Electronic copy available at: http://ssrn.com/abstract=1863629

The Profits-Leverage Puzzle Revisited∗

Murray Z. Frank† Vidhan K. Goyal‡

May 26, 2011

ABSTRACT

It is well known that in a leverage regression, profits are negatively related toleverage. The literature (e.g., Myers, 1993; Fama and French, 2002) considers thisto be a key rejection of the trade-off theory. We disagree. Contrary to Myers (1993),highly profitable firms typically issue debt and repurchase equity, while the lowestprofit firms tend to raise external funds – particularly equity. The typical issuanceis in the direction predicted by the trade-off. It is also true that more profitablefirms experience an increase in both the book value of equity and the market valueof equity. The effect of profits on equity drives the negative coefficient in the usualleverage regression, thus giving a misleading impression. Transaction costs may beimportant because we find that large firms make more active use of debt, whilesmall firms make more active use of equity. Furthermore, poor market conditionslead to reduced use of external finance. The impact is particularly strong on smalland low profit firms.

JEL classification: G32

Keywords: Capital structure, Trade-off theory, Profits, Agency theory, Leverageratios

∗We thank Raj Aggarwal, Mark Flannery, Fangjian Fu, Paul Povel, Jay Ritter, Philip Strahan, IlyaStrebulaev, Michael Roberts, as well as seminar audiences at the 2009 AFA, Universita Bocconi, BostonCollege, City University of Hong Kong, University of Florida, Imperial College, Korea University, Univer-sity of Minnesota, University of Pittsburgh, Oxford University, and Singapore Management Universityfor helpful comments. Murray Z. Frank thanks Piper Jaffray for financial support. Vidhan K. Goyalthanks the Research Grants Council of Hong Kong for financial support (Project #641608). We aloneare responsible for any errors. c© 2011 by Murray Z.Frank and Vidhan K. Goyal. All rights reserved.†Murray Z. Frank, Carlson School of Management, University of Minnesota, Minneapolis, MN 55455.

Tel.: (612) 625-5678. murra280@umn.edu‡Vidhan K. Goyal, Department of Finance, Hong Kong University of Science and Technology, Clear

Water Bay, Kowloon, Hong Kong. Tel.: +852 2358-7678. goyal@ust.hk

Electronic copy available at: http://ssrn.com/abstract=1863629

I. Introduction

The trade-off theory of capital structure predicts that more profitable firms ought

to borrow more and have higher leverage.1 The profits-leverage puzzle is the empirical

evidence that the predicted sign is backwards. “The most telling evidence against the

static trade-off theory is the strong inverse correlation between profitability and financial

leverage. Within an industry, the most profitable firms borrow less, the least profitable

borrow more” (Myers, 1993, page 6). This relationship between corporate profits and

leverage is widely regarded as a particularly serious defect of the trade-off theory (e.g.

Fama and French (2002)).

In this paper we revisit the profits-leverage relationship. We show that the standard

empirical methodology has interacted with the usual approach to simplifying the theory,

in a particularly misleading way. The empirical methodology has focused on leverage

ratios, but interpreted them as if they were the result of debt market actions. In fact,

the equity component is very important when considering the impact of profits on firm

capital structure empirically. The theory has focused on intuition derived from static

models with inadequate attention given to the dynamic impact of the form of transaction

costs.2

The empirical problem arises in the standard leverage regression. To see this, let D

denote corporate debt and E corporate equity, then leverage is L = DD+E

. Let xit denote a

factor such as profits, with the subscript i for each firm, and t for the date. Let εit denote

the error term, and α and β be the coefficients to be estimated. It is common to run a

panel regression such as Lit = α + βxit + εit. If xit is profits, then under the trade-off

theory a more profitable firm has a greater need to shield profits from taxation, and so

1The term ‘trade-off theory’ is used in different ways by different authors. For some authors it meansthat bankruptcy and taxes are being balanced (Kraus and Litzenberger, 1973). For other authors itincludes agency-based arguments (Fama and French, 2002). Some authors simplify by assuming thatinvestment is unaffected, even though the cost of capital is changed by the leverage choice. Other authorsactually analyze the impact of the leverage choice on investment. A recent review is provided by Frankand Goyal (2008).

2Our point is related to that in Leary and Roberts (2005). The difference is that we focus on profitsand we emphasize the importance of the simultaneous presence of fixed and variable transactions costs.

1

it is predicted that β > 0. Empirically, however, β < 0, and so the trade-off theory is

rejected. This rejection is the profits-leverage puzzle.

This rejection could arise if the trade-off theory is indeed wrong. This is the usual

interpretation. But the rejection could arise for a number of other reasons too. It could

come from debt or from equity. It could come from corporate inaction, action in the

wrong direction, or simply action that is in the right direction but not strong enough.

The standard interpretation is that the regression result is due to more profitable firms

borrowing less. We will show that this is actually incorrect.

We present a sequence of closely related analyses that decomposes the standard re-

gression. We start by replicating the standard leverage regression and showing that the

standard result continues to hold in more recent data. The standard result holds for both

book- and market-based definitions of leverage.

Since our goal is to trace the source of the ‘incorrect’ sign on profits, we begin with

simple sorts (firm size and profits) and descriptive statistics. In this way, we document

the frequency and magnitude of various capital structure rebalancing actions. The general

pattern is that more profitable firms tend to issue more debt and are much more likely to

repurchase equity. On the contrary, the lowest profit firms tend to retire debt and raise

more equity capital.

These basic patterns are very much in line with the traditional interpretation of the

static trade-off theory, but contradict the profits-leverage puzzle. So the next task is

to reconcile these findings with the standard leverage regression results. To that end

we examine the impacts of alternative conditioning factors, fixed firm effects, fixed year

effects, alternative standard error assumptions, the use of changes instead of levels, and

alternative normalizations of the issuing regressions.

We find that the defect is not with the theory, but with the use of scaled measures

of leverage in which profitability can affect both the numerator and the denominator

of the ratio. This makes the sign of the relationship between leverage and profitability

theoretically ambiguous.

The main findings are as given below.

2

1. When a firm makes extra profits, the book value of equity increases unless the firm

takes some sort of offsetting action. Similarly, when a firm makes extra profits,

unless there is some sort of offsetting action, the market value of the firm’s equity

increases. Thus more profitable firms will automatically have more book equity and

more market equity, unless the firm takes offsetting actions.

2. Among large firms: The highest profit firms increase their debt the most. Those

with high profits experience large increases in both the book and the market value

of equity. The highest profit firms tend to repurchase equity while the lowest profit

firms tend to issue more equity.

3. Among small firms: Profit seems to have only a very minor effect on debt. Those

with high profits experience some increases in both the book and the market value of

equity. Those with low profits experience negative effects on market equity. There

is a tendency to issue equity, with the lowest profit firms issuing the most equity.

4. Almost any optimizing model of an interior optimal capital structure will imply that

the use of debt and equity will vary as market conditions vary. Empirically there is

time variation in the corporate use of external financing. In good times, firms issue

more net debt and net equity than in bad times. In particular, issuing equity in bad

times is more of a problem than issuing equity in good times. The negative effect

of profits on equity issuing is much stronger in good times than in bad times.

5. When firms adjust leverage, the magnitude of the adjustment is not sufficient to

fully undo the impact of the underlying shocks. Firms do not return to a unique

static optimum. They seem to ‘underadjust’. In section VII we show that this is

exactly what ought to be expected in a trade-off model in which there are both fixed

and variable costs of adjustment. Full adjustment is costly so partial adjustment is

typical as the firm balances the costs and benefits at the margin.

There is a huge prior literature on our topic, and so we cannot review all related

studies. For a review of the literature see Frank and Goyal (2008). The fact that there is

3

an inverse relationship between profitability and leverage ratios has generated a variety

of responses from scholars.3

One response in the literature has been to argue that we should not consider static

models. The trade-off theory predictions can be more complex in a dynamic model such

as that of Fischer et al. (1989) or that of Strebulaev (2007).4 Empirically, the response

has been to argue that leverage and profitability are negatively related because firms

passively accumulate profits (see Kayhan and Titman, 2007).5 This implies that at the

time of rebalancing, leverage should be positively related to profitability. Mackie-Mason

(1990) shows that companies with tax loss carryforwards are more likely to issue equity.

Hovakimian et al. (2001) and Gomes and Phillips (2007) show that highly profitable firms

are indeed more likely to issue debt. This is consistent with what we find. By contrast,

Jung et al. (1996) report finding no relation between the likelihood of equity issuance and

profitability.

Welch (2004, 2007) makes the important point that changes in debt and equity values

and changes in debt ratios are conceptually different. This distinction also plays a role

in our analysis. Welch (2007) stresses the idea that non-financial liabilities should not

be implicitly mistreated as if they were equity by paying excessively narrow attention to

financial liabilities in a leverage ratio. We have adopted his approach in the empirical

work reported here.

This paper is organized as follows. Section II describes the construction of the data

and variables and provides summary statistics. Section III provides results from the fixed

effects estimates of leverage ratios. Section IV provides the main results on debt and

equity issuance regressions. Section V explores the debt and equity issuance responses of

3A partial list of papers documenting an inverse relation include Auerbach (1985), Graham and Tucker(2006), Long and Malitz (1985), Titman and Wessels (1988), Fischer et al. (1989), Rajan and Zingales(1995), and Booth et al. (2001). Frank and Goyal (2009) show that the inverse relation between leverageand profitability has become weaker in the recent decades.

4Of course, every model leaves some things out. For instance one might consider only general equilib-rium models, or only models that account for the nature of industrial competition, or those that accountfor imperfect decision making, or any of a host of other plausible considerations. This is simply a matterof taste.

5However, Chen and Zhao (2005) conclude that neither transaction costs nor taxes can properlyexplain the negative relation between leverage and profitability.

4

firms during good and bad times. Section VI examines the debt and equity issuances when

scaled by total issuances and total capital. Section VII shows how the smooth pasting

and value matching conditions from dynamic optimization have important implications

for leverage. This helps explain why the reactions to shock are only partial. Section VIII

concludes the paper.

II. Data

We use conventional data sources, starting with the merged Compustat-CRSP data.

The data are annual and are converted into constant 2000 dollars using the GDP defla-

tor. We exclude financial companies (SIC 6000-6999), firms involved in major mergers

(Compustat footnote code AB), firms reporting financial data in currencies other than the

U.S. dollars, and firms with missing data on our key variables.6 The ratio variables are

trimmed at the 1% level in both tails of the distribution. This serves to remove outliers

and the most extremely misrecorded data. The final sample consists of 179,021 firm-year

observations from 1971-2009.

Table I provides definitions of financial variables and reports summary statistics. The

average debt (in constant US$) is about $653 million while the median is $24 million.

A significant fraction of firms have zero debt (the 10th percentile is 0). Book equity is

slightly larger than book debt. Market equity is almost three times larger than book debt.

Book assets average $2,191 million although the medians are considerably smaller.

If issuing or retiring securities incurs no fixed costs, then we would expect to see

many small actions and very few large actions (Leary and Roberts, 2005). If there were

significant fixed costs involved in issuing or retiring outstanding securities, then small

issues might not be worthwhile. Table I shows that although most firms issue little debt

or equity in a given year, the averages are large. In other words, when firms actually enter

debt and equity markets, they intervene massively.

6These include debt, book value of equity, market value of equity, assets, book and market leverage,profitability, market-to-book assets ratio, and tangibility.

5

The mean constant dollar debt issue is $165 million (the median is $1.6 million). In

unreported tables, we find that the average debt issue is about 8.1% of assets (the median

is 1.8%). About 38% of the firms issue no debt; 8% issue between 0 and 1% of the value

of their assets as debt; another 16% issue between 1 and 5% of the value of their assets

as debt; and the remaining 38% issue debt in excess of 5% of the value of their assets.

The mean constant dollar equity issue is about $26 million (the median is about $0.4

million). As a fraction of assets, the mean and median equity issues are about 7% and

0.2%, respectively. About 33% of the firms issue no equity; 34% of the firms issue between

0 and 1% of the value of their assets as equity; another 14% issue between 1 and 5% of

the value of their assets as equity; and the remaining 19% of the firms issue equity that

is in excess of 5% of the value of their assets. Average debt repayments are larger than

equity repurchases. This perhaps reflects the finite maturity of debt and its contractual

repayment. The median firm does not repurchase equity.

We construct both book and market leverage ratios. Book leverage is defined as debt

over debt plus book equity. Market leverage is defined as debt over debt plus market

equity. The median book leverage is 0.36 (the average is 0.31). The median market

leverage is 0.27 (the average is 0.20).

Profitability is defined as the ratio of operating income before depreciation to assets.

While the average firm is profitable (the ratio of ebitda to assets is 0.05), the median

firm is even more profitable (with a profitability ratio of 0.11). The sample includes a

large number of unprofitable firms as the 10th percentile is -0.18. The table also reports

descriptive statistics on the market-to-book ratio and the tangibility ratio. The market-to-

book ratio (M/B), defined as the ratio of the market value of assets to book assets, averages

at about 1.65. Tangibility, defined as the ratio of net property, plant and equipment to

assets, averages at about 31%.

6

III. Estimating a Leverage Ratio

The previous literature focuses on estimates obtained using leverage ratios. Hence,

we start with a similar estimation to check whether our results match those of previous

studies. Table II presents the results. Some scholars advocate book leverage ratios while

others advocate market leverage ratios. We report results for both.

The regressions include leverage factors following the previous capital structure liter-

ature (see, for example, Rajan and Zingales (1995) and Frank and Goyal (2009)). The

factors include (i) profitability, (ii) industry median leverage, (iii) market-to-book assets

ratio, (iv) tangibility of assets, and (v) firm size. Industry median leverage is estimated

as the median leverage of all other firms in the industry (excluding the firm under con-

sideration). Firm size is defined as the natural log of assets. Other factors are defined in

Section II. We cluster standard errors by firm and estimate these regressions both with

and without fixed effects.

In Table II we run conventional cross section leverage regressions. Since we employ

the usual data, it is not surprising that our results match those reported in the existing

capital structure literature, i.e., profitability has a negative sign in both the book leverage

regression and in the market leverage regression. The coefficients on other factors largely

match those reported in earlier studies. Firms operating in industries with high lever-

age tend to have high leverage. A higher market-to-book ratio is associated with lower

leverage. Larger firms are typically more highly levered. The coefficients on tangibility

are positive. The conclusion from Table II is clear. The leverage regression results match

those reported in previous studies.

At times there is a concern that in a regression what is being estimated is a conditional

mean, but some parts of the distribution might behave differently from other parts. If

so, then ’accidents’ like sample selection issues, or asymmetries in the underlying distri-

butions might play more of a role than is recognized. The source of identification could

be misinterpreted. To guard against this potential problem we estimated the same model

7

using quantile regressions.7 The basic model results are robust in terms of both the sign

and statistical significance.

The impact of profits does appear to be somewhat stronger among the high leverage

firms. For instance in a book leverage regression the coefficient on profits for the first

quartile is -0.105 with a t-ratio of -37.8. For the third quartile the coefficient on profits is

-0.406 with a t-ratio of -101.5. This difference is curious and might deserve further study.

However, the fact that in each case we get the negative sign and statistical significance is

sufficient for the purposes of the current paper. So the results on profits are rather robust

across the distribution.

A. Frequency of Financing Activity

Table III tabulates the percentage of firms issuing or repurchasing debt or equity for

annual sorts based on lagged profitability. We employ the conventional 5% cut-off rule to

exclude minor fluctuations. Firms ‘issuing debt’ are therefore those that issue debt (both

short-term and long-term) in excess of 5% of the value of their assets. Other decisions

are similarly defined using a 5% cutoff.

How does security issuance behavior vary with firm profitability? To answer this

question, Table III sorts firms by profitability and reports the percentage of firms issuing

or repurchasing debt or equity. The results show that the likelihood of issuing debt is

mostly independent of firm profitability. Similarly, there is only a weak relation between

the profitability and the likelihood that the firm retires debt. Unlike debt issues, the

probability of issuing equity is strongly related to profitability.

Low-profit firms are much more likely to issue equity than are high-profit firms. Fur-

thermore, high-profit firms are much more likely to repurchase equity. Accordingly, low

profitability firms are much more likely to be net equity issuers than are high profitabil-

ity firms. Among the firms in the lowest quintiles of profits, roughly 30% of firms issue

7Cameron and Trivedi (2010) provide an extensive discussion of quantile regressions in Stata.

8

net equity that exceeds five percent of their assets. By contrast, for the most profitable

quintile of firms, only about 8% issue net equity.

Firm size is an important variable in the recent literature – it is often used as a proxy

for access to capital markets (as in Faulkender and Petersen (2006), and Leary (2009)).

Small firms are bank-dependent, risky, and informationally opaque. They have restricted

access to public debt markets and consequently face more severe supply constraints in

their ability to issue debt. Thus, we expect small firms to be more sluggish in adjusting

their debt and equity in response to shocks to profitability. Large firms, by contrast,

have much easier access to public debt markets and they face fewer obstacles in accessing

securities markets.

How do size and profitability interact? To examine this question, we first sort firms

annually by firm size and then, within each size quintile, we sort firms based on prof-

itability. The bottom part of Table III reports results for the smallest and the largest

size quintiles. Among the small firms, there is little relation between profitability and the

likelihood of issuing debt. However, larger firms exhibit a small increase in the likelihood

of net debt issuance with increasing profitability.

The effects of profitability on equity issuance and repurchases are much more consistent

across size quintiles. As profitability increases, firms are generally less likely to issue equity

and more likely to repurchase it. Across the two extreme size groups, we note a striking

difference between the proportion of firms issuing equity and that issuing debt. Among

low-profit small firms, almost 41% are equity issuers, whereas only about 9% of low-profit

large firms are equity issuers. However, regardless of size, we note a monotonic reduction

in the likelihood of issuing equity as profitability increases.

Importantly, Column (8) shows that the likelihood of issuing debt and simultaneously

repurchasing equity increases with profitability. Column (9) shows that, conversely, the

likelihood of issuing equity and retiring debt declines with profitability. The effects of

sorting on firm size and firm profitability mirror those reported for all firms. Again, we

find that low-profit firms are less likely to issue debt and repurchase equity; they are

9

instead more likely to issue equity and retire debt. Firms with high profitability exhibit

the reverse pattern.

B. Magnitude of Financing Activity

In the previous section, we considered the probability of having a nontrivial level of

debt or equity activity. The next question is how large are the dollar values involved. In

Table IV, we sort the firms according to profits and then tabulate the levels and changes

in both debt and equity. We do this first for all firms and then for small versus large

firms.

For the analysis on all firms, we observe in Column (1) that debt peaks at the middle

of the distribution. This is because firms with medium profitability are also the largest, as

seen in Column (8) which reports average asset values for different profitability quintiles.

It is further confirmed when we sort first by firm size and then examine firms with different

profitabilities within size quintiles. For small firms, debt is roughly independent of profits,

while for large firms low profit firms tend to have a higher level of debt.

As expected, Columns (3) and (5) show that more profitable firms have higher equity

values. Columns (1), (3), and (5) show that firms in our sample are quite typical of those

used in previous studies, which stands to reason because we are studying firms from the

most commonly used data set for such studies.

In Column (2) of Table IV, we consider the relationship between the change in debt

and firm profitability. Consistent with the predictions of the trade-off theory, we find that

debt issuances are significantly larger for more profitable firms. Also, consistently, less

profitable firms issue more equity while the most profitable firms repurchase equity.

The fact that more profitable firms issue debt and repurchase equity while the least

profitable firms retire debt and issue equity is consistent with the predicted relation be-

tween profitability and financing decisions under the trade-off theory. Columns (4) and

(6) provide an explanation of why the leverage ratio regression results contradict those

from the basic profitability sorts presented here. As we can see, profitability indirectly

10

affects leverage ratios by increasing equity values. Changes in both the book value of

equity and the market value of equity are positive and large for highly profitable firms.

By contrast, these changes are negative for less profitable firms.

We also examine two-way sorts by size and profitability and report results for the

smallest and largest quintile of firms. For the smallest quintile of firms, the change in

debt is largely unrelated to profits. But for large firms, there is a positive relation between

profits and debt issuances. High profit firms have a big positive change in debt. Low profit

large firms have a negative change in debt.

The changes in both the book value of equity and the market value of equity across

profit quintiles are illustrated in columns (4) and (6). Large and highly profitable firms

are associated with a big positive change in equity. For small firms the effect is much

weaker. However the impact from the large firms is sufficiently strong that the patterns

persist for the case of all firms.

Column (7) of Table IV is of particular importance for the trade-off theory. It shows

that small and low profit firms tend to issue more equity than do small and high profit

firms. Among large firms, the low profit ones tend to issue equity, while the high profit

ones tend to repurchase equity.

The finding that more profitable firms tend to repurchase equity comes as expected

from the basic trade-off theory. The fact that in general high profit firms tend to issue

more debt is also as predicted.

This evidence also illustrates an important issue concerning the use of leverage ratios.

Such ratios are often interpreted as essentially reflecting the use of debt by the firm. This

interpretation, while common, is empirically misleading.

For the typical firm, the change in the value of equity is larger than the change in

debt. For example, in the third profit quintile for large firms, the mean equity issue is

just $9 million, but the change in the market value of equity is $242 million. At the

same time the mean change in debt is $27 million. This suggests that a fair bit of the

observed variation in the leverage ratios is primarily driven by the changes in the market

value of equity in the denominator, rather than by the changes in debt in the numerator.

11

Since equity issues are often small, this implies that the variation in the leverage ratio is

primarily driven by internal operations rather than by external financing actions. This

again points to the fact that leverage ratios can provide a misleading account of actual

patterns in the data.

There is always a potential concern that the averages may be misleading due to the

impact of outliers. To address this concern, in Table V we present median values of the

profitability sorts. This table generally reinforces the findings in Table IV. The first

observation concerning the medians is that an average profitability firm typically reduces

debt. Low profit firms have a negative change in both book equity and market equity.

Equity issues are mostly found among low profit firms.

When we decompose small and large firms, important differences emerge at the me-

dians. Small firms generally have no change in debt and some reduction in both the

book and the market value of equity. Large unprofitable firms reduce debt and experience

declines in both book equity and market equity. Large profitable firms at the median

experience increases in both book and market equity. However experiencing an equity

increase is quite different from issuing equity. For both large and small firms equity is-

suance is found primarily among the low profit firms. The scale of equity issues relative

to firm size is much larger for small firms than for large firms.

IV. Estimating Debt and Equity Regressions

So far we have demonstrated that in our data the conventional leverage regressions

have the usual signs. We then demonstrated that in simple sorts of the data, strikingly

different financing patterns emerge. The next task is to reconcile these differences.

Table VI presents simple regressions predicting changes in debt, book equity, and

market equity, as well as equity issuances. Consistent with the sorts, we control for

changes in firm size, and we also include year dummies. There may be a concern about

the speed of a firm’s responses. Accordingly we consider the lagged change in profits as

the main case, but we also include the contemporaneous change in profits. Whether the

12

contemporaneous change in profits is included or not does not in fact matter. We report

panel-robust standard errors adjusted for clustering at the firm level.

The results in Table VI support the findings in the sorts. More profitable firms in-

crease debt. More profitable firms experience increases in book equity and market equity.

However, profitable firms show negative equity issues, meaning that when profitability

increases, firms tend to repurchase equity. All of these effects are statistically significant,

and seem intuitively reasonable.

The fact that more profitable firms do actually issue debt is crucial from the perspective

of the trade-off theory, as is the fact that these firms repurchase equity. However, these

firms apparently experience a large increase in the value of equity.

In Table VI all firms are pooled, and there are year fixed effects. Thus the time effects

have been removed, and identification is possible by observing the differences between

firms. Some scholars have argued that firms have financial targets that are key to under-

standing their financing behavior. Empirically defining the target is controversial since

there is no accepted model of the target. However, Lemmon et al. (2008) have argued

that there is a great deal of persistence in capital structure, so that a long term average

does a good job of predicting what firms will do. Thus, we run all of our regressions using

firm fixed effects. The long term average ought to reflect this targeting behavior.

We find that empirically very little changes whether we include firm fixed effects or

leave them out. Thus the targeting behavior, to the extent that it happens, does not

account for what we are reporting. Table VII provides an illustration. As is readily

apparent nothing much changes when we include the firm fixed effects. Accordingly

we do not think that the lack of concern for capital structure target seeking drives our

findings.

The next step is to bring the sorts and the simple regressions together into a common

setting. We therefore include factors in addition to profitability: (i) median industry

leverage, (ii) the market-to-book assets ratio, (iii) tangibility of assets, and (iv) firm size

(measured by the log of assets). Rajan and Zingales (1995) show that these factors are

related to leverage in G7 countries. A number of studies have used these factors to

13

estimate leverage targets. Frank and Goyal (2009) show that these factors are robustly

related to leverage in the U.S. In these regressions, we use indicators for the quintile that

the firm is in for each factor.

Table VIII reports these results. In Columns (1) and (2), we examine debt issues

and again show that profits positively affect debt issuances. The effects are large and

statistically significant at the 1% level. Columns (3) and (4), which examine book equity

show a strong effect of profits. This effect is only slightly reduced by the inclusion of

other factors. Columns (5) and (6) illustrate that the impact of profits on the change

in market equity is also robust to the inclusion of the conventional factors. Columns

(7) and (8) examine equity issuances. Here we again find that profits have a significant

negative impact on equity issuances. As before, the results are robust to the inclusion of

the conventional factors.

In unreported tables, we estimate debt and equity changes using quantile regressions.

In terms of the signs and significance of the profitability variable, the results are quali-

tatively similar to the OLS results reported in Table VIII. Profitability positively affects

debt issuances and negatively affects equity issuances across various quartiles.

While it is not our main focus, we note that the market-to-book ratio positively affects

debt issues and changes in the book value of equity. However, its impact on equity issues is

not statistically significant.8 In the existing literature, finding a negative relation between

the market-to-book ratio and leverage is common.9

8We are not testing the market timing hypothesis. However, these results are rather surprising fromthe perspective of the market timing theory of capital structure.

9The market-to-book ratio is commonly considered as a proxy for growth opportunities. Growth firmsare expected to finance with relatively more equity to avoid debt-related agency conflicts (Myers, 1977).Previous studies have typically found a negative relation between leverage and growth opportunities (seeSmith and Watts, 1992; Rajan and Zingales, 1995; Hovakimian et al., 2001; Goyal et al., 2002; Barclayet al., 2006; Frank and Goyal, 2009). The market timing literature also predicts a negative relationbetween the market-to-book ratio and leverage (Baker and Wurgler, 2002). Flannery and Rangan (2006),Kayhan and Titman (2007), and Liu (2009) suggest that it is difficult to disentangle the effect of growthopportunities and market timing in cross-sectional regressions of the market-to-book ratio on leverage.Graham and Harvey (2001) provide a useful survey of executives’ opinions about the importance ofvarious factors.

14

Firm size has a substantially larger effect on debt issuances than on equity issuances.

This may help to explain the commonly observed positive relation between firm size and

leverage ratios.

Table VIII also shows that there is nothing all that special about using sorts or regres-

sions to explain debt and equity issues. In either case we find that more profitable firms

tend to increase their debt, experience an increase in the value of equity, and repurchase

shares. Thus the control factors are not responsible for the usual rejection of the trade-off

theory. It would appear that what matters is the size of the issuing activity relative to

the organic increases in equity value due to profits. In other words what matters in the

leverage regression seems to be coming from the presence of E in DD+E

, and not from D.

Overall, the results from the debt and equity issuance regressions are consistent with

the trade-off theory. The coefficient estimates on the leverage factors generate several

interesting results. Profits positively affect debt issuances. Equity issues are negatively

related to profits. The market-to-book ratio positively affects the change in debt. Firm

size positively affects the change in debt and book equity. Firm size negatively affects

equity issues.

V. Are Financial Market Conditions Important?

According to the trade-off theory, capital structure is determined by considering the

impact of costs and benefits of debt. The time variation in the costs and benefits of debt

imply that issuance decisions would also vary over time. Furthermore, market conditions

affect the transaction costs of adjusting. Adverse selection is a greater problem in a

cold market than in a hot one. Accordingly it may be easier to adjust in good market

conditions. Related ideas have been developed by Huang and Ritter (2009), Faulkender

et al. (2010), and Halling et al. (2011). Faulkender et al.’s paper examines cross-sectional

variation in adjustment speeds including market valuations and how they may affect

adjustment speeds. It is natural to think that in good market conditions, it will be less

15

costly to issue both debt and equity, and adjusting leverage to respond to profitability

shocks would be much easier.

To test the importance of market conditions, we require a definition of good times

and bad times. Our empirical strategy is to estimate good times versus bad times at

the 4-digit industry level. We define an industry as having “good times” if the median

firm in that industry has a market-to-book ratio that is higher than the 67th percentile of

the time-series distribution of the industry median market-to-book ratios. Conversely, an

industry is defined as having bad times if the median firm in the industry has a market-

to-book ratio that is lower than the 33rd percentile of the time-series distribution of the

industry median market-to-book ratios.

Panel A of Table IX tabulates issuance activity for profitability sorts in both good

times and bad times. As might be expected, active debt and equity issuances are larger

during good times. There is also somewhat more active swaps between debt and equity

during good times.

Panel B reports the issuance activity for the smallest and the largest firm during the

good times and bad times. Within each size quintile, firms are sorted on profitability.

This is a three way sort. As before we find that there is much more active use of external

markets during good times. Small, low-profit firms are more likely to issue equity in good

times than in bad times. Debt issuances are significantly higher in good times. Large,

high-profit firms are significantly more likely to issue debt and repurchase equity in good

times than in bad times.

Panel C reports the magnitudes of the financial variables rather than the frequencies.

During bad times, less profitable large firms retire substantial amounts of debt and they

show a tendency to issue equity. Small firms do not seem to engage in similar debt

reduction activities. However, like the larger firms, there is a tendency for small firms to

issue more equity – at least to the extent possible.

During good times, large profitable firms raise significant amounts of debt as they

experience an increase in the value of their equity. Such firms also engage in share re-

purchases. Debt issues by smaller firms are much less affected by their own profitability

16

during good times and their change in debt is more or less independent of their prof-

its. However, equity issuance is primarily found among the low profit small firms during

good times. Table IX shows that, empirically, profitability has a time-varying impact on

leverage choices.

In Table X, the basic regressions for changes in debt and for equity issuance are

presented for both good times and bad times. Comparing good times with bad times,

we see that the effects of profits are much stronger in good times. In bad times the

impacts are rather weak statistically. This difference is interesting and deserves further

study. However for our purposes recall that the static trade-off theory implies time-

varying capital structure choices even when the target is time invariant. Empirically we

do observe time-varying choices.

VI. Is Scaling Important?

In the preceding section, we provided results for unscaled debt and equity issues.10

This seems appropriate to us. However it involves making two changes to the standard

regression. We would like to determine if both changes are crucial. Accordingly, in this

section, we take a step back to consider prior literature in which variables are scaled. The

questions are, how does scaling affect the results and why.

Table XI examines alternative scalings. Columns (1) and (2) scale the debt and equity

issuances by the total firm net issuance. Columns (3) and (4) scale the debt and equity

issuances by the sum of debt and book equity. Column (5) considers the change in debt

scaled by the sum of debt and book equity. Column (6) considers the change in leverage

due to external financing. Since we are examining changes, we use the changes in the

standard regression factors as controls. The primary interest is in the coefficient on the

change in profits.

10More than a century ago the famous statistician Pearson pointed out that scaling two independentvariables by the same third variable induces spurious correlation. Barraclough (2007) points out that thisidea extends to capital structure regressions. If you scale both the right-hand and left-hand side variablesin a regression by the same variable, that can induce a spurious correlation.

17

Column (1) shows that a change in profits is associated with an increase in debt issues.

But the sign reverses in Column (3) when we scale the debt issues by the sum of debt

plus book equity. This is telling. What is really driving the results is the change in

equity in the denominator, not the change in debt in the numerator. This result is further

substantiated in Column (5) where the change in debt to capital ratio is used instead of

debt issuance.

To further explore the impact of active issuance relative to passive experiencing of

changes we decompose leverage in Column (6). We separate out the effect of debt and

equity issues from those due to changes in retained earnings by defining leverage change

due to external financing as:

∆LeverageEF =Dt−1 + d

Dt−1 + Et−1 + d+ e− Dt−1

Dt−1 + Et−1, (1)

where D is debt, E is book value of equity , d is debt issues net of retirements, and e is

equity issues net of repurchases. Garvey and Hanka (1999) use a similar measure in their

study. This measure directly captures the net leverage effect of debt and equity issuances.

Column (6) reports results from regressions of the net leverage effect of debt and equity

issues on changes in profitability after controlling for other leverage factors in differences

and year indicator variables. The key effect is the coefficient on the change in profits,

which is positive. The effect of profitability on leverage change due to external financing

is positive and statistically significant. This comparison suggests that changes in total

debt and equity are only partly a result of debt and equity issuance decisions. Other

balance sheet adjustments complicate the inferences from leverage ratio regressions.

In Table XII, we examine change in leverage and change in leverage due to external

financing during good and bad times separately. The traditional negative effect of a change

in profits on a change in leverage is found both in good times and in bad times. However

when we decompose the impact in order to isolate the external component, as before, the

result disappears. In good times the external financing component of a change in profits

is fairly weak, but still positive. During bad times it is not statistically significant. This

implies that distinguishing between good and bad times does not fundamentally alter

18

the basic conclusions. The traditional leverage result on profits is driven by increases in

equity that are experienced and then partially, but not completely, offset by firms.

To the extent that firms are engaging in active financing they are following the pre-

scriptions of the trade-off theory. Thus we have overall a coherent picture of how firms

are responding to profits. Basically, more profitable firms experience an increase in the

value of their equity. They respond to this by issuing debt and repurchasing equity. But

the magnitude of the increase in equity is larger than the magnitudes of the active steps

taken in the debt and equity markets. This means that the firms’ actual actions are as

predicted by the trade-off theory. But it leaves open the question of why they do not act

more strongly.

In the next section we argue that partial adjustment to shocks is what ought to be

expected generally. The idea is that both fixed and variable adjustment costs are real and

need to be minimized in the firm’s optimization problem.

VII. Trade-Off with Adjustment Costs

The capital structure literature has long been interested in dynamics and capital struc-

ture adjustment paths. In recent years this interest has increasingly resulted in explicit

dynamic optimizing models such as those of Goldstein et al. (2001), Hennessy and Whited

(2005), Strebulaev (2007). These models commonly make specialized assumptions leading

some, such as Welch (2011), to question their generality.

In contrast, we argue that dynamic optimization (Dixit (1993), and Stokey (2009))

does offer some fairly general observations about the required conditions for optimality

when there are both fixed and variable adjustment costs. These conditions have important

implications for tests of the trade-off theory that have largely been ignored in the literature

on capital structure adjustment. As a result some rather misleading impressions have

become widespread.

The basic conditions for optimality are known as: “smooth pasting” and “value match-

ing”. Standard analysis of cash management (Constantinides and Richard (1978)), invest-

19

ment (Bertola and Caballero (1990)) and inventory (Stokey (2009)) all have an essentially

similar structure. This structure can be reinterpreted as a trade-off theory of corporate

capital structure. This works because the original models use fairly general assumptions

about the shapes of the underlying functions, rather than making problem-specific as-

sumptions. The presentation here largely follows that of Bertola and Caballero (1990).

Consider a model in which excessive, or inadequate leverage is costly. Think of these

costs as reflecting the taxation benefits of debt and deadweight bankruptcy costs. Lever-

age is the choice variable. Assume also that the firm has a nice concave production

function with a unique optimal scale of operations.

The risk-neutral firm chooses leverage in order to maximize the discounted present

value. Let L = leverage (the choice variable), r = the discount rate, ε = an exogenous

Brownian shock process, π = profits (twice differentiable, and strictly concave), V = the

firm’s value function. The unconstrained maximum is given by

x∗(ε) = arg maxL

π(L , ε).

If there were no adjustment costs then the firm would always pick leverage to ensure that

xτ = x∗(ε) for all τ . This is the static ‘leverage target’.

Now suppose that there are adjustment costs. The optimization problem can be

expressed as

V (Lt, εt) = max{Lt}

Et

∫ ∞t

e−r(τ−t)(π(L , ε)− ‘adjustment costs’).

To actively adjust leverage requires decision making. Adjusting takes time and effort

on the part of executives, along with board members and investment bankers in some

cases. Issuing securities also involves underwriting costs as documented by Altinkilic and

Hansen (2000) and Chen and Ritter (2000). There will normally be both a fixed cost

component and a variable cost component. Similarly, repurchasing securities will involve

both fixed and variable costs (fees).

20

In general, there is no reason for the fixed costs and the variable costs of increasing

and reducing leverage to be equal. In fact, there are good reasons to expect there to be

four distinct parameter values.11 Let cfi = the fixed cost of increasing leverage, cfr = the

fixed cost of reducing leverage, cvi = the variable cost of increasing leverage, cvr = the

variable cost of reducing leverage. All of these values are positive numbers.

If the firm wants to increase leverage by some amount ∆L, then it costs the firm

cfi + cvi∆L. Similarly if the firm wants to reduce leverage by some amount ∆L, then it

costs the firm cfr + cvr∆L. There is a discontinuity in the total cost of adjustment right

at the point of zero adjustment. Zero adjustment of leverage by the firm involves zero

adjustment cost. Any actual active adjustment entails a strictly positive fixed cost.

Consider what happens as the size of an adjustment shrinks towards zero. The average

unit cost becomes arbitrarily large since the fixed cost component is divided by something

incredibly small. But the profit function itself is smooth and has no such discontinuity.

Clearly it must be the case that a small enough (but strictly nonzero) leverage adjustment

cannot pay. Furthermore, the point at which it becomes too small to pay will generally

differ on the two sides of zero since the cost parameters differ.

With a setup that is essentially the same as this, Constantinides and Richard (1978)

and Bertola and Caballero (1990) show that the model can be depicted as in Figure 1.

The intuition is quite clear. If the firm is increasing leverage, then the marginal value of

a unit increase must equal the marginal cost of a unit increase. Otherwise the firm could

increase profits by making some other amount of adjustment. This pins down how large

an increase will be if it happens. When will the firm choose to increase leverage? It will

do so if the value of the firm is greater with a leverage increase than without. In other

words the firm undertakes the leverage increase at the point when the value of the firm

with the increase just matches the value of the firm without (‘value matching’). The same

reasoning applies to leverage reductions albeit with different parameter values.

11Going further, it ought to matter whether the action is in the debt market or in the equity market.Adding this would turn the four parameters discussed in the text into eight parameters. While thatwould be realistic, it would be overkill for our purposes. In this section we simply want to point out theimportance of smooth pasting and value matching for studies of capital structure.

21

Returning to Figure 1, the value function v(z) is rewritten in terms of zt = Lt − L∗t .The steps to make the conversion follow those of Bertola and Caballero (1990). There

are four critical boundary values Bla, Blr, Bua, Bur. Here B is a boundary value with the

subscript l denoting lower, u denoting upper, a denoting action point, and r denoting the

point to which the firm rebalances. Thus if Lt < Bla then the firm increases the leverage

to Blr. If Lt > Bua then the firm reduces leverage to Bur. If Bla < Lt < Bua, the firm

neither actively increases nor decreases leverage. The only changes to leverage reflect the

passive effect of the Brownian shocks.

As can be seen in Figure 1 the existence of the unit costs implies that increases and

decreases of leverage do not return the firm to the unconstrained maximum x∗. In each

case the movement is in that general direction, but in each case the movement is partial.

It does not pay to go all the way due to the unit adjustment costs.

This has crucial implications for tests of capital structure adjustment. Firms will not

adjust all the way to the static optimum. Instead there is movement in the direction

towards the optimum. Both increases and decreases are partial. There is a large zone of

inaction with a pair of outer boundaries at which it pays to readjust. There is also a pair

of inner readjustment levels with a gap in between. This inner gap includes the static

optimum. The larger the various adjustment costs the farther apart these critical values

will be.

It should be stressed that the analysis in this section is essentially a simple rein-

terpretation of previous models. Since those models have a very general structure the

interpretation in terms of leverage is not difficult. But by the same token, the ideas are

not novel. What is novel is that the models also apply to capital structure.

A limitation is that the model assumes that the choice variable is one dimensional

leverage. But interpreting leverage as one dimensional is a bit extreme. In reality, at least

debt and equity can be distinguished. Formally analyzing a model with fixed and variable

costs and with debt and equity would entail doubling the number of cost parameters.

The algebra would be messier. But the basic ideas would be the same for both debt and

equity. We would need to characterize the smooth pasting and value matching conditions

22

for both debt and equity. Assuming that the parameters differ, we would then have eight

cost parameters.

The optimal actions would have more complex rebalancing conditions and more com-

plex zones of inactivity. We would also need to decide in each case whether adjusting

debt or equity made more sense. Thus, some inequalities would need to be presented.

For our purposes the details of such analytics is not worth it. The existence of zones of

inactivity will remain. The fact that readjusting is only part way towards the static target

will remain. The fact that the theory implies the directions of the changes will remain.

As the number of choice variables increases, so will the number of rebalancing points.

Instead of two rebalancing points, for well behaved functions we ought to find four. As

still greater realism is introduced the complexity and the detail will grow. But the ideas

of value matching and smooth pasting will retain their basic importance.

The magnitudes of adjustments will depend on a number of parameters, and some

details of the functional forms. Characterizing these goes well beyond the scope of the

current paper. What we want to stress is that the trade-off theory has clear implications

for the directions of typical leverage adjustments. The implication for the magnitudes are

much more tenuous and detail dependent.

VIII. Conclusion

The connection between corporate profits and capital structure has been very influ-

ential in the assessment of the trade-off theory. The standard evidence has pushed the

literature away from the trade-off, and towards much more complex models and ideas.

As a result it is important to make sure that the evidence has been correctly interpreted.

Unfortunately, it has not.

In fact more profitable firms really do borrow more (not less). They tend to repurchase

equity. They experience an increase in both the book value of equity and the market value

of equity. Less profitable firms really do tend to reduce their debt and to issue equity.

23

Firm size and market conditions also matter. Larger firms tend to be more active

in the debt markets while smaller firms tend to be relatively more active in the equity

markets. During good times there is more use of external financing.

The usual profits-leverage puzzle result is primarily driven by the increase in equity

that is experienced by the more profitable firms. Accordingly the puzzle should be restated

as asking: why do firms not take sufficiently large offsetting actions to fully undo the

change in equity? What limits the magnitudes of the typical leverage response to profit

shocks?

In a frictionless model the partial response appears puzzling. But there is good empir-

ical reason to believe that rebalancing entails both fixed and variable costs. These costs

can be fully avoided by doing nothing. Accordingly, the firm must decide whether any

given shock is big enough to be worth responding to. If it is, then the firm must decide

how big a response is called for. These technical conditions are known as ‘value matching’

and ‘smooth pasting’.

Thus optimization implies that some shocks will be ignored. Even if the shock is not

ignored, the optimal response will only partially undo the shock. The magnitude of the

leverage response must balance the marginal cost and the marginal benefit of an extra

unit of leverage. Since the marginal cost of adjusting leverage is strictly positive, the

adjustment towards that static leverage optimum will only go part way. This is true both

for leverage increases and for leverage reductions.

Surely nobody ought to be surprised that more profitable firms are more inclined

to repurchase equity, while unprofitable firms tend not to do so. The fact that more

profitable firms typically experience an increase in the value of equity is equally natural.

Were it not for the contrary claims in the literature (i.e. the profits-leverage puzzle), we

would argue that nobody ought to find it surprising that more profitable firms are more

inclined to issue debt. The fact that leverage adjustments typically only partially offset

profit shocks, should also sound quite natural. These facts all fit together easily within

the trade-off theory.

24

References

Altinkilic, O., and R.S. Hansen, 2000, Are there economies of scale in underwriting fees?Evidence of rising external financing costs, Review of Financial Studies 13, 191–218.

Auerbach, A.J., 1985, Real determinants of corporate leverage, in B.M. Friedman, (ed.)Corporate capital structures in the United States (University of Chicago Press, Chicago,IL).

Baker, M., and J. Wurgler, 2002, Market timing and capital structure, Journal of Finance57, 1–32.

Barclay, M.J., E. Morellec, and Jr. C.W. Smith, 2006, On the debt capacity of growthoptions, Journal of Business 79, 37–59.

Barraclough, K., 2007, Scaling regression equations: Solution or problem? Working Paper,Vanderbilt University.

Bertola, G., and R.J. Caballero, 1990, Kinked Adjustment Costs and Aggregate Dynam-ics, NBER Macroeconomics Annual 5, 237–288.

Booth, Laurence, Varouj Aivazian, Asli Demirguc-Kunt, and Vojislav Maksimovic, 2001,Capital structures in developing countries, Journal of Finance 56, 87–130.

Cameron, A.C., and P.K. Trivedi, 2010, Microeconometrics Using Stata (Stata Press).

Chen, H.C., and J.R. Ritter, 2000, The seven percent solution, The Journal of Finance55, 1105–1131.

Chen, L., and X. Zhao, 2005, Profitability, mean reversion of leverage ratios and capitalstructure choices, working paper, Michigan State University and Kent State University.URL: http://ssrn.com/abstract=614082

Constantinides, G.M., and S.F. Richard, 1978, Existence of optimal simple policies fordiscounted-cost inventory and cash management in continuous time, Operations Re-search 26, 620–636.

Dixit, A.K., 1993, The art of smooth pasting (Routledge).

Fama, E., and K.R. French, 2002, Testing trade-off and pecking order predictions aboutdividends and debt, Review of Financial Studies 15, 1–33.

Faulkender, M., M. Flannery, K.W. Hankins, and J.M. Smith, 2010, Cash flows andleverage adjustment, Working paper, University of Maryland, University of Florida,and University of Kentucky.

Faulkender, M., and M.A. Petersen, 2006, Does the source of capital affect capital struc-ture?, Review of Financial Studies 19, 45–79.

25

Fischer, E., R. Heinkel, and J. Zechner, 1989, Dynamic capital structure choice: theoryand tests, Journal of Finance 44, 19–40.

Flannery, M., and K. Rangan, 2006, Partial adjustment towards target capital structures,Journal of Financial Economics 79, 469–506.

Frank, M.Z., and V.K. Goyal, 2008, Trade-off and pecking order theories of debt, in B.E.Eckbo, (ed.) Handbook of Corporate Finance: Empirical Corporate Finance, Vol. 2. In:Handbook of Finance Series, Chapter 12, – (Elsevier/North-Holland, Amsterdam).

Frank, M.Z., and V.K. Goyal, 2009, Capital structure decisions: Which factors are reliablyimportant?, Financial Management 38, 1–37.

Garvey, G.T., and G. Hanka, 1999, Capital structure and corporate control: The effectof antitakeover statutes on firm leverage, Journal of Finance 54, 519–546.

Goldstein, R., N. Ju, and H. Leland, 2001, An ebit-based model of dynamic capitalstructure, Journal of Business 74, 483–512.

Gomes, A.R., and G.M. Phillips, 2007, Private and public security issuance by publicfirms: The role of asymmetric information, Working Paper, Washington University inSt. Louis and University of Maryland.

Goyal, V.K., K.M. Lehn, and S. Racic, 2002, Growth opportunities and corporate debtpolicy: the case of the U.S. defense industry, Journal of Financial Economics 64, 35–59.

Graham, J.R., and C. Harvey, 2001, The theory and practice of corporate finance: evi-dence from the field, Journal of Financial Economics 60, 187–243.

Graham, J.R., and A.L. Tucker, 2006, Tax shelters and corporate debt policy, Journal ofFinancial Economics 81, 563–594.

Halling, M., J. Yu, and J. Zechner, 2011, Leverage dynamics over the business cycle, Work-ing paper, University of Utah, University of New South Wales, and Vienna Universityof Economics and Business Administration.

Hennessy, C.A., and T.A. Whited, 2005, Debt dynamics, Journal of Finance 60, 1129–1165.

Hovakimian, A., T. Opler, and S. Titman, 2001, The debt-equity choice, Journal ofFinancial and Quantitative Analysis 36, 1–24.

Huang, R., and J.R Ritter, 2009, Testing theories of capital structure and estimating thespeed of adjustment, Journal of Financial and Quantitative Analysis 44, 237–271.

Jung, K., Y. Kim, and R. Stulz, 1996, Timing, investment opportunities, managerialdiscretion, and the security issue decision, Journal of Financial Economics 42, 159–185.

26

Kayhan, A., and S. Titman, 2007, Firms’ histories and their capital structures, Journalof Financial Economics 83, 1–32.

Kraus, A., and R.H. Litzenberger, 1973, A state-preference model of optimal financialleverage, Journal of Finance 33, 911–922.

Leary, M.T., 2009, Bank loan supply, lender choice, and corporate capital structure,Journal of Finance 64, 1143–1185.

Leary, M.T., and M.R. Roberts, 2005, Do firms rebalance their capital structures?, Journalof Finance 60, 2575–2619.

Lemmon, M.L., M.R. Roberts, and J.F. Zender, 2008, Back to the beginning: Persistenceand the cross-section of corporate capital structure, Journal of Finance 63, 1575–1608.

Liu, X.L., 2009, Do firms have target leverage ratios? Evidence from historical market-to-book and past returns 15, 602–612.

Long, M.S., and I.B. Malitz, 1985, The investment-financing nexus: Some empirical evi-dence, Midland Finance Journal 53–59.

Mackie-Mason, J.K., 1990, Do taxes affect corporate financing decisions?, Journal ofFinance 45, 1471–1493.

Myers, S.C., 1977, Determinants of corporate borrowing, Journal of Financial Economics5, 147–175.

Myers, S.C., 1993, Still searching for optimal capital structure, Journal of Applied Cor-porate Finance 6.1, 4–14.

Rajan, R., and L. Zingales, 1995, What do we know about capital structure: Someevidence from international data, Journal of Finance 50, 1421–1460.

Smith, C.W., and R.L. Watts, 1992, The investment opportunity set and corporate financ-ing, dividend and compensation policies, Journal of Financial Economics 32, 263–292.

Stokey, N.L., 2009, The economics of inaction: Stochastic control models with fixed costs(Princeton University Press).

Strebulaev, I.A., 2007, Do tests of capital structure theory mean what they say?, Journalof Finance 62, 1747–1787.

Titman, S., and R. Wessels, 1988, The determinants of capital structure choice, Journalof Finance 43, 1–21.

Welch, I., 2004, Capital structure and stock returns, Journal of Political Economy 112,106–131.

27

Welch, I., 2007, Common flaws in empirical capital structure research Working Paper,http://ssrn.com/abstract=931675.

Welch, I., 2011, A critique of recent quantitative and deep-structure modeling in capitalstructure research and beyond Working Paper.

28

Fig

ure

1:Sm

oot

hP

asti

ng.

The

stat

icop

tim

alle

vera

gera

tio

isat

the

pea

kof

the

valu

efu

nct

ion.

The

pos

itiv

ely

slop

edline

segm

ents

hav

eth

esa

me

slop

eas

each

other

.Sim

ilar

ly,

the

neg

ativ

ely

slop

edlines

segm

ents

hav

eth

esa

me

slop

eas

each

other

.If

leve

rage

isst

rict

lyb

etw

eenBla

andBua

then

the

firm

willnot

acti

vely

adju

stle

vera

ge.

The

real

ized

leve

rage

isth

enth

epas

sive

resu

ltof

the

Bro

wnia

nsh

ock

s.If

leve

rage

isle

ssth

anBla

,th

enth

efirm

will

opti

mal

lyin

crea

sele

vera

geto

Blr

.If

leve

rage

isgr

eate

rth

anBua,

then

the

firm

will

opti

mal

lyre

duce

leve

rage

toBur.

Thes

ere

bal

anci

ng

choi

ces

equat

eth

em

argi

nal

cost

wit

hth

em

argi

nal

ben

efit

ofan

extr

aunit

ofle

vera

gech

ange

.D

ue

toth

eunit

cost

ofad

just

ing,

when

the

firm

adju

sts

itw

ill

adju

stin

the

dir

ecti

onof

the

stat

icop

tim

um

,but

itw

ill

only

gopar

tof

the

way

.G

oing

furt

her

wou

ldnot

be

wor

thth

eex

tra

cost

.

29

Table I

Data description

Distribution

Variable N Mean SD 10th 50th 90th

Debt ($ millions) 179,021 653.01 4,591.84 0.00 24.10 1,047.90Book equity ($ millions) 179,021 814.69 4,122.31 3.31 69.97 1,372.58

Market equity ($ millions) 179,021 1,783.77 9,589.09 8.56 118.33 2,697.70

Assets ($ millions) 179,021 2,191.30 11,530.12 10.12 153.00 3,574.98

Debt issuance ($ millions) 179,021 165.29 1,335.28 0.00 1.58 244.54

Equity issuance ($ millions) 179,021 25.67 186.21 0.00 0.38 39.65

Debt repayment ($ millions) 179,021 131.96 1,123.38 0.00 2.87 181.19

Equity repurchase ($ millions) 179,021 24.32 257.48 0.00 0.00 9.19

Book leverage 179,021 0.36 0.34 0.00 0.31 0.72

Market leverage 179,021 0.27 0.25 0.00 0.20 0.66

Profitability 179,021 0.05 0.27 -0.18 0.11 0.23MB 179,021 1.65 2.06 0.52 1.02 3.24

Tangibility 179,021 0.31 0.24 0.05 0.26 0.70

Data sources: The sample comes from the annual Compustat files. The sample period is 1971–2009. Weexclude financial companies (SIC 6000-6999), firms involved in major mergers (Compustat footnote codeAB), firms reporting financial data in currencies other than the U.S. dollar, and firms with missing dataon the key variables. All financial variables are deflated to year 2000 using the GDP deflator. The ratiovariables are trimmed at the 1% level in both tails of the distribution. This serves to remove outliers andthe most extremely misrecorded data.

Variable definitions:

Debt = Long-term debt (dltt) + Short-term debt (dlc)Book equity = Common shareholder equity (ceq)

Market equity = Number of outstanding shares (csho) × Closing share price (prcc f)Assets = Book assets (at)

Debt issuance = Issuance of long-term debt (Max(dltis, 0)) + Increase in current debt (Max(dlcch, 0))Equity issuance = Sale of common stock (Max(sstk, 0))Debt repayment = Reduction of long-term debt (Max(dltr, 0)) + Decrease in current debt (−Min(dlcch, 0))

Equity repurchase = Purchase of common stock (Max(prstkc, 0))Cash balance = Cash and marketable securities (che)

Book leverage = Debt/(Debt + Book equity)Market leverage = Debt/(Debt + Market equity)

Profitability = EBITDA (oibdp)/Total assets (at)Market-to-book ratio = Market value of assets (MVA)/Assets,

where MVA = Debt + Market equity + Preferred-liq. value (pstkl)- Deferred taxes (txditc)

Tangibility = Net property plant and equipment (ppent)/Total assets (at)

30

Tab

leII

:R

egre

ssio

ns

of

Book

and

Mark

et

Levera

ge

Rati

os

Th

eta

ble

pre

sents

esti

mat

esof

the

leve

rage

rati

ore

gre

ssio

ns

on

firm

chara

cter

isti

cs.

Th

esa

mp

leco

mes

from

the

an

nu

al

Com

pu

stat

file

sd

uri

ng

the

per

iod

1971

-200

9.F

inan

cial

firm

sare

excl

ud

ed.

Pan

elA

pre

sents

esti

mate

sof

the

book

leve

rage

esti

mate

das

the

rati

oof

deb

tov

erd

ebt

plu

sb

ook

equ

ity.

Pan

elB

pre

sents

esti

mat

esof

mark

etle

vera

ge,

esti

mate

das

the

rati

oof

deb

tov

erd

ebt

plu

sm

ark

eteq

uit

y.T

he

exp

lan

ato

ry

vari

able

sProfitability

t−1,( M B

) t−1,Tangibility t−1,

an

dLn

(Assets)

t−1

are

des

crib

edin

Tab

leI.IndMedianLev

t−1

ises

tim

ate

das

the

med

ian

book

leve

rage

ofal

loth

erfi

rms

inth

esa

me

ind

ust

ryin

Pan

elA

,an

das

the

med

ian

mark

etle

vera

ge

of

all

oth

erfi

rms

inth

esa

me

ind

ust

ry

inP

anel

B.

Th

ein

du

stry

isd

efin

edat

the

level

of

the

4-d

igit

SIC

cod

e.A

llsp

ecifi

cati

on

sin

clu

de

the

year

fixed

effec

ts.

Th

esp

ecifi

cati

on

s

inco

lum

n(2

)ad

dit

ion

ally

incl

ud

eth

efi

rmfi

xed

effec

ts.

We

rep

ort

t-st

ati

stic

sw

her

eth

est

an

dard

erro

rsare

clu

ster

edat

the

firm

level

in

par

enth

eses

.aS

ign

ifica

nt

atth

e1

per

cent

leve

l.

PanelA:BookLevera

ge

Qu

anti

leR

egre

ssio

ns

OL

Sw

ith

Fix

edE

ffec

tsw

ith

25th

%il

eM

edia

n75th

%il

eC

lust

ered

SE

Clu

ster

edS

ER

egre

ssio

nR

egre

ssio

nR

egre

ssio

n(1

)(2

)(3

)(4

)(5

)

Profitability

t−1

-0.2

55a

-0.1

97a

-0.1

05a

-0.1

70a

-0.4

06a

(-29

.3)

(-19.2

)(-

37.8

)(-

51.8

)(-

101.5

)

IndMedianLev

t−1

0.42

2a

0.1

23a

0.2

96a

0.5

24a

0.5

24a

(36.

9)(1

0.7

)(9

2.6

)(1

25.2

)(9

5.0

)( M B

) t−1

-0.0

16a

-0.0

09a

-0.0

10a

-0.0

16a

-0.0

23a

(-20

.3)

(-10.2

)(-

39.2

)(-

42.6

)(-

41.8

)

Tangibility t−1

0.18

4a

0.2

46a

0.2

39a

0.1

93a

0.1

23a

(20.

6)(1

5.4

)(9

6.4

)(5

8.0

)(2

7.6

)

Ln

(Assets)

t−1

0.01

1a

0.0

22a

0.0

24a

0.0

18a

0.0

05a

(11.

4)(7

.6)

(89.9

)(4

7.8

)(9

.6)

Constant

0.11

9a

0.0

98a

-0.1

19a

0.0

16a

0.2

94a

(15.

6)(6

.0)

(-28.4

)(2

.7)

(38.7

)

Yea

rF

ixed

Eff

ects

Yes

Yes

Yes

Yes

Yes

Fir

mF

ixed

Eff

ects

No

Yes

No

No

No

R2-A

dju

sted

0.13

00.5

41

Pse

ud

oR

20.1

60

0.1

50

0.0

92

Observations

158,

824

158,8

24

158,8

24

158,8

24

158,8

24

31

Table

IIC

onti

nued

PanelB:M

ark

etLevera

ge

Qu

anti

leR

egre

ssio

ns

OL

Sw

ith

Fix

edE

ffec

tsw

ith

25th

%il

eM

edia

n75th

%il

eC

lust

ered

SE

Clu

ster

edS

ER

egre

ssio

nR

egre

ssio

nR

egre

ssio

n(1

)(2

)(3

)(4

)(5

)

Profitability

t−1

-0.1

29a

-0.1

29a

-0.0

71a

-0.1

05a

-0.1

97a

(-27

.5)

(-26.2

)(-

34.9

)(-

42.5

)(-

53.8

)

IndMedianLev

t−1

0.45

6a

0.1

99a

0.3

22a

0.5

77a

0.6

33a

(50.

6)(2

3.9

)(1

29.9

)(1

63.0

)(1

04.2

)( M B

) t−1

-0.0

30a

-0.0

14a

-0.0

13a

-0.0

21a

-0.0

35a

(-50

.9)

(-30.3

)(-

74.3

)(-

70.9

)(-

53.4

)

Tangibility t−1

0.12

9a

0.1

82a

0.1

32a

0.1

43a

0.1

02a

(19.

1)(1

8.1

)(7

6.2

)(5

7.1

)(2

3.2

)

Ln

(Assets)

t−1

0.00

9a

0.0

48a

0.0

13a

0.0

10a

0.0

01a

(11.

2)(2

5.8

)(6

8.2

)(3

4.2

)(2

.9)

Constant

0.10

0a

-0.1

12a

-0.0

49a

0.0

50a

0.2

90a

(17.

1)(-

9.8

)(-

17.3

)(1

1.8

)(3

9.8

)

Yea

rF

ixed

Eff

ects

Yes

Yes

Yes

Yes

Yes

Fir

mF

ixed

Eff

ects

No

Yes

No

No

No

R2-A

dju

sted

0.30

30.6

74

Pse

ud

oR

20.1

57

0.2

25

0.2

05

Observations

158,

578

158,5

78

158,5

78

158,5

78

158,5

78

32

Tab

leII

I:D

ebt

and

equit

yis

suers

:P

rofita

bil

ity

sort

s

Th

esa

mp

leco

nta

ins

non

-fin

anci

alfi

rms

list

edon

the

an

nu

alC

om

pu

stat

file

sfo

rth

ep

erio

dfr

om1971

to2009.

Th

eta

ble

pre

sents

the

per

centa

ge

offi

rms

issu

ing

and

reti

rin

g(o

rre

pu

rch

asin

g)d

ebt

an

deq

uit

y.A

firm

iscl

ass

ified

as

‘iss

uin

gd

ebt’

ifit

issu

esd

ebt

inex

cess

of

5%

of

the

valu

e

ofit

sas

sets

;as

‘iss

uin

geq

uit

y’

ifit

issu

eseq

uit

yin

exce

ssof

5%

of

the

valu

eof

its

ass

ets;

as

‘ret

irin

gd

ebt’

ifit

reti

res

deb

tin

exce

ssof

5%

of

the

valu

eof

its

asse

ts;

and

as‘r

epu

rch

asin

geq

uit

y’

ifit

rep

urc

hase

seq

uit

yin

exce

ssof

5%

of

the

valu

eof

its

ass

ets.

Inad

dit

ion

,w

eals

ore

port

net

-deb

tis

suer

s,w

hic

har

efi

rms

that

issu

en

etd

ebt

over

5%

of

the

valu

eof

thei

rass

ets,

an

dn

eteq

uit

yis

suer

s,w

hic

hare

firm

sth

at

issu

en

et

equ

ity

inex

cess

of5%

ofth

eva

lue

ofth

eir

asse

ts.

We

an

nu

all

yso

rtfi

rms

on

lagged

pro

fita

bil

ity

an

dre

port

the

per

centa

ge

of

firm

sin

each

of

thes

eca

tego

ries

.T

he

bot

tom

par

tof

the

tab

lere

port

sth

ep

erce

nta

ge

of

firm

sis

suin

gor

reti

rin

gse

curi

ties

by

pro

fita

bil

ity

wit

hin

the

small

est

and

larg

est

asse

tqu

inti

les.

33

Table

III

Conti

nued

Per

cen

tage

of

firm

s

Issu

ing

Ret

irin

gIs

s.N

etIs

suin

gR

epu

rch

.Is

s.N

etIs

s.B

oth

Iss.

Deb

tIs

s.E

qu

ity

Iss.

Non

eD

ebt

Deb

tD

ebt

Equ

ity

Equ

ity

Equ

ity

D&

ER

ep.

Equ

ity

Ret

.D

ebt

Rep

.N

on

e

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Sort

son

firm

pro

fita

bili

ty

Allfirms

Low

π27

.624

.518

.630.1

1.3

29.7

7.1

0.1

3.8

28.7

231

.929

.918

.111.7

2.1

11.2

2.7

0.2

2.0

38.6

338

.534

.419

.48.6

2.9

8.0

2.1

0.5

1.5

36.9

438

.633

.021

.38.1

4.3

7.5

2.0

0.7

1.4

37.2

Hig

hπ

32.9

27.3

19.8

9.2

8.2

8.1

1.7

1.3

1.4

40.3

Smallfirms

Low

π27

.520

.420

.141.1

1.1

40.5

10.9

0.1

4.7

16.0

229

.123

.321

.337.9

1.0

37.8

9.9

0.1

4.5

24.0

328

.124

.620

.426.5

1.4

26.1

6.6

0.1

4.1

32.1

427

.527

.218

.616.2

1.5

15.9

3.4

0.2

3.5

38.6

Hig

hπ

27.5

28.1

17.8

13.6

2.7

13.1

2.5

0.2

2.6

40.1

Largefirms

Low

π41

.436

.317

.78.7

2.2

7.9

2.8

0.3

1.1

35.4

244

.937

.918

.06.2

3.0

5.7

1.7

0.7

0.9

35.8

343

.936

.018

.65.6

4.1

4.8

1.6

0.9

0.7

37.6

440

.332

.019

.44.6

6.7

3.9

1.3

1.2

0.6

39.3

Hig

hπ

37.4

26.4

20.7

5.0

12.9

3.5

1.0

2.8

0.5

41.1

34

Tab

leIV

:M

agnit

ude

of

Fin

anci

ng

Act

ivit

y

Th

esa

mp

leco

nta

ins

non

-fin

anci

alfi

rms

list

edon

the

an

nu

al

Com

pu

stat

file

sfo

rth

ep

erio

dfr

om

1971

to2009.

Th

eta

ble

pre

sents

aver

age

deb

tan

deq

uit

y,ch

ange

sin

deb

tan

deq

uit

yan

deq

uit

yis

suan

ces

(in

mil

lions

of

doll

ars

)fo

rfi

rms

sort

edon

pro

fita

bil

ity

wit

hin

size

class

es.

Th

eta

ble

rep

orts

info

rmat

ion

for

all

firm

sso

rted

on

pro

fita

bil

ity

an

dfo

rp

rofi

tab

ilit

yso

rts

wit

hin

the

small

est

an

dla

rges

tfi

rms.

Th

eso

rts

are

don

ean

nu

ally

.

D∆D

BV

E∆BVE

MV

E∆MVE

Equ

ity

Iss.

Ass

ets

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

AllFirms

Low

π82

.8-4

.777.8

-9.7

119.

7-4

.56.6

233.9

260

4.9

-13.

4508.6

-23.8

720.

6-7

.516.8

1,6

90.8

31,

226.

78.

71,1

22.7

-21.9

1,8

33.6

3.2

8.5

3,5

50.9

483

3.4

23.3

1,1

66.0

6.9

2,4

07.

673.7

-7.9

2,9

94.1

Hig

hπ

570.

253

.41,1

70.5

71.1

3,8

17.

167.7

-36.1

2,5

81.2

SmallFirms

Low

π2.

50.

44.2

0.1

33.

22.8

3.3

9.7

22.

90.

65.5

-0.2

27.8

1.6

2.1

11.6

33.

10.

76.3

0.1

21.2

0.5

1.2

12.7

43.

00.

67.0

0.5

17.9

1.0

0.8

13.6

Hig

hπ

2.4

0.6

8.4

1.4

23.4

1.7

0.7

14.2

Largefirms

Low

π3,

928.

6-5

5.4

2,9

89.9

-152.1

4,6

71.2

10.8

62.5

10,8

46.3

23,

825.

619

.13,1

77.7

-94.5

5,1

22.2

-66.1

11.0

10,7

21.4

33,

074.

326

.83,4

97.9

-41.1

6,1

73.0

241.6

9.4

9,6

97.3

42,

622.

762

.03,9

14.8

45.2

8,4

72.

794.4

-57.0

9,8

54.7

Hig

hπ

2,18

0.4

192.

94,6

41.6

261.3

14,9

24.

1202.1

-147.8

10,1

70.5

35

Tab

leV

:M

edia

nP

rofita

bil

ity

Sort

s

Th

esa

mp

leco

nta

ins

non

-fin

anci

alfi

rms

list

edon

the

an

nu

al

Com

pu

stat

file

sfo

rth

ep

erio

dfr

om

1971

to2009.

Th

eta

ble

pre

sents

med

ian

deb

t

and

equ

ity,

med

ian

chan

ges

ind

ebt

and

equ

ity,

and

med

ian

equ

ity

issu

an

ces

(in

mil

lion

sof

doll

ars

)fo

rfi

rms

sort

edon

pro

fita

bil

ity

wit

hin

size

clas

ses.

Th

eta

ble

rep

orts

info

rmat

ion

for

all

firm

sso

rted

on

pro

fita

bil

ity

an

dfo

rp

rofi

tab

ilit

yso

rts

wit

hin

the

small

est

an

dla

rges

tfi

rms.

Th

e

sort

sar

ed

one

annu

ally

.

D∆D

BV

E∆BVE

MV

E∆MVE

Equ

ity

Iss.

Ass

ets

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

AllFirms

Low

π2.

10.

07.5

-1.7

25.

6-2

.00.1

19.2

218

.6-0

.244.9

-1.8

59.8

-1.9

0.0

110.3

381

.6-0

.6127.4

-0.3

163.7

-0.5

0.0

322.4

478

.7-0

.2154.1

1.8

248.8

0.3

0.0

355.6

Hig

hπ

27.3

0.0

136.1

6.6

330.

01.4

0.0

257.8

SmallFirms

Low

π0.

50.

01.3

-0.7

14.

0-1

.40.6

4.0

20.

60.

02.5

-0.8

11.4

-1.2

0.1

5.6

30.

90.

03.2

-0.5

8.5

-0.7

0.0

6.7

41.

20.

03.9

-0.1

6.8

-0.3

0.0

7.9

Hig

hπ

1.0

0.0

5.1

0.4

9.8

-0.1

0.0

9.0

Largefirms

Low

π1,

148.

5-3

8.1

1,0

26.9

-37.1

1,3

22.7

-20.2

0.3

3,3

39.0

21,

305.

1-3

9.3

1,2

78.6

-14.0

1,7

57.

116.9

0.5

3,9

24.6

31,

155.

4-2

8.7

1,3

42.9

-2.4

2,1

62.

330.5

0.0

3,7

03.1

499

6.3

-20.

91,5

05.2

19.4

2,9

42.

430.8

0.0

3,6

70.5

Hig

hπ

736.

10.

01,6

38.0

61.3

4,9

14.

243.9

0.0

3,4

97.6

36

Tab

leV

I:D

ebt

and

Equit

yC

hanges

Th

esa

mp

leco

nta

ins

non

-fin

anci

alfi

rms

list

edon

the

an

nu

al

Com

pu

stat

file

sfo

rth

ep

erio

dfr

om

1971

to2009.

Th

eta

ble

pre

sents

esti

mate

s

from

regr

essi

ons

of

chan

gein

deb

t(∆D

),ch

ange

inth

eb

ook

valu

eof

equ

ity

(∆BVE

),ch

an

gein

the

mark

etva

lue

of

equ

ity

(∆MVE

),an

dn

et

equ

ity

issu

ance

s(EquityIss.)

.T

he

exp

lan

ator

yva

riab

les

incl

ud

ecu

rren

tan

dla

gged

chan

ge

inop

erati

ng

inco

me

bef

ore

dep

reci

ati

on

(∆Profits

and

∆Profits t−1

)an

dla

gged

chan

gein

book

valu

eof

ass

ets

(∆Assets t−1).

Th

ere

gre

ssio

ns

incl

ud

eyea

rin

dic

ato

rva

riab

les.

Th

ere

port

ed

t-st

atis

tics

are

corr

ecte

dfo

rcl

ust

erin

gat

the

firm

leve

l.a,b,

an

dc

mea

nsi

gn

ifica

nt

at

the

1%

,5%

,an

d10%

leve

l,re

spec

tive

ly.

∆D

∆BVE

∆MVE

EquityIss.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

∆Profits t−1

0.25

4a

0.23

6a

0.2

33a

0.3

80a

0.0

70

0.6

61a

-0.0

70a

-0.0

93a

(4.0

)(3

.2)

(3.6

)(3

.9)

(0.6

)(2

.9)

(-4.2

)(-

5.1

)

∆Profits

0.50

9b

0.8

20a

1.4

87a

-0.0

43a

(2.5

)(3

.3)

(4.9

)(-

3.3

)

∆Assets t−1

0.01

7-0

.053c

-0.2

42a

0.0

09b

(0.8

)(-

1.7

)(-

3.4

)(2

.3)

Constant

-9.2

83-1

7.55

5a

-4.5

12

-7.1

32

155.1

52a

170.3

95a

12.9

52a

13.9

60a

(-1.

2)(-

2.8)

(-0.7

)(-

0.9

)(4

.9)

(4.9

)(4

.5)

(4.5

)

Yea

reff

ects

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

R2−Adjusted

0.00

90.

047

0.0

09

0.1

07

0.0

13

0.0

54

0.0

15

0.0

21

Observations

162,

056

162

,056

162,1

30

162,1

30

157,5

50

157,5

50

162,1

54

162,1

54

37

Tab

leV

II:D

ebt

and

Equit

yC

hanges

–F

ixed

Eff

ect

s

Th

esa

mp

leco

nta

ins

non

-fin

anci

alfi

rms

list

edon

the

an

nu

al

Com

pu

stat

file

sfo

rth

ep

erio

dfr

om

1971

to2009.

Th

eta

ble

pre

sents

fixed

-eff

ect

esti

mat

esfr

omre

gres

sion

sof

chan

ges

ind

ebt

(∆D

),ch

an

ges

inth

eb

ook

valu

eof

equ

ity

(∆BVE

),ch

an

ges

inth

em

ark

etva

lue

of

equ

ity

(∆MVE

),an

dn

eteq

uit

yis

suan

ces

(EquityIss.)

.T

he

exp

lan

ato

ryva

riab

les

incl

ud

ecu

rren

tan

dla

gged

chan

ge

inop

erati

ng

inco

me

bef

ore

dep

reci

atio

n(∆Profits

and

∆Profits t−1

),an

dla

gged

chan

ge

inth

eb

ook

valu

eof

ass

ets

(∆Assets t−1).

Inad

dit

ion

tofi

xed

firm

effec

t,th

e

regr

essi

ons

incl

ud

eyea

rin

dic

ator

vari

able

s.T

he

rep

ort

edt-

stati

stic

sare

corr

ecte

dfo

rcl

ust

erin

gat

the

firm

leve

l.a,b

,an

dc

mea

nsi

gn

ifica

nt

atth

e1%

,5%

,an

d10

%le

vel,

resp

ecti

vel

y.

∆D

∆BVE

∆MVE

EquityIss.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

∆Profits t−1

0.21

6a

0.24

8a

0.1

51b

0.3

45a

-0.0

38

0.5

95b

-0.0

46b

-0.0

74a

(3.3

)(3

.1)

(2.5

)(3

.5)

(-0.3

)(2

.5)

(-2.5

)(-

5.3

)

∆Profits

0.50

0b

0.7

83a

1.4

04a

-0.0

33a

(2.4

)(3

.2)

(4.8

)(-

3.4

)

∆Assets t−1

0.00

0-0

.067b

-0.2

53a

0.0

12b

(0.0

)(-

2.1

)(-

3.5

)(2

.5)

Constant

-16.

699

-28.

300a

3.4

34

-5.1

35

114.4

70a

118.2

30a

60.4

91a

59.4

87a

(-1.

4)(-

3.0)

(0.4

)(-

0.5

)(3

.2)

(2.9

)(6

.9)

(7.4

)

Yea

reff

ects

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Fir

meff

ects

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

R2−Adjusted

0.00

70.

041

0.0

05

0.1

00

0.0

13

0.0

53

0.0

18

0.0

27

Observations

162,

056

162

,056

162,1

30

162,1

30

157,5

50

157,5

50

162,1

54

162,1

54

38

Tab

leV

III:

Deb

tan

dE

qu

ity

Issu

ance

s,P

rofita

bil

ity

and

Levera

ge

Fact

or

Qu

inti

les

Th

esa

mp

leco

nta

ins

non

-fin

anci

alfi

rms

list

edon

the

an

nu

al

Com

pu

stat

file

sfo

rth

ep

erio

dfr

om

1971

to2009.

Th

eta

ble

pre

sents

esti

mate

s

from

regr

essi

ons

ofch

ange

ind

ebt

(∆D

),ch

ange

inth

eb

ook

valu

eof

equ

ity

(∆BVE

),ch

an

ge

inth

em

ark

etva

lue

of

equ

ity

(∆MVE

),an

d

net

equ

ity

issu

ance

s(EquityIss.)

.T

he

exp

lan

atory

vari

ab

les

incl

ud

ela

gged

pro

fita

bil

ity

qu

inti

les

an

dla

gged

leve

rage

fact

or

qu

inti

les.

Th

e

regr

essi

ons

incl

ud

eyea

rin

dic

ator

vari

able

s.T

he

rep

ort

edt-

stati

stic

sare

corr

ecte

dfo

rcl

ust

erin

gat

the

firm

leve

l.a,b

,an

dc

mea

nsi

gn

ifica

nt

atth

e1%

,5%

,an

d10

%le

vel,

resp

ecti

vel

y.

∆D

∆BVE

∆MVE

EquityIss.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Pro

fita

bil

ity

Qu

inti

le15

.019

a9.5

01a

20.6

11a

15.1

50a

19.1

18a

22.6

39a

-12.0

81a

-11.4

49a

(10.

2)(6

.2)

(9.3

)(1

0.1

)(3

.2)

(5.0

)(-

8.9

)(-

12.6

)

Ind

ust

ryM

edia

nL

ever

age

Qu

inti

le0.9

95

-0.7

04

-17.9

64a

3.8

93a

(0.6

)(-

0.4

)(-

3.2

)(3

.3)

Ass

etQ

uin

tile

13.7

95a

4.8

38c

-3.7

30

-6.0

09a

(3.6

)(1

.9)

(-0.6

)(-

3.3

)

Mar

ket/

Book

Qu

inti

le11.0

28a

25.9

50a

-39.3

66a

0.0

62

(4.8

)(7

.9)

(-6.0

)(0

.1)

Tan

gib

ilit

yQ

uin

tile

-1.3

58

3.3

21

22.8

78a

3.5

85a

(-0.8

)(1

.3)

(3.9

)(2

.9)

Constant

-68.

802a

-124.6

39a

-89.7

28a

-173.8

60a

53.6

46

156.7

15b

48.8

84a

42.6

42a

(-9.

0)(-

9.4

)(-

9.6

)(-

8.1

)(1

.4)

(2.5

)(9

.6)

(4.6

)

Yea

reff

ects

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

R2−Adjusted

0.00

20.0

02

0.0

03

0.0

04

0.0

12

0.0

13

0.0

10

0.0

11

Observations

155,

587

155,0

37

155,5

87

155,0

37

155,5

87

155,0

37

155587

155,0

37

39

Table IX

Debt and Equity Issues in Good and Bad Times

The table reports the frequency and magnitude of financing activity for sorts on profits for sub-samples

of firms in good and bad times. An industry is defined as having “good times” if the median firm in that

industry has a market-to-book ratio that is higher than the 67th percentile of the time-series distribution

of industry median market-to-book ratios. Conversely, an industry is defined as having bad times if the

median firm in that industry has a market-to-book ratio that is lower than the 33rd percentile of the

time-series distribution of industry median market-to-book ratios. Panels A and B report the percentage

of firms (a) issuing net debt in excess of 5% of the value of their assets, (b) issuing net equity in excess of

5% of the value of their assets, (c) issuing debt and repurchasing equity both in excess of 5% of the value

of their assets, and (d) issuing equity and retiring debt both in excess of 5% of the value of their assets.

Panel C tabulates the mean debt and equity levels, and the mean changes in debt and equity issuances.

The sample contains non-financial firms listed on the annual Compustat files for the period from 1971 to

2009.

40

Table IX Continued

Issuing Issuing Issuing Debt Iss. EquityNet Debt Net Equity Rep. Equity Ret. Debt

(1) (2) (3) (4)

Panel A: Sorts on Profitability

Bad

Tim

es Low Profits 14.5 13.1 0.1 2.0

2 17.0 4.9 0.2 0.8

3 17.3 4.6 0.4 0.7

4 18.2 4.7 0.3 1.0

High Profits 17.7 5.1 0.6 1.0

Good

Tim

es Low Profits 20.6 38.1 0.1 4.6

2 19.7 14.8 0.2 2.3

3 21.2 10.3 0.4 1.8

4 23.4 9.2 1.0 1.8

High Profits 21.6 9.2 1.6 1.4

Panel B: Sorts on firm size and profitability

Bad

Tim

es

Sm

all

Fir

ms Low Profits 15.1 31.8 0.0 3.1

2 18.2 27.6 0.2 2.5

3 15.1 14.0 0.2 2.9

4 18.3 7.3 0.0 1.9

High Profits 17.7 8.0 0.0 1.1

Lar

gefi

rms Low Profits 17.2 5.4 0.1 0.4

2 14.8 3.9 0.4 0.5

3 15.0 4.3 0.4 0.4

4 15.6 3.3 0.3 0.6

High Profits 14.7 2.8 0.5 0.3

Good

Tim

es

Sm

all

Fir

ms Low Profits 21.3 44.8 0.1 5.4

2 23.0 44.3 0.1 4.7

3 22.2 32.5 0.0 4.7

4 20.3 19.7 0.2 3.8

High Profits 19.0 15.3 0.2 3.1

Lar

gefi

rms Low Profits 20.3 9.6 0.3 1.2

2 20.8 6.6 0.9 1.3

3 23.2 5.4 1.6 0.6

4 21.5 3.9 1.9 0.5

High Profits 23.4 3.6 3.8 0.4

41

Table

IXC

onti

nued

D∆D

BV

E∆BVE

MV

E∆MVE

Equ

ity

Iss.

Ass

ets

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Pan

elC

:M

agn

itu

de

of

Fin

an

cin

gA

ctiv

ity

(Mea

ns)

BadTimes

SmallFirms

Low

π4.

00.3

5.8

-1.4

30.5

-0.6

2.2

14.0

24.4

0.5

8.2

-0.7

24.0

6.7

1.7

18.0

34.5

0.4

9.4

-0.2

17.6

1.8

0.5

18.7

44.3

0.9

9.8

0.2

13.7

-0.4

0.3

18.8

Hig

hπ

3.6

1.0

11.4

1.3

20.9

-1.6

0.4

19.9

Largefirms

Low

π3,

364.

7-7

2.9

2,5

22.8

-169.2

2,3

04.4

163.3

94.4

8,9

71.5

23,

030.6

-95.2

2,9

83.4

-35.4

3,2

84.0

277.5

56.0

9,0

67.5

32,

930.1

4.9

3,3

59.8

-13.9

3,9

47.1

307.6

56.8

9,2

24.7

42,

280.6

-6.4

3,8

16.7

19.4

5,2

13.1

441.5

-6.6

8,9

02.2

Hig

hπ

1789

.962.0

4,7

66.9

13.0

8,7

99.1

58.3

-31.4

9,5

73.4

GoodTimes

SmallFirms

Low

π2.

40.6

3.8

0.5

33.9

2.3

3.9

9.0

22.

60.8

4.8

-0.1

30.1

-0.4

2.5

10.4

33.

00.9

6.0

0.4

24.6

-0.3

1.7

12.5

42.

80.7

6.6

0.8

20.6

1.8

1.2

13.0

Hig

hπ

2.3

0.6

8.5

1.6

26.1

1.3

0.8

14.1

Largefirms

Low

π4,

532.

236.0

3,4

76.7

-103.1

6,5

57.2

-259.5

52.9

12,4

65.1

24,

580.

357.5

3,5

27.3

-138.8

6,9

10.8

-421.4

-23.4

12,5

22.3

32,

951.

5111.4

3,4

85.1

-2.4

7,5

85.5

-278.7

-31.7

9,5

34.7

42,

752.

4124.2

3,9

38.6

71.6

10,6

85.8

-32.5

-104.5

10,2

26.0

Hig

hπ

2,42

8.5

228.1

4,8

18.9

376.5

18,5

65.1

268.2

-221.6

10,8

29.9

42

Tab

leX

:D

eb

tan

dE

quit

yC

hanges

inG

ood

and

Bad

Tim

es

–R

egre

ssio

ns

Th

esa

mp

leco

nta

ins

non

-fin

anci

alfi

rms

list

edon

the

an

nu

al

Com

pu

stat

file

sfo

rth

ep

erio

dfr

om

1971

to2009.

Th

eta

ble

pre

sents

esti

mate

s

from

regr

essi

ons

ofch

ange

ind

ebt

(∆D

)an

dn

eteq

uit

yis

suan

ces

(EquityIss.)

ingood

an

db

ad

tim

es.

Th

eex

pla

nato

ryva

riab

les

incl

ud

e

chan

gein

pro

fits

,la

gged

chan

gein

pro

fits

,an

dla

gged

chan

ge

inass

ets.

Th

ere

gre

ssio

ns

incl

ud

eye

ar

ind

icato

rva

riab

les.

An

ind

ust

ryis

defi

ned

ash

avin

g“g

ood

tim

es”

ifth

em

edia

nfi

rmin

that

ind

ust

ryhas

am

ark

et-t

o-b

ook

rati

oth

at

ish

igh

erth

an

the

67th

per

centi

leof

the

tim

e-se

ries

dis

trib

uti

onof

ind

ust

rym

edia

nm

arke

t-to

-book

rati

os.

Conve

rsel

y,an

ind

ust

ryis

defi

ned

as

hav

ing

bad

tim

esif

the

med

ian

firm

inth

at

ind

ust

ry

has

am

arket

-to-

book

rati

oth

atis

low

erth

anth

e33rd

per

centi

leof

the

tim

e-se

ries

dis

trib

uti

on

of

ind

ust

rym

edia

nm

ark

et-t

o-b

ook

rati

os.

Th

e

rep

orte

dt-

stat

isti

csar

eco

rrec

ted

for

clu

ster

ing

at

the

firm

leve

l.a,b,

an

dc

mea

nsi

gn

ifica

nt

at

the

1%

,5%

,an

d10%

leve

l,re

spec

tivel

y.

Good

Tim

esB

ad

Tim

es

∆D

EquityIss.

∆D

EquityIss.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

∆Profits

0.94

2a

0.92

2a

-0.1

13a

-0.1

39a

0.7

25

0.7

37c

-0.0

11

-0.0

12

(3.3

)(3

.0)

(-2.8

)(-

3.6

)(1

.6)

(1.7

)(-

0.6

)(-

0.7

)

∆Profits t−1

0.22

8c

-0.2

08a

0.2

44

-0.0

21

(1.7

)(-

3.5

)(1

.4)

(-1.4

)

∆Assets t−1

0.03

1b

0.0

19b

0.0

66

0.0

05

(2.3

)(2

.4)

(1.0

)(0

.5)

Constant

92.3

46a

-33.

480c

13.1

73c

7.8

77c

-7.3

12

14.0

27

3.4

71b

7.5

45

(2.7

)(-

1.9)

(1.8

)(1

.7)

(-0.8

)(1

.5)

(2.1

)(1

.5)

Yea

reff

ects

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

R2−Adjusted

0.08

60.

098

0.0

20

0.0

58

0.2

23

0.2

57

0.0

12

0.0

13

Observations

74,8

2768

,729

74,8

91

68,7

87

26,9

65

26,0

13

26,9

71

26,0

18

43

Tab

leX

I:Sca

led

issu

ance

s

Th

esa

mp

leco

nta

ins

non

-fin

anci

alfi

rms

list

edon

the

an

nu

al

Com

pu

stat

file

sfo

rth

ep

erio

dfr

om

1971

to2009.

Th

eta

ble

pre

sents

esti

mate

sfr

omre

gres

sion

sof

deb

tis

suan

ceto

tota

lis

suan

ce(i

nco

lum

n(1

)),

equ

ity

issu

an

ceto

tota

lis

suan

ce(i

nco

lum

n(2

)),

deb

tis

suan

ceto

tota

lca

pit

al(i

nco

lum

n(3

)),

equ

ity

issu

ance

toto

tal

cap

ital

(in

colu

mn

(4))

,ch

an

ge

ind

ebt

toca

pit

ali

zati

on

rati

o(i

nco

lum

n(5

)),

an

dch

an

ge

inle

vera

gera

tio

con

sid

erin

gon

lyex

tern

alfi

nan

cin

g(i

nco

lum

n(6

)).

Th

ech

an

ge

inle

ver

age

rati

oco

nsi

der

ing

on

lyex

tern

al

fin

an

cin

gis

defi

ned

as:

∆LeverageE

F=

Dt−

1+d

Dt−

1+E

t−1

+d

+e−

Dt−

1

Dt−

1+E

t−1,

(2)

wh

ere

Dis

deb

t,E

isb

ook

valu

eof

equ

ity,

dis

deb

tis

sues

net

of

reti

rem

ents

,an

de

iseq

uit

yis

sues

net

of

rep

urc

hase

s.T

he

regre

ssio

ns

incl

ud

e

lagg

edle

vera

gefa

ctor

san

dye

arin

dic

ator

vari

able

s.T

he

rep

ort

edt-

stati

stic

sare

corr

ecte

dfo

rcl

ust

erin

gat

the

firm

leve

l.a,b,

an

dc

mea

n

sign

ifica

nt

atth

e1%

,5%

,an

d10

%le

vel,

resp

ecti

vely

.

DebtI

ss

TotI

ss

EquityIss

TotI

ss

DebtI

ss

(D+E)

EquityIss

(D+E)

∆D

D+E

∆LeverageE

F

(1)

(2)

(3)

(4)

(5)

(6)

∆Profitability

t−1

0.04

4a

-0.0

44a

-0.0

15a

-0.0

67a

-0.0

33a

0.0

14b

(3.5

)(-

3.5

)(-

3.4

)(-

8.3

)(-

3.5

)(2

.3)

∆Ind.medianbookleverage t−1

0.04

2c

-0.0

42c

-0.0

07

-0.0

15a

0.0

01

0.0

01

(1.9

)(-

1.9

)(-

1.5

)(-

3.2

)(0

.2)

(0.3

)

∆Market/bookt−

1-0

.007

a0.0

07a

0.0

02a

0.0

08a

-0.0

04a

0.0

00

(-4.

7)(4

.7)

(6.8

)(1

0.6

)(-

5.5

)(0

.5)

∆Tangibility t−1

-0.0

370.0

37

0.1

25a

0.1

02a

0.1

05a

0.0

33a

(-1.

2)(1

.2)

(14.4

)(9

.8)

(7.9

)(4

.4)

∆Assets t−1

-0.0

78a

0.0

78a

0.0

57a

0.0

17a

0.0

15a

0.0

25a

(-9.

7)(9

.7)

(28.3

)(7

.0)

(5.3

)(1

4.7

)

Constant

0.78

2a

0.2

11a

0.0

12a

0.0

15a

0.0

00

0.0

03b

(46.

3)(1

3.3

)(6

.7)

(11.8

)(0

.0)

(2.2

)

Yea

reff

ects

Yes

Yes

Yes

Yes

Yes

Yes

R2−Adjusted

0.01

50.0

15

0.0

22

0.0

25

0.0

09

0.0

12

Observations

133,

905

133,9

06

140,5

52

140,7

33

138,2

29

140,5

72

44

Table XII

Externally Financed Leverage Changes in Good and Bad Times

The sample contains non-financial firms listed on the annual Compustat files for the period from 1971 to2009. The table presents estimates from regressions of change in debt to capitalization ratio (in columns(1) and (3)) and change in leverage ratio considering only external financing (in columns (2) and (4)).The change in leverage ratio considering only external financing is defined as:

∆LeverageEF =Dt−1 + d

Dt−1 + Et−1 + d+ e− Dt−1

Dt−1 + Et−1, (3)

where D is debt, E is book value of equity, d is debt issues net of retirements, and e is equity issues net of

repurchases. The regressions include lagged leverage factors and year indicator variables. The reported

t-statistics are corrected for clustering at the firm level. An industry is defined as having “good times”

if the median firm in that industry has a market-to-book ratio that is higher than the 67th percentile of

the time-series distribution of industry median market-to-book ratios. Conversely, an industry is defined

as having “bad times ” if the median firm in that industry has a market-to-book ratio that is lower than

the 33rd percentile of the time-series distribution of industry median market-to-book ratios. a, b, and c

mean significant at the 1%, 5%, and 10% level, respectively.

Good Times Bad Times

∆ DD+E ∆LeverageEF ∆ D

D+E ∆LeverageEF

(1) (2) (3) (4)

∆Profitabilityt−1 -0.022c 0.016c -0.073b -0.007(-1.7) (1.8) (-2.5) (-0.4)

∆Ind.medianbookleveraget−1 0.000 -0.001 -0.010 0.001(0.0) (-0.1) (-0.7) (0.2)

∆Market/bookt−1 -0.004a 0.000 -0.008a -0.000(-4.0) (0.5) (-2.8) (-0.3)

∆Tangibilityt−1 0.097a 0.033a 0.127a 0.059a

(4.5) (2.7) (4.9) (4.3)

∆Assetst−1 0.014a 0.024a 0.037a 0.036a

(3.0) (8.4) (4.5) (8.8)

Constant -0.009 -0.000 0.028c -0.021(-1.2) (-0.0) (1.7) (-1.1)

Year effects Yes Yes Yes Yes

R2 −Adjusted 0.006 0.009 0.026 0.023

Observations 56,820 58,200 23,462 23,511

45