0.0924 -0.0080 -0.2395 -0.0846
(0.0001) (0.7796) (0.0001) (0.0001) (0.0001) (0.3492) (0.0001) (0.0001)
D_RND 0.0093 0.0112 0.0235 0.0270 0.0104 0.0120 0.0226 0.0254
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
DIV -0.1726 -0.1343 -0.6657 -0.5842 -0.4323 -0.3884 -1.0917 -1.0052
(0.2635) (0.3608) (0.0007) (0.0010) (0.0001) (0.0004) (0.0001) (0.0001)
Adjusted-R
2
0.1555 0.2350 0.1791 0.3340 0.2375 0.2901 0.2985 0.3955
C. Large Firms with Positive Retained Earnings (Large = 1; posret = 1) (Obs = 54508)
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.1719 0.3395 0.2606 0.4496 0.2292 0.3623 0.3363 0.4878
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Retained -0.3032 -0.3525 -0.2562 -0.2985
(0.0001) (0.0001) (0.0001) (0.0001)
Zero -0.0974 -0.1358 -0.0525 -0.0780
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0183 -0.0106 -0.0297 -0.0274
(0.0001) (0.0001) (0.0001) (0.0001)
Cash -0.1989 -0.2183 -0.1505 -0.1670
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.2559 0.1459 0.2970 0.1709 0.2692 0.1801 0.3181 0.2154
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax -0.0325 0.0183 -0.0356 0.0221 -0.0178 0.0259 -0.0178 0.0322
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
OI -0.1188 0.0336 -0.2254 -0.0464 -0.2435 -0.1156 -0.3822 -0.2320
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
MB -0.0196 -0.0109 -0.0253 -0.0148 -0.0426 -0.0366 -0.0539 -0.0465
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0055 -0.0009 0.0048 -0.0026 -0.0012 -0.0062 -0.0040 -0.0098
(0.0001) (0.0080) (0.0001) (0.0001) (0.0013) (0.0001) (0.0001) (0.0001)
DEP -0.5648 -0.4208 -0.6547 -0.4863 -0.7573 -0.6385 -0.8692 -0.7302
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
FA 0.2011 0.0998 0.1670 0.0520 0.2205 0.1433 0.1935 0.1053
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.4746 -0.1979 -0.5593 -0.2348 -0.2406 -0.0436 -0.3130 -0.0805
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0095) (0.0001) (0.0001)
D_RND 0.0044 0.0038 0.0026 0.0018 0.0073 0.0059 0.0062 0.0045
(0.0005) (0.0007) (0.0620) (0.1304) (0.0001) (0.0001) (0.0001) (0.0002)
DIV -2.0472 -0.8934 -1.9990 -0.6575 -1.7345 -0.7702 -1.8094 -0.6858
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Adjusted-R
2
0.3192 0.4639 0.3075 0.4833 0.4286 0.5126 0.4385 0.5312
D. Large Firms with Negative Retained Earnings (Large = 1; posret = 0) (Obs = 11218)
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.1334 0.2762 0.2916 0.4642 0.2018 0.3179 0.3453 0.4864
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Retained -0.0169 -0.0195 0.0081 0.0105
(0.0001) (0.0001) (0.0016) (0.0001)
Zero -0.2242 -0.2780 -0.1355 -0.1744
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0214 -0.0455 -0.0251 -0.0472
(0.0013) (0.0001) (0.0001) (0.0001)
Cash -0.2437 -0.2840 -0.1984 -0.2313
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.5824 0.4681 0.6110 0.4771 0.4289 0.3440 0.4485 0.3485
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax 0.0026 0.0116 -0.0148 -0.0002 -0.0452 -0.0385 -0.0674 -0.0560
(0.9151) (0.6214) (0.5532) (0.9926) (0.0181) (0.0379) (0.0006) (0.0028)
OI 0.2531 0.2028 0.1803 0.1173 0.1614 0.0980 0.0913 0.0124
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.4115)
MB -0.0094 0.0022 -0.0194 -0.0048 -0.0472 -0.0371 -0.0615 -0.0486
(0.0001) (0.2338) (0.0001) (0.0092) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0092 0.0028 -0.0033 -0.0113 0.0039 -0.0011 -0.0065 -0.0128
(0.0001) (0.0817) (0.0539) (0.0001) (0.0030) (0.3836) (0.0001) (0.0001)
DEP -0.0463 -0.1912 -0.0054 -0.1775 -0.2271 -0.2665 -0.2403 -0.2855
(0.4703) (0.0024) (0.9337) (0.0045) (0.0001) (0.0001) (0.0001) (0.0001)
FA 0.1438 0.0724 0.1584 0.0730 0.1527 0.0921 0.1701 0.0973
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.2450 -0.0309 -0.4524 -0.2108 -0.2313 -0.0461 -0.4071 -0.1967
(0.0001) (0.4336) (0.0001) (0.0001) (0.0001) (0.1376) (0.0001) (0.0001)
D_RND 0.0235 0.0231 0.0197 0.0191 0.0071 0.0074 0.0051 0.0053
(0.0001) (0.0001) (0.0001) (0.0001) (0.0712) (0.0499) (0.2111) (0.1697)
DIV -1.3241 -1.3598 -1.1891 -1.2291 -1.5774 -1.5930 -1.6544 -1.6728
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Adjusted-R
2
0.1963 0.2644 0.2243 0.3201 0.3040 0.3507 0.3620 0.4253
doc_698862373.pdf
Empirical studies in the capital structure find a positive relationship between firm size and leverage. Suggested explanations in the literature include: large firms tend to have more leverage perhaps because they are more transparent; have lower asset volatility; more diversified; naturally sell large enough debt issues so that the fixed costs of public borrowing are not prohibitive; have lower probability of default and less financial distress costs.
Financial Flexibility, Leverage, and Firm Size
1
by
Soku Byoun
Hankamer School of Business
Baylor University
One Bear Place 98004
Waco, TX 76798
Tel: (254) 710–7849
Fax: (710) 710-1092
Email: Soku [email protected]
January 2007
1
We would like to thank the GAMF. We appreciate the support for this project that was provided
by the Hankamer School of Business at Baylor University.
Financial Flexibility, Leverage, and Firm Size
Abstract
We ?nd that small ?rms have lower leverage ratios, not because of internally generated
funds or additional debt ?nancing (as implied by the pecking order theory) but because of
additional equity ?nancing (consistent with our ?nancial ?exibility hypothesis). This ?nd-
ing can be explained by neither of the pecking order theory and the tradeo? theory—the
pecking order may be reversed for small ?rms that prefer external equity to debt ?nancing
while the tradeo? theory may miss out some important aspects of capital structure deci-
sions. We argue that small ?rms maintain low leverage by issuing equity and building up
cash holdings for ?nancial ?exibility. Debt covenant often carry restrictions on ?nancing
and investment decisions that are especially cumbersome for small, growing ?rms. Equity
?nancing allows small ?rms to raise cash without impeding ?nancial ?exibility. Consistent
with this argument, we ?nd small ?rms build up cash holdings in order to preserve ?nancial
?exibility through external equity. Once we account for ?nancial ?exibility, the positive
relationship between ?rm size and leverage found in previous studies is unclear.
JEL Classi?cation: G32
Keywords: Financial Flexibility; Trade-o? theory; Pecking-order theory
I. Introduction
Empirical studies in the capital structure ?nd a positive relationship between ?rm size
and leverage.
1
Suggested explanations in the literature include: large ?rms tend to have
more leverage perhaps because they are more transparent; have lower asset volatility; more
diversi?ed; naturally sell large enough debt issues so that the ?xed costs of public borrowing
are not prohibitive; have lower probability of default and less ?nancial distress costs. On the
other hand, small ?rms incur higher costs of issuing debt or equity since they are subject to
severe asymmetric information problems and default risk, more likely to be growing ?rms
with volatile cash ?ows and hence have less access to external funds than do large ?rms.
Further, the costs of ?nancial distress are likely to be particularly severe for small ?rms
because much of their value comes from growth options whose value depreciates rapidly if
the ?rm experiences ?nancial distress. In addition, small ?rms have a large fraction of their
assets that are ?rm speci?c or intangible, limiting their value as collateral.
Given that small ?rms grow faster than large ?rms (Evans (1987)), there are two alter-
natives for small ?rms to have lower leverage; by ?nancing their growth either exclusively
through retained earnings or through external equity. Most explanations for the positive
relationship between ?rm size and leverage assume implicitly or explicitly that external
equity is prohibitively expensive for small ?rms and hence small ?rms’ ?nancing should
come exclusively from internal funds.
2
There is also evidence that ?rms prefer internal
?nancing to external ?nancing.
3
According to the pecking order theory (Myers and Ma-
jluf (1984)), adverse selection costs of external equity are much greater than those of debt.
1
For example, see Titman and Wessels (1988), Rajan and Zingales (1995), Graham,
Lemmon, and Schallheim (1998), Hovakimain, Opler, and Titman, (2001), Booth et al.
(2001) and Fama and French (2002). However, Faulkender and Petersen (2006) ?nd a weak
or negative relationship between the leverage and ?rm size.
2
See, for example, Frank and Goyal (2003), Leary and Roberts (2005), Strebulaev (2006),
and Kurshev and Strebulaev (2006) for such arguments.
3
See Hovakimian, Opler, and Titman (2001) and Hovakimian, Hovakimian, and Tehra-
nian (2004).
1
Issuance costs are also much greater for equity than for debt.
4
Facing such high adverse
selection/transaction costs, small ?rms should avoid issuing equity by all means. Hence
the literature has paid little attention to the potential role of external equity in relaxing
?nancing constraints of small ?rms in debt ?nancing.
We suggest the desire for “?nancial ?exibility” as an alternative explanation for small
?rms’ low leverage and yet their reliance on external equity ?nancing. Recently, the survey
results of Graham and Harvey (2001), Bancel and Mittoo (2004), and Brounen et al. (2004)
show that corporate managers explicitly express that they are mostly concerned about
“?nancial ?exibility” in their capital structure decisions. We ?rst examine the concept of
?nancial ?exibility closely, paying special attention to those features of ?exibility brought
to light by recent management and organization literatures. The term is very broad and has
many legitimate uses that need not be forced under a single de?nition. At the same time
it will be necessary to de?ne the term more clearly so as to avoid the confusion from its
various uses in the ?nance literature. Thus, we ?rst develop a concept of ?nancial ?exibility
and then investigate the relevance of ?nancial ?exibility to capital structure decisions.
We de?ne ?nancial ?exibility as the degree of capacity and speed at which the ?rm can
mobilize its ?nancial resources in order to take reactive, preventive and exploitive actions
to maximize the ?rm value. We are persuaded that all of the uses of ?exibility pertinent to
the ?nance literature are encompassed by its reactive, preventive and exploitive nature.
In view of ?nancial ?exibility, change in pro?t (especially loss) can be important determi-
nant of leverage. Speci?cally, ?rms with negative retained earnings (from the accumulation
of losses) are likely to have little ?nancial ?exibility and debt capacity but ample needs
for additional cash. Our main hypothesis is that ?rms with negative retained earnings are
more likely to issue equity to build up cash holdings in order to preserve ?nancial ?exibility
and hence have low leverage. The corollary to this hypothesis is that cash holdings will be
negatively associated with leverage. We also examine if small ?rms’ lower leverage can be
4
Altinkilic and Hansen (2000) ?nd that equity issuing costs are on average 5.38% of the
issue proceeds while debt issuing costs are on average 1.09%. Leary and Roberts (2005)
also report signi?cantly larger equity issuance costs.
2
explained by the consideration of ?nancial ?exibility focusing on the relationship between
?rm size and leverage.
We ?nd that large ?rms retain much more earnings than small ?rms and that low lever-
age for small ?rms results from external equity ?nancing rather than internal funds. While
small ?rms avoid debt ?nancing, they are much more active in tapping into external equity
capital. Firms with negative retained earnings have lower leverage ratios and issue several
times more equity than ?rms with positive retained earnings. We also ?nd that small ?rms
have negative retained earnings with more cash holdings than other ?rms. Thus, our ?nd-
ings are consistent with the argument that small ?rms build ?nancial ?exibility through cash
holdings and equity ?nancing to cope with their “abnormal” periods of earnings shortfalls
(DeAngelo and DeAngelo (2006)).
We further show that ?rm size has an overall strong and signi?cant positive association
with leverage ratios. However, the positive relationship between ?rm size and leverage ra-
tios are substantially weakened or reversed for large ?rms when we divide ?rms re-estimate
regressions for ?rms divided into small/large and positive/negative retained earnings. Also,
negative retained earnings dummy variables are associated with signi?cant and positive
coe?cient estimates, suggesting lower leverage ratios for ?rms with negative retained earn-
ings. On the other hand, when we include retained earnings as a continuous variable in
the subgroup regressions, positive retained earnings are signi?cantly and negatively asso-
ciated with leverage ratios, whereas negative retained earnings show less economically and
statistically signi?cant association with leverage ratios. Thus, our results show that ?rms
with negative retained earnings build up cash holdings through equity ?nancing, lowering
leverage ratios, whereas ?rms with more positive retained earnings also have lower leverage
ratios through the accumulation of earnings (as a means of building ?nancial ?exibility).
Overall, the relationship between leverage and ?rm size is not clear.
Our study brings new evidence to bear on an important issue in the capital structure
literature. The literature has wrestled with the problem of sorting out the e?ects of adverse
section costs of asymmetric information on capital structure.
5
On the one hand, the liter-
5
For example, see Myers and Majluf (1984), Viswanath (1993), Chang and Dasgupta
3
ature ?nds that larger ?rms tend to issue more debt relative to equity than smaller ?rms
and hence appear to provide a better ?t for the pecking order theory (Shyam-Sunder and
Myers (1999) and Frank and Goyal (2002)). On the other hand, our results show that small
?rms issue equity and raise up cash holdings despite having low leverage. Lemmon and
Zender (2004) provides a justi?cation for equity issuances that equity issuers are prevented
from issuing debt because of concerns over ?nancial distress or to preserve ?nancial slack
for future investment. Further, Fama and French (2002) and Leary and Roberts (2005a)
show that ?rms are more likely to use equity ?nancing as investment increases and/or cash
?ow decreases but the majority of equity ?nancings occur when ?rms still have su?cient
debt capacity to ?ll their investment needs. However, small ?rms in our sample appear to
issue equity and build up cash holdings in order to cope with abnormal earnings shortfalls
rather than to preserve ?nancial slack.
As an alternative explanation for violating the ?nancing hierarchy, Fama and French
(2005) and Leary and Roberts (2005a) suggest that ?rms are able to issue securities in
a manner that avoids the adverse selection costs associated with information asymmetry.
Alternatively, managers may time the market when information asymmetry, and the cor-
responding costs, are low so that deviations from the hierarchy do not incur a signi?cant
penalty.
6
Our ?ndings suggest that the external ?nancing hierarchy suggested by the peck-
ing order theory is revered due to the concern for ?nancial ?exibility. Consistent with our
evidence, Byoun (2006a) ?nds that small debt-free ?rms raise much external equity while
reducing debt and paying large dividend. Thus, ?nancial ?exibility can bear more impor-
tant relevance to capital structure decisions than the adverse selection costs of asymmetric
(2003), and Lemmon and Zender (2004) under the pecking order framework, and Frank
and Goyal (2003), Fama and French (2002), Barclay and Smith (2005), Leary and Roberts
(2005), Leary and Roberts (2005a), Strebulaev (2006) and Byoun (2006) under the tradeo?
framework.
6
Rajan and Zingales (1995), Jung, Kim, and Stulz (1996), Pagano, Panetta, and Zingales
(1998), Hovakimian, Opler, and Titman (2001), Baker and Wurgler (2002), and Leary
and Roberts (2005a)) examine managers’ market-timing attempts. The survey results in
Graham and Harvey (2001) suggest that managers issue equity following an increase in
stock price.
4
information.
Our ?ndings suggest that small ?rms have lower leverage ratios, not because of internally
generated funds or additional debt ?nancing (as implied by the pecking order theory) but
because of additional equity ?nancing (consistent with our ?nancial ?exibility hypothesis).
Small ?rms build up cash holdings in order to preserve ?nancial ?exibility through external
equity. Overall, asymmetric information falls short of providing a complete explanation for
motivation behind ?rms’ external ?nancing decisions. An alternative explanation should
include the bene?ts and costs of ?nancial ?exibility, which may require a substantial al-
teration to the tradeo? argument which is based only on traditional costs and bene?ts of
taxes, bankruptcy costs, agency costs, and transaction costs.
II. The Concept of Financial Flexibility: A Literature Review
The pecking order theory by Myers and Majluf (1984) assumes that ?rms desire
to maintain “?nancial slack” to avoid the need for external funds. However, ?nding that
managers value ?nancial ?exibility is not su?cient to prove that the pecking-order model
is the true description of capital structure choice (Opler et al., 1999). Graham and Harvey
(2001) make this point explicit:
The most important item a?ecting corporate debt decisions is management’s
desire for “?nancial ?exibility,”... However, the importance of ?exibility in the
survey responses is not related to informational asymmetry (size or dividend
payout) or growth options in the manner suggested by the pecking-order theory.
In fact, ?exibility is statistically more important for dividend-paying ?rms, op-
posite the theoretical prediction (if dividend-paying ?rms have relatively little
informational asymmetry). Therefore, a deeper investigation indicates that the
desire for ?nancial ?exibility is not driven by the factors behind the pecking-
order theory.
Despite managers’ contention that ?nancial ?exibility is an important factor in the
decision-making process of managers, the capital structure literature has to date remained
aloof to recognize and incorporate ?nancial ?exibility. Frank and Goyal (2005) reason, “the
5
stress on ?nancial ?exibility is interesting, but potentially open to a variety of interpre-
tations. In our view the survey evidence is of interest, but it is best regarded as being
interesting and suggestive, rather than providing de?nitive tests.” In addition to consid-
erable ambiguity in the use of the term, judgments about ?exibility are subjective and
informal and ?exibility levels are rarely monitored or even measured. Accordingly, dealing
with ?nancial ?exibility may be criticized as being less than practical and based on specu-
lation on the ability of a ?rm to respond to hypothetical future events. It is therefore not
surprising that there is relatively little systematic study of ?nancial ?exibility in the capital
structure literature.
7
Graham Harvey (2001) see ?nancial ?exibility as “preserving debt capacity to make
future expansions and acquisitions” or “minimizing interest obligations, so that they do not
need to shrink their business in case of an economic down turn.” Gamba and Triantis (2005),
in their attempt to model the value of ?nancial ?exibility, de?ne, ?nancial ?exibility as “the
ability of a ?rm to access and restructure its ?nancing with low transaction costs.” They
further elaborate by adding “?nancially ?exible ?rms are able to avoid ?nancial distress in
the face of negative shocks, and to fund investment at low cost when pro?table opportunities
arise.” Donaldson (1969, 1971) uses “?nancial mobility” to describe “the capacity to redirect
the use of ?nancial resources in a manner consistent with the evolving goals of management
as it responds to new information about the company and its environment.” Donaldson
particularly relates ?nancial mobility to capital structure decisions where the goal is to ?nd
the optimal mix of ?nancing sources.
Heath (1978) describes ?nancially ?exible company as one that can take corrective action
that will eliminate an excess of required cash payments over expected cash receipts quickly
and with minor adverse e?ect on its present and future earnings or on the market value of
its stock. The American Institute of Certi?ed Public Accountants (AICPA, 1993) adopts
Heath’s view by de?ning ?nancial ?exibility as “the ability to take action that will eliminate
7
In contrast, a branch of real options literature has been developed to deal with “in-
vestment ?exibility.” Gamba and Triantis (2005) note that most real options models are
designed to measure the value of “investment ?exibility” under the assumption of perfect
“?nancial ?exibility.”
6
an excess of required and expected cash payments over expected resources.” The Financial
Accounting Standards Board’s (FASB) de?nes ?nancial ?exibility as “the ability of an
entity to take e?ective actions to alter amounts and timing of cash ?ows so it can respond
to unexpected needs and opportunities.” Most of the treatments of ?nancial ?exibility in
the ?nance literature are more or less about the ability of a ?rm to meet its expected future
needs through large cash ?ow, large unused borrowing capabilities, or large liquid assets.
The importance of ?exibility in a ?rm is well recognized in management and organization
literature. Bueno-Campos (1992), Ahmed et al. (1996), Albizu-Gallastegui (1997), Hitt et
al. (1998) and Volberda (1998) de?ne “?exibility” as the ability to deliver cost-e?cient
responses quickly to changes in the business environment and to adapt and anticipate
changes that a?ect the goals of ?rms. There are other views from di?erent functional
areas of business (See Koornhof (1998) for a more detailed review on this). For example,
Pasmore (1994) view humans are the drivers of organization ?exibility. Harrigan (1985)
use the term “strategic ?exibility” to refer to a ?rm’s ability to reposition itself in markets,
change its game plan or dismantle its current strategies. Trigeorgis (1993) and Kulatilaka
(1993) use the term “operating ?exibility” to describe the ability of managers to revise
operating decisions in response to favorable opportunities or deteriorating conditions. This
includes switching from one project to another. Such operating options are critical when
the environment is highly volatile and technology is ?exible, thus permitting managerial
intervention at little cost.
Bernstein (1993) de?nes ?exibility as the ability of an enterprise to take steps to counter
unexpected interruptions in the ?ow of funds for reasons however unexpected. In this view,
?nancial ?exibility means the ability to borrow from a variety of sources, to raise equity
capital, to sell and redeploy assets, and to adjust the level and the direction of operations in
order to meet changing circumstances. Koornhof (1998) de?nes ?exibility as an ability to
take actions to reposition the resources and functions of the organization to new information
and environment in a manner consistent with the evolving vision, strategies and goals of
management.
The de?nitions of ?exibility as addressed in the management and organization litera-
7
tures recognize the “reactive” and “preventive” nature of ?exibility while failing to include
the “exploitive” nature of ?exibility for uncertain competitiveness or environment. The
combination of reactive, preventive, and exploitive nature of ?exibility is more evident in
Volberda (1998) who views ?exibility in two di?erent perspectives: internal ?exibility as
the ?rm’s capacity to adapt to the demands of the environment, while external ?exibility
as the ?rm’s capacity to in?uence their environment and thereby reduce their vulnerability.
Following the Volberda’s (1998) notion of ?exibility, we propose to regard the ?nancial
?exibility not as the passive accumulation of resources but as the degree of capacity and speed
at which the ?rm can mobilize its ?nancial resources in order to take reactive, preventive and
exploitive actions to maximize the ?rm value. The choice of ?nancial ?exibility is pragmatic
and avowedly relativistic; it is chosen because of its ability to bring the diverse uses of
?exibility into meaningful comparative relationships. Actions initiated ahead of time are
typically taken in anticipation of certain events, or in an attempt to change the rules of the
game. When expectations are not met, or when events occur that have not been predicted,
a ?rm may require ?exibility after the fact. In these cases, attempts are made to correct a
mistake or to capitalize on an unexpected opportunity. The point to note is that actions
taken ahead of time, even in the absence of a speci?c goal, can create options that can be
used at a later stage. When a new product unexpectedly becomes an industry standard (e.g.,
Apple’s iPod), resulting in a rapid expansion of the market demand, exploitive maneuvers
are important to focus resources and to rapidly capitalize on spontaneous opportunities. The
speed is critical. According to our de?nition, ?nancial ?exibility is a function of uncertainty;
not just about future cash ?ows but also about organization and environment. If the
business environment is more turbulent and competitive (development stage in the life
cycle), there will be more demand for ?exibility to cope the uncertainty. Flexibility arises
from a formal decision problem in which the choice from future options are a?ected by the
choice made now (Gerwin, 1993). In other words, the decision on ?exibility made in the
present impacts on the options management will have available in the future in response
to unforeseeable change. Financial ?exibility is future oriented. It would be fundamentally
inappropriate of a CFO of a company to say that his or her job is to maximize ?exibility for
8
the organization. Thus, maximizing the ?rm value should be the ultimate goal of optimizing
?nancial ?exibility.
It is apparent that certain aspects of ?nancial ?exibility have been addressed in the
literature. For example, Goldstein, Ju, and Leland (2001) note that a ?rm with low leverage
today preserves the subsequent option to increase leverage. Byoun (2006) ?nd evidence that
?rms preserve borrowing capacity to ?nance future investment or growth opportunities.
Graham (2000) shows that ?rms preserve debt capacity to make future expansions and
acquisitions. Motyka, Leuca, and Fawson (2005) also ?nd that ?nancial institutions hold
excess liquidity to cope with the unpredictable nature of loss (infrequent but high impact
risk) in order to achieve a competitive advantage for aggressive pricing and better margins.
III. Financial Flexibility and Leverage: the Hypotheses
DeAngelo and DeAngelo (2006) note that ?rms can develop potential sources of
future ?nancial ?exibility through cash accumulation, the preservation of debt capacity, and
equity payouts. According to their argument, in “normal” periods, mature ?rms maintain
low leverage and high payouts, thus preserving the ?rm’s option to borrow or issue equity in
the future while limiting agency costs on cash balances. In “abnormal” periods characterized
by unanticipated earnings shortfalls or pro?table new investment opportunities, the ?rm
issues securities, either debt or equity, depending on the trade-o? between bene?ts and
costs of issuing now versus preserving the option for the future. Thus, in view of ?nancial
?exibility, change in pro?t (especially loss) can be important determinant of leverage.
We identify ?rms in those “abnormal” periods of unanticipated earnings shortfalls ac-
cording to retained earnings. Retained earnings are accumulation of ?rms’ reinvested pro?ts
over time. Negative retained earnings re?ect ?rms’ earnings shortfalls over time. Even a
little debt may cause ?rms with negative retained earnings to be in ?nancial distress. The
limitation on debt issuance that results from the risk of asset substitution (Jensen and
Meckling (1976)) are more important for ?rms with negative retained earnings. Firms with
negative retained earnings lack investible funds for their pro?table investments and hence
sources of free cash ?ow tend to be relatively less for them, and thus reducing the ben-
9
e?t of debt that limits the scope of overinvestment and perquisites by managers (Jensen
(1986), Stulz (1990) and DeAngelo and DeAngelo (2006)). Hence the bene?ts of debt are
less helpful both in terms of the sources and uses of free cash ?ow. Another bene?t to the
use of leverage is its signal to the market about the quality or riskiness of the ?rm (Ross
(1977), Leland and Pyle (1977), and Heinkel (1982)). However, debt ?nancing renders ?rms
with negative earnings vulnerable to predatory strategies such as price wars by established
?rms to exhaust vulnerable ?rms ?nancially (Poitevin (1989)), thus deteriorating ?nancial
?exibility. In addition, debt covenant often carry restrictions on ?nancing and investment
decisions that are especially cumbersome for small, growing ?rms. Accordingly, small ?rms
with negative retained earnings have little incentive to use leverage to signal their quality.
Overall, small ?rms with negative retained earnings are likely to have little ?nancial
?exibility and debt capacity but ample needs for additional cash. On the other hand,
equity issues neither require collateral or restrictive covenants, nor accentuate moral hazard
problems that are associated with leverage, nor raise the probability of ?nancial distress.
Thus, our main hypothesis is that ?rms with negative retained earnings are more likely to
issue equity than debt and have low leverage than ?rms with positive retained earnings.
We also hypothesize that small ?rms’ lower leverage can be explained by ?nancial ?exibility
consideration.
A ?rm can also develop ?nancial ?exibility through cash accumulation (DeAngelo and
DeAngelo (2006)). On the one hand, cash holdings increase ?nancial ?exibility. On the
other hand, it increases agency costs. Leverage can mitigate agency costs, but leverage
in turn reduces future ?nancial ?exibility. As noted above, ?rms with negative earnings
are likely to be in need of ?nancial ?exibility while constrained in borrowing and with
little concern for agency costs and thus they can accumulate cash holdings through equity
?nancing in order to preserve ?nancial ?exibility. Accordingly, we expect that cash holdings
are negatively associated with leverage ratios.
II. Data
The initial sample consists of all available U.S. ?rms for the period of 1971–2005
from the annual Compustat ?les. Following previous studies, we exclude ?nancial ?rms and
10
regulated utilities from the sample.
8
We also require ?rms to have positive total assets,
book and market value of equity and net sales. These variables are used to de?ate other
variables and it is di?cult to interpret the results when they have non-positive values.
We also delete observations with missing or non-positive values for the number of shares
outstanding (Compustat item 25) and stock price at the end of the ?scal year (item 199).
Accordingly, we drop bout 8 % of ?rm-year observations in the sample that have non-positive
total assets market value of equity or net sales. After these requirements are applied, the
sample consists of 179,418 ?rm-year observations.
While Shyam-Sunder and Myers (1999) and Myers (1984) argue that there are rational
reasons for managers to specify debt targets in terms of book values, Titman and Wessels
(1988) and Welch (2004) are inclined toward the use of debt level measured at market value.
Accordingly, we estimate the models using total (item 9 + item 34) and long-term (item 9)
debt ratios measured with both book and market value of total assets.
III. Estimation and Results
A. Firm Size and Leverage
In order to examine the relationship between ?rm size and leverage, we divide the sam-
ple into size deciles each year and report the leverage ratios measured in long-term and total
debt to book/market value of assets. The market value of assets equals total assets (item 6)
minus total equity (item 216) minus balance sheet deferred taxes and investment tax credit
(item 35) plus the market value of common equity (price (item 199) times shares outstand-
ing (item 54)) plus preferred stock liquidating value (item 10, replaced by the redemption
value of preferred stock (Item 56) when missing).
9
We delete all observations with leverage
8
Financial ?rms are represented by SIC codes 6000-6799 and utilities by SIC codes 4800-
4999. These ?rms have very di?erent capital structures and their ?nancing decisions may
not convey the same information as non-?nancial and non-regulated ?rms. For example, a
relatively high leverage ratio is normal for ?nancial ?rms, but the same high leverage ratio
for non-?nancial ?rms may indicate possible ?nancial distress.
9
The results does not change when we exclude deferred taxes and investment tax credit
or include convertible debt (item 79) in the de?nition of book equity as in Alti (2006) and
Kayhan and Timan (2006).
11
ratios less than zero or greater than one.
10
We de?ne size in three di?erent ways based on
book value of total assets (item 6), market value of total assets and net sales (item 12), but
the results are similar and we report only those based on the book value of total assets.
Table I
Panel A of Table I shows that regardless of the various de?nitions of leverage ratios,
there is a positive relationship between ?rm size and leverage ratio especially for smaller
size deciles. However, the positive relationship between ?rm size and leverage is not clear
for ?rms in the largest three deciles. We also report the percentage of zero-debt ?rms in
each size decile. Small ?rms are associated with much more zero-debt ?rms than large ?rms.
Byoun (2007) suggests that zero-debt ?rms are constrained by debt market while uncon-
strained by equity market. In order to examine whether the negative relationship between
?rms size and leverage is driven by these zero-debt ?rms, we report the results excluding
zero-debt ?rms in Panel B of Table I. Even though the leverage ratios of small ?rms increase
without the zero-debt ?rms, the positive relationship between size and leverage ratio are
still present for smaller size deciles. Thus, our results con?rm that there exists fairly strong
positive relationship between ?rm size and leverage except for ?rms in the largest three
deciles in which the positive relationship is weakened or reversed.
Table II
Faulkender and Petersen (2006) argue that market frictions may cause ?rms to be
rationed by their lenders, leading some ?rms to appear under-levered relative to uncon-
strained ?rms. Thus, when estimating a ?rm’s leverage, it is important to include not only
10
Without this requirement, the average book leverage ratio of the sample ?rms in the
?rst size decile are greater (but market leverage ratios are smaller) than ?rms in larger size
deciles since there are a few ?rms with book leverage ratios greater than one in the ?rst
size decile. When we winsorize leverage ratios at 99 percentile, there still exist ?rms with
leverage ratios greater than one.
12
determinants of its desired leverage (the demand side) but also variables that measure the
constraints on a ?rm’s ability to increase its leverage (the supply side). Following Faulkender
and Petersen (2005) and Lemmon and Zender (2004) we use ?rms’ long-term credit ratings
(item 280) as a measure of accessibility to the public debt markets. Rating information is
available only from 1985. Accordingly we divide the sample into two subperiods into before
and after 1985, which also allows us to examine any discernable change in the relationship
between ?rm size and leverage. For the period of 1971-1984, the relationship between ?rm
size and leverage is positive and monotonic, whereas the relationship is weak or negative for
?rms in the largest three deciles for the period of 1985-2005. The results show that small
?rms rarely have long-term credit ratings and most ratings are concentrated in the largest
three deciles. The lack of available credit ratings for small ?rms may indicate that these
?rms have relatively less debt capacity and hence lower leverage.
Our results explain why Faulkender and Petersen (2006) ?nd a negative relationship
between leverage and ?rm size. The sample in Faulkender and Petersen (2006) includes
only ?rms with credit ratings that are mainly from the largest size deciles for the period
since 1985 and these ?rms show a weak or negative association between ?rm size and
leverage.
B. Firm Size, Cash Holdings, Retained Earnings and External Financing Ac-
tivities
In order to examine weather the lower leverage for small ?rms results from accumulated
internal equity (as suggested by the pecking order theory) or external equity (as suggested
by the ?nancial ?exibility hypothesis), we report retained earnings (item 36), net long-term
debt issue (item 111 - item 114), net total debt issue (item 111 ? item 114 ? item 301
if item 318 = 1 and item 111 ? item 114 + item 301, otherwise)
11
and net new equity
issue (item 108 - item 115) as proportions of total assets. We also examine the ratio of
11
Changes in current debt (item 301) represent an increase in working capital for format
code 1 but a decrease in working capital for format codes.
13
cash and marketable securities to total assets ([item 162 + item 193] / item 6)
12
. We drop
observations with missing values in any of the reported variables.
Table III
Table III reports the results. The results in Panel A show that small ?rms tend to
have more cash holdings while having less retained earnings than large ?rms. In fact, the
average retained earnings are negative for ?rms in smaller size deciles. Thus, small ?rms’
growth is not likely to come mainly from internal equity. Small ?rms’ long-term or total
debt ?nancing is miniscule compared to that of large ?rms. On the other hand, small ?rms’
equity ?nancing is phenomenal. The ?rms in the ?rst and second size deciles issue equity
on annual average 25% and 12% respectively of total assets.
Our results can be driven by IPO ?rms that are more likely to be in small size deciles. In
order to examine the IPO e?ects, we identify the IPO date from Compustat and designate
the ?rst ?scal year ending after the IPO date as a IPO year. We also identify the ?rst year
appearing in the Compustat for those that do not have IPO dates but the Computat begins
its coverage during our sample period and treat it like the IPO year. The results excluding
these IPO years are reported in Panel B. They show that the magnitude of external equity
raised by small ?rms become smaller without IPO years, but it is still signi?cantly greater
than that raised by larger ?rms.
Another possibility is that the results could be driven by a few outliers especially in
small size deciles. To address this concern we reproduce results with winsorization of the
equity ?nancing variable at 1st and 99th percentiles. Again the results in Panel C show
the same result that the small ?rms heavily rely on external equity with little debt. The
pattern remains intact but only with less magnitudes when we winsorize the variable with
greater cuto? percentiles.
Overall, ?rm size is negatively associated with cash and debt ?nancing whereas positively
12
Including accounts receivable (item 2) in addition to cash and marketable securities
produces almost identical results.
14
associated with retained earnings, equity issue and dividend payout ratio. Thus, small ?rms
appear to have lower leverage ratios, not because of internally generated funds or additional
debt ?nancing but because of additional equity ?nancing. Small ?rms also build up cash
holdings in order to preserve ?nancial ?exibility through external equity.
C. Firm Size, Retained Earnings and Leverage
In order to disentangle the relationship between ?rm size and leverage ratios while
accounting for the strong association of ?rm size with retained earnings, we ?rst examine
the leverage ratios for ?rms divided into negative and positive retained earnings groups
within each size decile.
Panel A of Table IV shows cash holdings, dividend, and leverage ratios for each group.
Interesting is the ?nding that the smaller ?rms (in size deciles below 6) with negative
retained earnings hold more cash balances than similar size ?rms with positive retained
earnings probably as a means of preserving ?nancial ?exibility. On the other hand, large
?rms with negative retained earnings tend to carry less cash balances with higher leverage
ratios than large ?rms with positive retained earnings. The market value leverage ratios
for ?rms with negative retained earnings are always smaller than book value leverage ratios
because negative retained earnings increase market value of total assets when we subtract
total equity from total assets to replace with the market value of equity. Since the portion
of negative retained earnings relative to total assets are signi?cantly greater for small decile
?rms, smaller ?rms (in 1 to 4 size deciles) with negative retained earnings have higher book
leverage ratios whereas lower market-value leverage ratios than ?rms with positive retained
earnings in the same size deciles. Thus, ?rms with negative retained earnings appear to
have higher book leverage ratios because of less total assets stemming from negative retained
earnings. The results suggest that the relationship between ?rm size and leverage within
smaller size deciles (less than decile 5) can depend on whether the leverage is measured
in terms of book or market value because of the signi?cant number of ?rms with negative
retained earnings. Firms with positive retained earnings pay higher dividend than ?rms
with negative retained earnings. Thus, there are important di?erences between positive
15
and negative retained earnings groups.
Panel B of Table IV shows that ?rms with negative retained earnings issue much more
equity than those with positive retained earnings. The larger equity issues of small ?rms
are driven by ?rms with negative retained earnings as they issue equity to raise cash while
maintaining ?nancial ?exibility. This ?nding is consistent with our hypothesis that small
?rms with negative retained earnings issue equity rather than debt to preserve ?nancial
?exibility. Larger ?rms with negative retained earnings tend to issue both debt and equity,
but their equity issues are signi?cantly greater than those of large ?rms with positive re-
tained earnings.
Table IV
D. Regression Results
We ?rst estimate regressions with variables typically used in previous cross-sectional
studies as well as additional variables we expect to have signi?cant impacts on leverage
ratios. The following ?rm and industry characteristic variables are included:
Retained = retained earnings divided by total assets;
NegRet = dummy variable equal to one for the year with negative retained earnings and
zero otherwise;
Zero = dummy variable equal to one for the year with zero debt and zero otherwise;
IPO = dummy variable equal to one for IPO year and zero otherwise;
Cash = Cash and equivalents divided by total assets;
Med = industry median debt ratio (based on two-digit SIC or Fama and French (2002)
industry groupings). According to Frank and Goyal (2004), the industry median
leverage is an important determinant of a ?rm’s leverage ratio, acting as a proxy for
several factors, including intangibility, regulation, stock variance, uniqueness, pur-
chasing manager’s sentiment index, etc.;
16
Tax = marginal tax rate equal to the statutory tax rate if the ?rm reports no net operating
loss carryforwards (item 52) with positive pretax return (item 170) and zero otherwise.
The statutory taxes are 48% from 1971 to 1978, 46% from 1979 to 1986, 40% in 1987,
34% from 1988 to 1992, and 35% from 1993 to 2003. Plesko (2003) shows that this
binary measure captures the marginal tax e?ects;
OI = operating income (item 13) divided by total assets (item 6). A ?rm with higher
earnings could prefer to operate with either lower or higher leverage. Lower leverage
might occur, as higher retained earnings mechanically reduce leverage, or if the ?rm
limits leverage to protect the franchise responsible for producing these high earnings.
Higher leverage might re?ect the ?rm’s ability to meet debt payments out of its
relatively high earnings cash ?ow;
MB = market-to-book ratio of assets.
13
A higher MB is generally taken as a sign of more
attractive future growth options, which a ?rm tends to protect by limiting its leverage;
LnA = log of total assets (item 6) as a measure of ?rm size. Larger ?rms tend to: have more
leverage (perhaps because they are more transparent); have lower asset volatility; or
naturally sell large enough debt issues so that the ?xed costs of public borrowing are
not prohibitive;
14
DEP = depreciation and amortization (item 14) as a proportion of total assets. Firms
with more depreciation expenses have less need for the interest deductions associated
with debt ?nancing;
FA = ?xed assets (item 8) divided by total assets. Firms operating with greater tangible
assets have a higher debt capacity;
13
The results do not change when we exclude deferred taxes and investment tax credit
or include convertible debt (item 79) in the de?nition of book equity (as in Alti (2006) and
Kayhan and Titman (2006)).
14
The results are not a?ected whether the size is de?ned in terms of market value of
assets or of net sales (item 12).
17
RND = research and development expenditures (item 46) divided by net sales (item 12).
RND can be taken as a proxy for future expected investment (Fama and French
(2002)). They also serve as an additional proxy for non-debt tax shields. We set
missing values as zero and include a dummy variable;
D RND = dummy variable that equals one for ?rms with missing RND and zero otherwise;
DIV = common stock dividends (item 127) divided by total assets. DIV controls for
possible trade-o? between debt and dividend in reducing agency costs of free cash
?ow (Fama and French (2002)); and
AZ = Altman’s Z-score modi?ed by MacKie-Mason (1990): (3.3EBIT (item 178) + sales
(item 12) + 1.4 retained earnings (item 36) + 1.2 working capital (item 4 - item 5))
divided by total assets. Altman’s Z-score measures the ex ante probability of distress
(Graham (1996, 2000)).
We winsorize all the variables de?ated by total assets at the 1st and 99th percentiles
except for industry median (Med), dividend (DIV ), and R&D (RND) which are winsorized
only at the 99th percentile because many ?rms have a value of zero for these variables.
Table V reports two sets of estimation results for each dependent variable, with and
without variables NegRet, Zero, IPO, and Cash. These additional variables are not
frequently used in previous studies and we want to see if the results are di?erent when they
are included. The coe?cient estimates on ?rm size (LnA) are highly signi?cant and positive
in all regressions. Thus, there is a fairly strong positive relationship between leverage and
?rm size even after controlling for the additional variables. All the other coe?cient estimates
are signi?cant with the same signs found in previous studies. When we include NegRet,
Zero, IPO and Cash, the coe?cient estimates on these variables are negative. This result
suggests that ?rms with negative retained earnings have signi?cantly lower leverage. Also,
?rms holding more cash balances tend to have lower leverage.
In order to further examine the e?ect of retained earnings on the relationship between
?rm size and leverage, we divide the ?rm into four groups: large/small ?rms (deciles greater
than/less than or equal to 5) with positive/negative retained earnings. The reasons we
18
divide ?rms this way are that the e?ect of negative retained earnings could be di?erent
between small and large ?rms and that in our previous results the relationship between
leverage and ?rm size is rather ambiguous for larger ?rms. We run the same regressions as
in Table V for these subgroups except that we replace the negative retained earnings dummy
variable with retained earnings (Retained) winsorized at the 1st and 99th percentiles.
The estimation results are reported in Table VI. The results show that the coe?cient
estimates on size (LnA) tend to be positive for small ?rms (in Panels A and B) but negative
or insigni?cant for large ?rms (in Panels C and D). Thus, the positive relationship between
?rm size and leverage holds true only for small ?rms. This ?nding is consistent with
the univariate results that show lower leverage ratios for the largest decile ?rms. The
coe?cient estimates on retained earnings (Retained) are highly signi?cant and negative for
?rms with positive retained earnings (in Panels A and C), whereas they are economically or
statistically insigni?cant for ?rms with negative retained earnings (in Panels B and D). As
we observed in Table IV, the e?ects of negative retained earnings are di?erent between book
and market value leverage ratios: negative retained earnings lower the book leverage, which
results in small negative coe?cient estimates on retained earnings in book-value-leverage-
ratio regressions; and negative retained earnings increase the market value leverage, which
results in small positive or insigni?cant coe?cient estimates on retained earnings in market-
value-leverage-ratio regressions.
Overall, our results suggest that the positive relationship between leverage and ?rm size
hold for small ?rms but not for large ?rms when we control for retained earnings which
measures the degree of ?nancial ?exibility. The ?rm size up to a certain level appears
to be important for leverage but its importance disappears once ?rms outgrow that level.
Small ?rms’ lower leverage ratios appear to result from their concern for ?nancial ?exibility
(issuing equity and building up cash holdings) and large ?rms with positive retained earnings
also have lower leverage as they accumulate internal funds to preserve ?nancial ?exibility
or to ?nance growth opportunities. Thus, the relationship between leverage and ?rm size
appears to be positive for small ?rms but negative for large ?rms.
19
VI. Summary and Conclusions
We examine the relationship between ?rm size and leverage in the view of ?nancial
?exibility. We de?ne ?nancial ?exibility as the degree of capacity and speed at which the
?rm can mobilize its ?nancial resources in order to take reactive, preventive and exploitive
actions to maximize the ?rm value. We hypothesize that ?rms with negative retained
earnings are likely to have little ?nancial ?exibility and debt capacity but ample needs
for additional cash. Accordingly, ?rms with negative retained earnings are more likely to
issue equity to build up cash holdings (a means of ?nancial ?exibility) and hence have low
leverage. The corollary to this hypothesis is that cash holdings will be negatively associated
with leverage. We also examine if we can explain the positive relationship between ?rm size
and leverage in the view of ?nancial ?exibility, given that many small ?rms have negative
retained earnings and are in need of ?nancial ?exibility.
Consistent with our hypothesis, ?rms with negative retained earnings issue several times
more equity than ?rms with positive retained earnings. While small ?rms avoid debt ?-
nancing, they are much more active in tapping into external equity capital. We also ?nd
that small ?rms often have negative retained earnings with no less cash holdings than other
?rms and that small ?rms with negative retained earnings have lower leverage than ?rms
with positive retained earnings.
We further show that ?rm size has an overall strong and signi?cant positive associa-
tion with leverage. However, the positive relationship between ?rm size and leverage are
substantially weakened or reversed for large ?rms when we control for retained earnings.
Our regression results, coupled with univariate results, suggest that small ?rms with neg-
ative retained earnings build up cash holdings through equity ?nancing, lowering leverage
ratios, whereas large ?rms with positive retained earnings accumulate earnings (as a means
of building ?nancial ?exibility), resulting in lower leverage ratios. Thus, the relationship
between leverage and ?rm size is unclear—we need more research on this issue. Overall,
small ?rms appear to have lower leverage ratios, not because of internally generated funds
or additional debt ?nancing but because of additional equity ?nancing. Small ?rms also
build up cash holdings in order to preserve ?nancial ?exibility through external equity.
20
This ?nding can be explained by neither of the pecking order theory and the tradeo?
theory—the pecking order may be reversed for small ?rms that prefer external equity to debt
?nancing while the tradeo? theory may miss out some important aspects of capital structure
decisions. In conclusion, the bene?ts and costs associated with ?nancial ?exibility in?uence
?rms’ capital structure decisions—but not in the manner hypothesized by the traditional
trade-o? theory. Thus, a substantial alteration may be required to the tradeo? argument
which is based only on traditional costs and bene?ts of taxes, bankruptcy costs, agency
costs, and transaction costs.
21
References
Almeida, Heitor and Murillo Campello, 2005, Firm ?nancing-investment interactions: Ev-
idence from debt and equity issues, New York University and University of Illinois
Working paper.
Alti, Aydogan, 2006, How persistent is the impact of market timing on capital structure,
Journal of Finance 61, 1681-1710.
Altinkilic O. and R.S. Hansen, 2000, Are there economies of scale in underwriter fees?
Evidence of rising external ?nancing costs, Review of Financial Studies 13(1), 191–
218.
Asquith, Paul and David W. Mullins, Jr., 1986, Equity issues and o?ering dilution, Journal
of Financial Economics 15, 61–89.
Baker, Malcolm and Je?rey Wurgler, 2002, Market timing and capital structure, Journal
of Finance 57, 1–32.
Baltagi, Badi H., 2001, Econometric Analysis of Panel Data, 2nd edition, John Wiley &
Sons.
Barclay, Michael J. and Cli?ord W. Smith, 2005, The capital structure puzzle: The evi-
dence revisited, Journal of Applied Corporate Finance 17(1), 8–17.
Berger, Phillip, Eli Ofek, and David Yermack, 1997, Managerial entrenchment and capital
structure decisions, Journal of Finance 52, 1411–1438.
Bharath, Sreedhar T., Paolo Pasquariello, Guojun Wu, 2006, Does asymmetric information
drive capital structure decisions?, University of Michigan working paper.
Byoun, Soku, 2006, How do ?rms adjust their capital structures? Baylor University Work-
ing Paper.
Byoun, Soku, 2006a, Why do some ?rms go debt-free? Baylor University Working Paper.
22
Calomiris, C.W. Hubbard, R.G., 1990, Firm Heterogeneity, Internal Finance and Credit
Rationing, Economic Journal 100, 90–104.
Calomiris, C., Himmelberg, C. P., and Wachtel, P., 1995, Commercial paper, corporate
?nance, and the business cycle, Carnegie-Rochester Conference Series on Public Policy
42 (June), 203-50.
Cantillo, M., and J. Wright, 2000, How do ?rms choose their lenders? An empirical
examination, Review of Financial Studies 13, 155-190.
Chang, X. and S. Dasgupta, 2003, Capital structure theories: Some new tests, Hong Kong
University of Science and Technology working paper.
DeAngelo H. and L. DeAngelo, 2006, Capital Structure, Payout Policy, and Financial
Flexibility, University of Southern California working paper.
Evans, D. 1987, Tests of alternative theories of ?rm growth, Journal of Political Economy
95, 657674.
Fama, E. F. and French, K. R., 2002, Testing trade-o? and pecking order predictions about
dividends and debt, Review of Financial Studies 15(1), 1–33.
Fama, Eugene F. and Kenneth R. French, 2005, Financing decisions: Who Issues Stock?,
Journal of Financial Economics 76, 549–582.
Fama, E. F. and MacBeth, J. D., 1973, Risk, return, and equilibrium: Empirical tests,
Journal of Political Economy 81, 607–636.
Faulkender, Michael, and Mitchell A. Petersen, 2006, Does the source of capital a?ect
capital structure?, forthcoming, Review of Financial Studies 19, 45–79.
Flannery, Mark J. and Kasturi P. Rangan, 2006, Partial Adjustment Toward Target Cap-
ital Structures, Journal of Financial Economics Forthcoming.
Frank, M. Z. and Vidhan K. Goyal, 2003, Testing the pecking order theory of capital
structure, Journal of Financial Economics 67(2), 217–248.
23
Frank, M. Z. and Vidhan K. Goyal, 2004, Capital structure decisions: Which factors are
reliably important? University of British Columbia working paper.
Frank, M. Z. and Vidhan K. Goyal, 2005, Trade-o? and Pecking Order Theories of Debt,
B. Espen Eckbo(ed.), Handbook of Corporate Finance: Empirical Corporate Finance
(Handbooks in Finance Series, Elsevier/North-Holland), Chapter 7.
Goldstein, H., 1995, Multilevel Statistical Models, Halsted Press, New York.
Goldstein, R. N. Ju, and H. Leland, 2001, An EBIT-based Model of Dynamic Capital
Structure, Journal of Business 74, 483–512.
Graham, John R., 1996, Debt and the marginal tax rate, Journal of Financial Economics
41, 41–73.
Graham, John R., 2000, How big are the tax bene?ts of debt? Journal of Finance 55,
1901–1941.
Graham, John R. and Campbell R. Harvey, 2001, The theory and practice of corporate
?nance: evidence from the ?eld, Journal of Financial Economics 61, 187–243.
Heinkel, R., 1982, A theory of capital structure relevance under imperfect information,
Journal of Finance 37, 1141-1150.
Hovakimian, Armen, Tim C. Opler, and Sheridan Titman, 2001, The debt-equity choice:
An analysis of issuing ?rms, Journal of Financial and Quantitative Analysis 36(1),
1–24.
Hovakimian, Armen, Gayane Hovakimian and Hassan Tehranian, 2004, Determinants of
target capital structure: The case of dual debt and equity issues, Journal of Financial
Economics 71, 517–540.
Jensen, M.C., 1986, Agency costs of free cash ?ow, corporate ?nance and takeovers, Amer-
ican Economic Review 76, 323-339.
24
Jensen, M.C. and W. Meckling, 1976, Theory of the ?rm: Managerial behavior, agency
costs, and capital ttructure, Journal of Financial Economics 3, 305-360.
Jung, Kooyul, Yong-Cheol Kim, and Rene M. Stulz, 1996, Timing, investment oppor-
tunities, managerial discretion, and the security issue decision, Journal of Financial
Economics 42, 159–185.
Kashyap, Anil K., Owen A. Lamont and Jeremy C. Stein, 1994, Credit Conditions and the
Cyclical Behavior of Inventories, Quarterly Journal of Economics 109 (3), 565-592.
Kayhan, Ayla and Sheridan Titman, 2006, Firms’ histories and their capital structures,
Journal of Financial Economics, forthcoming.
Leary, Mark T. and Michael R. Roberts, 2005, Do ?rms rebalance their capital structures?
Journal of Finance 60, 2575–2619.
Leary, Mark T. and Michael R. Roberts, 2005a, The Pecking Order, debt capacity, and
information asymmetry, Duke University and University of Pennsylvania working pa-
per.
Lee, Inmoo, Scott Lochhead, Jay Ritter, and Quanshui Zhao, 1996, The costs of rasing
capital, Journal of Financial Research 19 (1), 59-74.
Leland, H. and D. Pyle, 1977, Information asymmetries, ?nancial structure, and ?nancial
intermediation, Journal of Finance 32, 371-388.
Lemmon, Michael L. and Jaime F. Zender, 2004, Debt capacity and tests of capital struc-
ture theories. University of Utah and University of Colorado working paper.
Lemmon, Michael L., Michael Roberts, and Jaime F. Zender, 2006, Back to the beginning:
Persistence and the cross-section of corporate capital structure, University of Utah,
University of Pennsylvania and University of Colorado working paper.
Lewellen, Katharina , 2003, Financing Decisions When Managers Are Risk Averse, MIT
Sloan School of Management Working paper.
25
MacKie-Mason, J.K., 1990, Do taxes a?ect corporate ?nancing decisions? Journal of
Finance 45, 1471–1494.
Modigliani, Franco and Merton H. Miller, 1958, The cost of capital, corporation ?nance
and the theory of investment, American Economic Review 53, 261–297.
Myers, S.C., 1984, The Capital structure puzzle, Journal of Finance 39, 575–592.
Myers, S.C. and N.S. Majluf, 1984, Corporate ?nancing and investment decisions when
?rms have information that investors do not have, Journal of Financial Economics
13, 187–221.
Pagano, Marco, Fabio Panetta, and Luigi Zingales, 1998, Why do companies go public?
An empirical analysis, Journal of Finance 53, 27–64.
Petersen, Mitchell A., 2005, Estimating standard errors in ?nance panel data sets: Com-
paring approaches, Northwestern University working paper.
Plesko, George A., 2003, An evaluation of alternative measures of corporate tax rates,
Journal of Accounting and Economics 35, 201–226.
Poitevin, M., 1989, Financial signalling and the deep-pocket argument, Rand Journal of
Economics 20, 26-40.
Rajan, R.G. and L. Zingales, 1995, What do we know about capital structure? Some
evidence from international data, Journal of Finance 50, 1421–1460.
Ross, S., 1977, The determination of ?nancial structure: The incentive signalling approach,
Bell Journal of Economics 8, 23-40.
Shyam-Sunder, L. and S.C. Myers, 1999, Testing static trade-o? against pecking order
models of capital structure, Journal of Financial Economics 51, 219–244.
Strebulaev, Ilya, 2006, Do tests of capital structure theory mean what they say? Journal
of Finance, forthcoming.
26
Stulz, R., 1990, Managerial discretion and optimal ?nancing policies, Journal of Financial
Economics 26, 3-27.
Titman, S. and R. Wessels, 1988, The determinants of capital structure choice, Journal of
Finance 43, 1–19.
Viswanath, P. V., 1993, Strategic considerations, the pecking order hypothesis, and market
reactions to equity ?nancing, Journal of Financial and Quantitative Analysis 28, 213–
234.
Welch, Ivo, 2004, Capital structures and stock returns, Journal of Political Economy 112,
106–131.
Wooldridge, Je?rey W., 2002, Econometric Analysis of Cross Section and Panel Data,
Cambridge: The MIT Press.
27
Table I. Firm Size Deciles and Leverage Ratios
The data consists of 179,418 firm-year observations for the period 1971-2005. Observations with missing values in any of
the reported variables are deleted. Size is size deciles based on total assets. Book /Market Long-term/Total Debt is long-
term/total debt over book/market value of total assets. The market value of assets equals total assets minus total equity
minus balance sheet deferred taxes and investment tax credit plus the market value of common equity plus preferred stock
liquidating value. % of Firms with Zero Debt is the percentage of firms relative to the total number of firms in each size
decile. A zero-debt firm is a firm with no debt.
A. All firm-year observations (179,418)
Size Decile Total Assets
Book Long-
term Debt
Book Total
Debt
Market Long-
term Debt
Market Total
Debt
% of Firms
with Zero
Debt
1 3.62 0.0974 0.2074 0.0590 0.1164 0.2035
2 10.39 0.1241 0.2184 0.0943 0.1647 0.1578
3 21.66 0.1356 0.2186 0.1137 0.1828 0.1487
4 40.62 0.1452 0.2170 0.1295 0.1936 0.1480
5 71.75 0.1651 0.2286 0.1482 0.2062 0.1293
6 128.62 0.1916 0.2493 0.1687 0.2217 0.0994
7 240.64 0.2188 0.2725 0.1890 0.2378 0.0744
8 496.17 0.2437 0.2942 0.2089 0.2537 0.0445
9 1354.40 0.2476 0.2968 0.2125 0.2552 0.0299
10 15673.95 0.2387 0.3017 0.2138 0.2679 0.0063
B. Non-zero-debt firm-year observations (155,435)
Size Decile Total Assets
Book Long-
term Debt
Book Total
Debt
Market Long-
term Debt
Market Total
Debt
1 3.67 0.1223 0.2604 0.0741 0.1462
2 10.26 0.1474 0.2593 0.1120 0.1955
3 21.17 0.1593 0.2568 0.1335 0.2147
4 39.21 0.1704 0.2547 0.1520 0.2273
5 68.78 0.1896 0.2626 0.1702 0.2368
6 123.99 0.2127 0.2768 0.1873 0.2461
7 237.02 0.2364 0.2944 0.2042 0.2569
8 490.26 0.2550 0.3079 0.2187 0.2655
9 1347.74 0.2553 0.3060 0.2190 0.2630
10 15694.31 0.2402 0.3036 0.2151 0.2696
Table II. Firm Size Deciles and Leverage Ratios for Sub-periods Divided into Before and After 1985
The data consists of firm-year observations for the period 1971-2005. Observations with missing values in any of the
reported variables are deleted. Size is size deciles based on total assets. Book /Market Long-term/Total Debt is long-
term/total debt over book/market value of total assets. The market value of assets equals total assets minus total equity
minus balance sheet deferred taxes and investment tax credit plus the market value of common equity plus preferred stock
liquidating value. % of Firms with Zero Debt is the percentage of firms with no debt relative to the total number of firms
in each size decile. % of Firms with Bond Rating is the percentage of firms with long-term credit ratings relative to the
total number of firms in each size decile.
A. For 1971 – 1984 Period (53,702 Obs)
Size Decile
Total
Assets
Book Long-
term Debt
Book Total
Debt
Market
Long-term
Debt
Market
Total Debt
% of Firms
with Zero
Debt
1 4.19 0.1132 0.2046 0.0873 0.1525 0.1734
2 9.75 0.1481 0.2350 0.1345 0.2123 0.1034
3 17.06 0.1727 0.2552 0.1658 0.2453 0.0812
4 27.68 0.1923 0.2695 0.1939 0.2719 0.0594
5 44.14 0.2035 0.2750 0.2031 0.2754 0.0540
6 71.33 0.2193 0.2873 0.2189 0.2880 0.0352
7 122.58 0.2315 0.2941 0.2293 0.2926 0.0374
8 239.36 0.2326 0.2893 0.2322 0.2884 0.0239
9 631.22 0.2470 0.3008 0.2488 0.3016 0.0121
10 4276.30 0.2505 0.3044 0.2638 0.3172 0.0019
B. For 1985 – 2005 Period (119,813)
Size Decile
Total
Assets
Book Long-
term Debt
Book Total
Debt
Market
Long-term
Debt
Market
Total Debt
% of Firms
with Zero
Debt
% of Firms
with Credit
Rating
1 3.36 0.0903 0.2087 0.0463 0.1003 0.2170 0.0000
2 10.67 0.1134 0.2110 0.0763 0.1433 0.1822 0.0004
3 23.72 0.1190 0.2023 0.0903 0.1548 0.1790 0.0006
4 46.41 0.1241 0.1934 0.1006 0.1586 0.1877 0.0022
5 84.14 0.1479 0.2078 0.1236 0.1751 0.1631 0.0128
6 154.28 0.1792 0.2323 0.1461 0.1920 0.1282 0.0551
7 293.57 0.2131 0.2628 0.1709 0.2133 0.0910 0.1533
8 611.28 0.2486 0.2963 0.1985 0.2382 0.0538 0.3279
9 1678.72 0.2479 0.2950 0.1962 0.2343 0.0379 0.5758
10 20778.29 0.2334 0.3005 0.1914 0.2458 0.0083 0.7800
Table III. Firm Size Deciles, Cash Holdings, Retained Earnings and External Financing Activities
The data consists of firm-year observations for the period 1971-2005. Observations with missing values in any of the
reported variables are deleted. Size deciles are based on total assets. All the variables are reported as a proportion of total
assets.
A. All firm-year observations (173,515)
Size Decile
Cash and
Equivalents
Retained
Earnings
Net Long-
term Debt
Issue
Net Total
Debt Issue
Net New
Equity Issue Dividend
1 0.4141 -3.8807 0.0023 -0.0004 0.2527 0.0077
2 0.4012 -0.8725 0.0024 0.0027 0.1164 0.0068
3 0.3989 -0.4103 0.0007 0.0025 0.0852 0.0078
4 0.3958 -0.1390 0.0013 0.0024 0.0777 0.0083
5 0.3725 0.0244 0.0044 0.0059 0.0604 0.0093
6 0.3475 0.0961 0.0103 0.0113 0.0453 0.0097
7 0.3157 0.1656 0.0174 0.0183 0.0273 0.0117
8 0.2784 0.1940 0.0219 0.0229 0.0158 0.0136
9 0.2469 0.1995 0.0219 0.0227 0.0082 0.0170
10 0.2195 0.2102 0.0163 0.0172 0.0017 0.0193
B. Non-IPO firm-year observations (154,156)
Size Decile
Cash and
Equivalents
Retained
Earnings
Net Long-
term Debt
Issue
Net Total
Debt Issue
Net New
Equity Issue Dividend
1 0.4033 -4.4562 0.0010 -0.0016 0.1744 0.0083
2 0.3945 -0.9800 0.0015 0.0019 0.0771 0.0069
3 0.3910 -0.4492 0.0007 0.0030 0.0495 0.0074
4 0.3797 -0.1444 0.0038 0.0056 0.0357 0.0073
5 0.3615 0.0281 0.0066 0.0084 0.0283 0.0082
6 0.3426 0.1029 0.0125 0.0140 0.0230 0.0092
7 0.3146 0.1742 0.0174 0.0183 0.0153 0.0111
8 0.2791 0.2003 0.0218 0.0228 0.0096 0.0132
9 0.2473 0.2047 0.0212 0.0219 0.0046 0.0164
10 0.2187 0.2120 0.0160 0.0168 0.0004 0.0193
C. Non-IPO firm-year observations with winsoriation at 1 and 99 percentiles (151,058)
Size Decile
Cash and
Equivalents
Retained
Earnings
Net Long-
term Debt
Issue
Net Total
Debt Issue
Net New
Equity Issue Dividend
1 0.3976 -3.4280 0.0025 0.0017 0.0743 0.0086
2 0.3880 -0.8900 0.0019 0.0027 0.0541 0.0067
3 0.3870 -0.4281 0.0010 0.0040 0.0432 0.0073
4 0.3776 -0.1393 0.0037 0.0057 0.0346 0.0072
5 0.3599 0.0276 0.0064 0.0084 0.0289 0.0081
6 0.3411 0.1017 0.0119 0.0134 0.0248 0.0091
7 0.3140 0.1723 0.0168 0.0177 0.0177 0.0110
8 0.2784 0.1979 0.0214 0.0224 0.0122 0.0131
9 0.2469 0.2032 0.0206 0.0212 0.0073 0.0163
10 0.2181 0.2111 0.0156 0.0164 0.0021 0.0193
Table IV. Firm Size Deciles, Retained Earnings, Leverage, Financing Activities
The data consists of firm-year observations for the period 1971-2005. Observations with missing values in any of the
reported variables are deleted. Size deciles are based on total assets. Firms are divided into positive and negative retained
earnings groups within each size decile. All the variables are reported as a proportion of total assets.
A. Cash Holdings and Leverage
Size
Decile
Retained
Earnings
Cash and
Equivalents Dividend
Book Long-
term Debt
Book Total
Debt
Market
Long-term
Debt
Market
Total Debt
1 -5.2296 0.4144 0.0039 0.1014 0.2276 0.0521 0.1098
1 0.3082 0.4132 0.0195 0.0850 0.1447 0.0806 0.1370
2 -1.7479 0.4062 0.0051 0.1365 0.2508 0.0872 0.1619
2 0.3014 0.3944 0.0091 0.1074 0.1748 0.1039 0.1684
3 -1.2568 0.4267 0.0065 0.1439 0.2463 0.1021 0.1770
3 0.2991 0.3748 0.0089 0.1286 0.1952 0.1235 0.1877
4 -0.8691 0.4397 0.0043 0.1518 0.2370 0.1162 0.1832
4 0.2892 0.3688 0.0106 0.1412 0.2051 0.1374 0.1998
5 -0.6213 0.4221 0.0053 0.1872 0.2702 0.1468 0.2152
5 0.2934 0.3510 0.0111 0.1558 0.2111 0.1488 0.2023
6 -0.5084 0.3784 0.0039 0.2442 0.3198 0.1915 0.2548
6 0.2899 0.3371 0.0115 0.1745 0.2264 0.1612 0.2109
7 -0.4025 0.3146 0.0071 0.3214 0.3939 0.2471 0.3074
7 0.2968 0.3159 0.0127 0.1944 0.2437 0.1752 0.2213
8 -0.3103 0.2600 0.0087 0.3723 0.4357 0.2898 0.3442
8 0.2903 0.2823 0.0146 0.2177 0.2656 0.1926 0.2354
9 -0.3077 0.2327 0.0105 0.3787 0.4394 0.2920 0.3434
9 0.2747 0.2492 0.0180 0.2274 0.2748 0.2002 0.2415
10 -0.1789 0.1896 0.0097 0.3590 0.4179 0.2878 0.3378
10 0.2459 0.2226 0.0202 0.2271 0.2905 0.2067 0.2612
Total
B. External Financing Activities
Size
Decile
Retained
Earnings
Net Long-term
Debt Issue
Net Total Debt
Issue
Net New
Equity Issue
Number of
Obs
1 -5.2296 0.0029 0.0008 0.3227 12324
1 0.3082 0.0004 -0.0041 0.0348 3989
2 -1.7479 0.0027 0.0038 0.1766 9318
2 0.3014 0.0020 0.0012 0.0353 6891
3 -1.2568 -0.0039 -0.0008 0.1446 7426
3 0.2991 0.0045 0.0052 0.0348 8575
4 -0.8691 -0.0051 -0.0045 0.1465 6013
4 0.2892 0.0050 0.0065 0.0370 9764
5 -0.6213 -0.0049 -0.0033 0.1255 4744
5 0.2934 0.0083 0.0098 0.0330 10931
6 -0.5084 0.0039 0.0029 0.1051 3937
6 0.2899 0.0124 0.0141 0.0259 11657
7 -0.4025 0.0160 0.0168 0.0706 3059
7 0.2968 0.0177 0.0186 0.0170 12270
8 -0.3103 0.0196 0.0185 0.0483 2665
8 0.2903 0.0224 0.0239 0.0092 12551
9 -0.3077 0.0356 0.0344 0.0310 2102
9 0.2747 0.0197 0.0209 0.0047 12897
10 -0.1789 0.0209 0.0172 0.0165 1397
10 0.2459 0.0159 0.0172 0.0003 13324
Total 155834
Table V
Parameter Estimates from Cross-sectional/Panel Regressions on Determinants of Leverage Ratio
The sample consists of 146,553 firm-year observations with relevant Compustat data from 1971 to 2005. The dependent
variable is the total/long-term debt?? (TD/LD) divided by book/market value of assets (BA/MA). The independent variables
are as follows: dummy variable equal to one if the firm has negative retained earnings and zero otherwise (NegRet);
dummy variable equal to one if the firm has zero debt and zero otherwise (Zero); dummy variable equal to one for IPO
year and zero otherwise (IPO); cash and equivalents divided by total assets (Cash); industry median debt ratio (Med);
marginal tax rate equal to the statutory tax rate if the firm reports no net operating loss carryforwards with positive pretax
return and zero otherwise (Tax); operating Income divided by total assets (OI); market-to-book ratio of assets (MB); log of
book value of total assets (LnA); depreciation and amortization divided by total assets (DEP); fixed assets divided by total
assets (FA); research and development expenditures divided by total assets (RND); a dummy variable for missing values
in RND (D_RND); and common stock dividends divided by total assets (DIV). T-statistics p-values are in the parentheses.
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.0684 0.1967 0.2055 0.3904 0.0956 0.1840 0.2272 0.3544
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
NegRet -0.0599 -0.0782 -0.0241 -0.0301
(0.0001) (0.0001) (0.0001) (0.0001)
Zero -0.1101 -0.1790 -0.0750 -0.1232
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0017 -0.0071 -0.0107 -0.0187
(0.2081) (0.0001) (0.0001) (0.0001)
Cash -0.1797 -0.2575 -0.1354 -0.1925
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.2816 0.2246 0.3232 0.2405 0.2803 0.2411 0.3221 0.2653
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax -0.0527 -0.0062 -0.0994 -0.0390 -0.0218 -0.0023 -0.0569 -0.0325
(0.0001) (0.0075) (0.0001) (0.0001) (0.0001) (0.2704) (0.0001) (0.0001)
OI -0.0248 0.0318 -0.1068 -0.0298 -0.0359 -0.0084 -0.0834 -0.0461
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0008) (0.0001) (0.0001)
MB -0.0119 -0.0076 -0.0184 -0.0113 -0.0310 -0.0269 -0.0466 -0.0403
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0155 0.0140 0.0073 0.0044 0.0116 0.0095 0.0052 0.0019
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
DEP -0.2086 -0.4138 -0.0395 -0.3319 -0.4373 -0.5609 -0.4252 -0.6026
(0.0001) (0.0001) (0.0264) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
FA 0.2106 0.1348 0.1792 0.0665 0.2069 0.1475 0.1812 0.0939
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.2185 -0.0390 -0.4682 -0.1984 -0.1514 -0.0188 -0.3325 -0.1345
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0049) (0.0001) (0.0001)
D_RND 0.0095 0.0159 0.0096 0.0191 0.0095 0.0143 0.0115 0.0185
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
DIV -2.2344 -1.9337 -2.4436 -2.0101 -1.9972 -1.8326 -2.3792 -2.1390
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Adjusted-R
2
0.2595 0.3412 0.2288 0.3715 0.3483 0.3916 0.3494 0.4229
Table VI
Parameter Estimates from Cross-sectional/Panel Regressions on Determinants of Leverage Ratio Subsamples
Divided by Firm Size and Postive/Negative Retained Earnings
The sample consists of Compustat firms from 1971 to 2005. The dependent variable is the total/long-term debt?? (TD/LD)
divided by book/market value of assets (BA/MA). The independent variables are as follows: retained earnings over total
assets (Retained); dummy variable equal to one if the firm has zero debt and zero otherwise (Zero); dummy variable equal
to one for IPO year and zero otherwise (IPO); cash and equivalents divided by total assets (Cash); industry median debt
ratio (Med); marginal tax rate equal to the statutory tax rate if the firm reports no net operating loss carryforwards with
positive pretax return and zero otherwise (Tax); operating Income divided by total assets (OI); market-to-book ratio of
assets (MB); log of book value of total assets (LnA); depreciation and amortization divided by total assets (DEP); fixed
assets divided by total assets (FA); research and development expenditures divided by total assets (RND); a dummy
variable for missing values in RND (D_RND); and common stock dividends divided by total assets (DIV). T-statistics p-
values are in the parentheses.
A. Small Firms with Positive Retained Earnings (Large = 0; posret = 1) (Obs = 35494)
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.0639 0.1805 0.2076 0.3939 0.0850 0.1896 0.2349 0.4052
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Retained -0.2159 -0.3101 -0.1779 -0.2526
(0.0001) (0.0001) (0.0001) (0.0001)
Zero -0.0760 -0.1270 -0.0638 -0.1073
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0137 -0.0178 -0.0212 -0.0303
(0.0001) (0.0001) (0.0001) (0.0001)
Cash -0.1197 -0.2076 -0.1118 -0.2002
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.1210 0.0690 0.1855 0.1007 0.1582 0.1136 0.2351 0.1608
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax 0.0095 0.0399 -0.0337 0.0095 0.0225 0.0487 -0.0157 0.0212
(0.0075) (0.0001) (0.0001) (0.0113) (0.0001) (0.0001) (0.0004) (0.0001)
OI -0.0207 0.0405 -0.0948 -0.0070 -0.0861 -0.0350 -0.1905 -0.1179
(0.0072) (0.0001) (0.0001) (0.3860) (0.0001) (0.0001) (0.0001) (0.0001)
MB -0.0167 -0.0139 -0.0242 -0.0185 -0.0339 -0.0306 -0.0508 -0.0442
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0132 0.0116 0.0040 0.0013 0.0150 0.0130 0.0081 0.0046
(0.0001) (0.0001) (0.0001) (0.0859) (0.0001) (0.0001) (0.0001) (0.0001)
DEP -0.6190 -0.5234 -0.7032 -0.5489 -0.5646 -0.4934 -0.6532 -0.5365
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
FA 0.3011 0.2059 0.2641 0.1047 0.2716 0.1867 0.2302 0.0847
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.2564 -0.1022 -0.5093 -0.2502 -0.2618 -0.1287 -0.5144 -0.2863
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
D_RND -0.0024 0.0018 0.0005 0.0084 -0.0028 0.0015 0.0008 0.0089
(0.1009) (0.1784) (0.7769) (0.0001) (0.0616) (0.2796) (0.6852) (0.0001)
DIV -1.8208 -0.5368 -2.6551 -0.7151 -1.7131 -0.6541 -2.4987 -0.9023
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Adjusted-R
2
0.2619 0.3992 0.2370 0.4635 0.3048 0.3960 0.3161 0.4602
B. Small Firms with Negative Retained Earnings (Large = 0; posret = 0) (Obs = 31550)
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.0690 0.1541 0.2211 0.3763 0.0679 0.1299 0.1884 0.3001
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Retained -0.0054 -0.0039 -0.0001 0.0040
(0.0001) (0.0001) (0.8748) (0.0001)
Zero -0.1025 -0.1929 -0.0588 -0.1129
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0066 -0.0208 -0.0120 -0.0283
(0.0150) (0.0001) (0.0001) (0.0001)
Cash -0.1582 -0.2705 -0.1094 -0.1836
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.1838 0.1322 0.2584 0.1674 0.1476 0.1149 0.1968 0.1396
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax 0.0072 0.0164 -0.0730 -0.0592 0.0091 0.0144 -0.0526 -0.0450
(0.5932) (0.2014) (0.0001) (0.0001) (0.3538) (0.1300) (0.0001) (0.0001)
OI 0.0399 0.0498 0.0019 0.0077 0.0425 0.0425 0.0318 0.0232
(0.0001) (0.0001) (0.7298) (0.1329) (0.0001) (0.0001) (0.0001) (0.0001)
MB -0.0058 -0.0021 -0.0135 -0.0063 -0.0163 -0.0135 -0.0316 -0.0261
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0075 0.0110 -0.0081 -0.0030 0.0092 0.0107 0.0033 0.0050
(0.0001) (0.0001) (0.0001) (0.0023) (0.0001) (0.0001) (0.0001) (0.0001)
DEP -0.0270 -0.2348 0.3195 -0.0171 -0.1033 -0.2199 0.0456 -0.1372
(0.3101) (0.0001) (0.0001) (0.5882) (0.0001) (0.0001) (0.0686) (0.0001)
FA 0.2320 0.1467 0.2174 0.0644 0.1658 0.1060 0.1581 0.0522
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.1222 -0.0032 -0.3443 -0.1239 -0.0924 -0.0080 -0.2395 -0.0846
(0.0001) (0.7796) (0.0001) (0.0001) (0.0001) (0.3492) (0.0001) (0.0001)
D_RND 0.0093 0.0112 0.0235 0.0270 0.0104 0.0120 0.0226 0.0254
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
DIV -0.1726 -0.1343 -0.6657 -0.5842 -0.4323 -0.3884 -1.0917 -1.0052
(0.2635) (0.3608) (0.0007) (0.0010) (0.0001) (0.0004) (0.0001) (0.0001)
Adjusted-R
2
0.1555 0.2350 0.1791 0.3340 0.2375 0.2901 0.2985 0.3955
C. Large Firms with Positive Retained Earnings (Large = 1; posret = 1) (Obs = 54508)
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.1719 0.3395 0.2606 0.4496 0.2292 0.3623 0.3363 0.4878
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Retained -0.3032 -0.3525 -0.2562 -0.2985
(0.0001) (0.0001) (0.0001) (0.0001)
Zero -0.0974 -0.1358 -0.0525 -0.0780
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0183 -0.0106 -0.0297 -0.0274
(0.0001) (0.0001) (0.0001) (0.0001)
Cash -0.1989 -0.2183 -0.1505 -0.1670
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.2559 0.1459 0.2970 0.1709 0.2692 0.1801 0.3181 0.2154
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax -0.0325 0.0183 -0.0356 0.0221 -0.0178 0.0259 -0.0178 0.0322
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
OI -0.1188 0.0336 -0.2254 -0.0464 -0.2435 -0.1156 -0.3822 -0.2320
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
MB -0.0196 -0.0109 -0.0253 -0.0148 -0.0426 -0.0366 -0.0539 -0.0465
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0055 -0.0009 0.0048 -0.0026 -0.0012 -0.0062 -0.0040 -0.0098
(0.0001) (0.0080) (0.0001) (0.0001) (0.0013) (0.0001) (0.0001) (0.0001)
DEP -0.5648 -0.4208 -0.6547 -0.4863 -0.7573 -0.6385 -0.8692 -0.7302
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
FA 0.2011 0.0998 0.1670 0.0520 0.2205 0.1433 0.1935 0.1053
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.4746 -0.1979 -0.5593 -0.2348 -0.2406 -0.0436 -0.3130 -0.0805
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0095) (0.0001) (0.0001)
D_RND 0.0044 0.0038 0.0026 0.0018 0.0073 0.0059 0.0062 0.0045
(0.0005) (0.0007) (0.0620) (0.1304) (0.0001) (0.0001) (0.0001) (0.0002)
DIV -2.0472 -0.8934 -1.9990 -0.6575 -1.7345 -0.7702 -1.8094 -0.6858
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Adjusted-R
2
0.3192 0.4639 0.3075 0.4833 0.4286 0.5126 0.4385 0.5312
D. Large Firms with Negative Retained Earnings (Large = 1; posret = 0) (Obs = 11218)
Independent
Variable
LD / BA TD / BA LD /MA TD / MA
Constant 0.1334 0.2762 0.2916 0.4642 0.2018 0.3179 0.3453 0.4864
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Retained -0.0169 -0.0195 0.0081 0.0105
(0.0001) (0.0001) (0.0016) (0.0001)
Zero -0.2242 -0.2780 -0.1355 -0.1744
(0.0001) (0.0001) (0.0001) (0.0001)
IPO -0.0214 -0.0455 -0.0251 -0.0472
(0.0013) (0.0001) (0.0001) (0.0001)
Cash -0.2437 -0.2840 -0.1984 -0.2313
(0.0001) (0.0001) (0.0001) (0.0001)
Med 0.5824 0.4681 0.6110 0.4771 0.4289 0.3440 0.4485 0.3485
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Tax 0.0026 0.0116 -0.0148 -0.0002 -0.0452 -0.0385 -0.0674 -0.0560
(0.9151) (0.6214) (0.5532) (0.9926) (0.0181) (0.0379) (0.0006) (0.0028)
OI 0.2531 0.2028 0.1803 0.1173 0.1614 0.0980 0.0913 0.0124
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.4115)
MB -0.0094 0.0022 -0.0194 -0.0048 -0.0472 -0.0371 -0.0615 -0.0486
(0.0001) (0.2338) (0.0001) (0.0092) (0.0001) (0.0001) (0.0001) (0.0001)
LnA 0.0092 0.0028 -0.0033 -0.0113 0.0039 -0.0011 -0.0065 -0.0128
(0.0001) (0.0817) (0.0539) (0.0001) (0.0030) (0.3836) (0.0001) (0.0001)
DEP -0.0463 -0.1912 -0.0054 -0.1775 -0.2271 -0.2665 -0.2403 -0.2855
(0.4703) (0.0024) (0.9337) (0.0045) (0.0001) (0.0001) (0.0001) (0.0001)
FA 0.1438 0.0724 0.1584 0.0730 0.1527 0.0921 0.1701 0.0973
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
RND -0.2450 -0.0309 -0.4524 -0.2108 -0.2313 -0.0461 -0.4071 -0.1967
(0.0001) (0.4336) (0.0001) (0.0001) (0.0001) (0.1376) (0.0001) (0.0001)
D_RND 0.0235 0.0231 0.0197 0.0191 0.0071 0.0074 0.0051 0.0053
(0.0001) (0.0001) (0.0001) (0.0001) (0.0712) (0.0499) (0.2111) (0.1697)
DIV -1.3241 -1.3598 -1.1891 -1.2291 -1.5774 -1.5930 -1.6544 -1.6728
(0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001) (0.0001)
Adjusted-R
2
0.1963 0.2644 0.2243 0.3201 0.3040 0.3507 0.3620 0.4253
doc_698862373.pdf