2000 - does corporate hedging increase firm value- an empirical analysis

8/10/2019 2000 - Does Corporate Hedging Increase Firm Value- An Empirical Analysis

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Does Corporate Hedging Increase Firm Value?

An Empirical Analysis1

John R. Grahama, Daniel A. Rogers ,b

aFuqua School of Business, Duke University, Durham, NC 27708-0120, USAbNortheastern University, Boston, MA 02115, USA

January 20, 2000

Abstract

We study the derivative holdings of firms facing interest rate and/or currency risk. We net long and short

positions to measure the extent of hedging with net notional values. Our results are consistent with firms

hedging in response to expected financial distress costs, firm size, and investment opportunities, and also

to increase debt capacity and therefore firm value. Corporate hedging is not related to an explicit

estimate of the convexity in each firm's tax function. The tax gain associated with increased debtcapacity is much larger than the potential increase in value related to tax convexity.

JEL classification: G39; G32

Keywords: Corporate hedging; Derivatives; Capital structure; Taxes

1We thank Tim Adam, George Allayannis, Hank Bessembinder, Gordon Bodnar, Nick Bollen, David Haushalter, Eric

Hughson, Ron Lease, Mike Lemmon, Uri Loewenstein, Steve Manaster, Mitchell Petersen, Jim Schallheim, CathySchrand, Betty Simkins, Cliff Smith, Liz Tashjian, Wayne Thomas, Sheridan Titman, Bob Whaley, Jaime Zender, and

seminar participants at the 2000 AFA meeting, California State University-Northridge, the 1999 EFA meeting, the 1999

FMA meeting, Fordham University, Marquette University, Northeastern University, Oklahoma State University,

Southern Methodist University, University of Utah, Washington State University, and Wilfrid Laurier University for

helpful comments and suggestions. We also appreciate the research assistance of Yong Cai, Suzanne Perlee, and Ge

Zhang. This paper builds upon Rogers dissertation at the University of Utah.

Corresponding author. Tel.: 617/373-4707; fax: 617/373-8798; e-mail: [email protected].


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If capital markets are perfect, hedging with derivative financial instruments (derivatives) does

not add to firm value, so firms should not hedge. Yet, an increasing number of firms use derivatives each

year. The International Swaps and Derivatives Association (ISDA) reports (on its Internet site,

http://www.isda.org) that the notional value of outstanding OTC derivative contracts more thanquadrupled from 1994 to 1999, increasing from $11.3 to over $50 trillion. A large body of theoretical

research identifies costly market imperfections that, if they exist, explain why firms might hedge (see

Section I for a literature review). A number of empirical studies examine derivative holdings to identify

which of the theoretical incentives and imperfections lead to corporate hedging. Our paper adds to the

empirical literature by determining the factors that are related to corporate hedging for a unique sample

of firms facing interest rate and currency risk.

We use net notional derivative holdings to measure hedging for a broad cross-section of U.S.

firms with ex ante risk exposure. Our data are different from, and in many cases better than, those used

in previous studies of corporate hedging. Effective December 15, 1994, SFAS 119 requires firms to

report detailed information on the direction and purpose of notional derivative holdings, which makes it

possible to net long and short positions. (Prior to SFAS 119, notional values in financial statements

were aggregated across derivative type, and therefore it was not possible to reliably net derivative

positions.) Among research that uses financial statements to identify the determinants of hedging, ours is

the only study to determine net positions based on SFAS 119.2Our net derivatives variable measures

the extent of hedging activity more precisely than variables used in past research.

Our dependent variable allows us to study the extent of derivative holdings, which differentiates

our paper from many corporate hedging papers. As summarized in Table I, most of the early empirical

hedging papers either use survey data (e.g., Nance, Smith, and Smithson, 1993; and Dolde, 1995) or

study the binary decision of whether or not to hedge (e.g., Mian, 1996; and Gczy, Minton, and

Schrand, 1997). Some recent papers use aggregated notional values of derivative holdings to study the

extent of hedging (e.g., Allayannis and Ofek, 1998; Berkman and Bradbury, 1996; Gay and Nam,

1999; and Howton and Perfect, 1999). However, these aggregated measures are not modified for

offsetting long and short payoffs, and so they are less precise than our dependent variable.

2Wong (1997) uses SFAS 119 data to examine whether net notional value reliably measures currency exposure.


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We restrict our sample to firms that face ex ante currency or interest rate risk. This is important

because we can interpret a lack of derivative holdings as a decision by a firm to hedge none of its risks,

which is distinct from not holding derivatives because of a lack of exposure to hedgeable risks. Other

studies that restrict their samples to firms with ex ante exposure include Gczy, Minton, and Schrand(1997), Tufano (1996) and Haushalter (2000). These papers examine either the binary hedging decision

or hedging within a single industry, while we study the extent of hedging for a broad cross-section of

firms. Studying a broad cross-section also sets our paper apart from most other empirical hedging

papers, many of which examine large, Fortune 500-type firms (see Table I).

In sum, we use a relatively precise dependent variable to determine which market imperfections

lead to corporate hedging among firms with ex ante interest rate or currency risk exposure, and for a

broader cross-section than studied in most hedging research. We believe that using this sample and

hedging data contribute to the body of knowledge, even if we were to only examine the same

hypotheses studied in other papers.

In addition to the advantages offered by the data, our paper makes three contributions to the

literature investigating the causes of corporate hedging. First, we study whether firms hedge in response

to tax function convexity. Smith and Stulz (1985) show that if the function that maps income into tax

liability is convex, then by Jensen's Inequality, firms can reduce expected tax liabilities by hedging to

reduce income volatility. As summarized in Table I, virtually every empirical study that investigates the

use of derivatives includes a variable to proxy for tax function convexity. As we argue below, these

variables are, at best, imprecise measures of tax function convexity. We use a variant of the Graham and

Smith (1999) approach to explicitly calculate tax function convexity, and find no relation between

derivative holdings and tax function convexity. Although not finding evidence that firms hedge in

response to tax function convexity is a "non-result", we think it is important because it implies that other

research either needs to be reinterpreted or else use a more precise measure of convexity.

The second contribution is our investigation of whether firms hedge in response to an alternative

tax-related incentive to hedge, namely, hedging to increase debt capacity. Ross (1997) and Leland

(1998) model the primary benefit of debt financing as the tax deductibility of interest and show that by

hedging firms can increase debt capacity and therefore firm value. Stulz (1996) argues that hedging is

used to reduce the probability of "left-tail" outcomes, thereby increasing debt capacity and interest


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write-offs. We investigate the hedging and debt policy choices jointly using simultaneous equations

regressions. We find that leverage exerts a positive influence on the use of both interest rate (IR) and

currency (FX) derivatives. Importantly, we also find that the debt-hedging relation runs the other way:

hedging leads to greater debt capacity. For the average firm, hedging with interest rate (currency)derivatives increases the debt ratio by 2.85% (4.52%), with the capitalized value of the incremental tax

shields resulting from this increased debt equaling 1.4% (1.4%) of firm value. (Our estimates indicate

that tax incentives to increase debt capacity are approximately 10 times larger than convexity

incentives.) To the best of our knowledge, this is the first evidence that hedging increases debt capacity

and firm value, and moreover, the only explicit empirical estimate of value added due to derivatives

hedging associated with any of the hypothesized explanations of why firms hedge.

The third contribution of the paper involves contrasting, across the IR and FX samples, other

explanations of how costly volatility can lead to corporate hedging. We find evidence that firms use

derivatives in a manner consistent with value maximization. In addition to pursuing tax savings through

greater debt, we find that large firms subject to underinvestment problems and high expected distress

costs use IR derivatives to hedge. We also find strong relations between the extent of FX hedging and

both size and leverage. The FX results are weakly consistent with theories that suggest hedging reduces

underinvestment costs. In both samples, hedging increases with institutional ownership. Overall, in both

samples, we find that firms hedge in response to tax incentives to increase debt capacity,

underinvestment costs, financial distress costs, and firm size. Finding these results in both the IR and FX

samples indicates that these basic factors that drive corporate hedging can emanate from different

sources of risk, and also that firms hedge with more than one type of derivative security to reduce the

effects of costly volatility.

The remainder of the paper is organized as follows. Section I reviews risk management theories

and the related empirical evidence about why firms hedge, and defines the explanatory variables.

Section II describes how we construct the IR and FX samples and the hedging variables. Section III

performs univariate analysis of the differences between derivative users and non-users. Section IV

provides multivariate tests of the likelihood and extent of derivatives hedging, and also examines the

relation between derivatives hedging and tax incentives in greater detail. We conclude in Section V.


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I. Value-maximizing rationales for hedging

An extension of theModigliani and Miller (1958, 1961) propositions on capital structure and

dividend policy suggests that, in the absence of market imperfections, hedging does not add to firm

value. If capital markets are perfect, shareholders possess the requisite information about a firmsidiosyncratic risk exposures, and the necessary tools, to create their desired risk profiles; therefore, in

this environment, there is no reason for a firm to hedge. For corporate hedging to increase firm value,

market imperfections must exist. If a firm is exposed to economic risks in an imperfect environment,

these exposures, if unhedged, can impose costs on the corporation. Hedging helps reduce these costs.

For example, market imperfections can create an environment in which exposure to volatile interest

rates is costly.

Schrand (1998) points out that hedging research can be grouped into at least two broad

categories: 1) papers that investigate which market imperfections make volatility costly and therefore

lead to corporate hedging, and 2) papers that investigate why one method of reducing volatility is

cheaper than another. With respect to 1), financial economists have identified at least four market

imperfections that make volatility costly: the corporate income tax, costs of financial distress, managerial

risk aversion, and information asymmetry. (In the remainder of this section, we describe how these

imperfections provide an incentive to hedge.) Notably, the theories that model how these imperfections

impose costs on the corporation generally do not specify the source of the volatility, nor which type of

derivative instrument should be used to hedge. As examples of 2), Fenn, Post, and Sharpe (1996) and

Visvanathan (1998) study which factors and imperfections make it cheaper to use interest rate swaps in

conjunction with short-term debt instead of issuing long-term debt.

Our primary purpose is to determine which factors make cash flow or income volatility costly

and so our paper belongs in category 1. (See Table I for a review of empirical papers in this category.)

Given that the theories do not specify which type of derivative should be used to reduce volatility, we

test whether the factors outlined below affect the incentive to hedge using either interest rate or currency

derivatives. The remainder of this section describes imperfections and incentives that can affect

corporate hedging.


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A. Tax function convexity and the incentive to hedge

Smith and Stulz (1985) demonstrate that volatility is costly for firms with convex effective tax

functions. Fig. 1 provides a simple illustration of their argument. A firm that realizes taxable income

levels of Aor B, each with a probability of 1/2, has an expected tax liability of E[T]. If the firmeliminates taxable income uncertainty (perhaps through hedging), it earns income level Cwith certainty,

and lowers its expected tax liability to E[T|H]. Reducing the volatility of taxable income reduces the

firms expected tax liability and increases market value. The argument also works in reverse: If a firm

has a concave tax function, hedging to reduce the volatility of taxable income increases expected tax

liabilities and decreases firm value.

If the tax function were linear over the entire income range, there would not be a convexity-

based tax incentive to hedge. Ignoring progressivity, this would be the case if loss firms received an

immediate payment from the government equal to the product of the corporate tax rate and the dollar

amount of the loss. Instead of receiving such a payment, firms can carry losses backward and forward

to offset taxable income in other years. If firms could immediately sell tax preference items (such as net

operating loss carryforwards) at full price, or if the firms were certain they would eventually use their tax

preference items and the discount rate were zero, there would be no tax incentive to hedge. Therefore,

it is the limitations on the ability to sell or immediately use tax preference items that lead to convex tax

functions and (convexity-based) tax incentives to hedge.

Graham and Smith (1999) simulate important features of the corporate tax code to explicitly

measure tax function convexity for a large sample of U.S. firms. They find that roughly one-half of

corporations face a convex tax schedule. For these firms, the average tax savings achievable by

reducing income volatility by 5% are approximately $120,000. However, the savings are material for

only about 10% of Compustat firms. Graham and Smith also find that the tax function is effectively

concave for 25% of their sample, although tax incentives to increase volatility are typically small.

Most empirical derivatives papers measure tax function convexity with a variable based on

existing net operating loss (NOL) carryforwards (see Table I). Such variables imply that firms with

existingNOLs have convex tax functions, although the Smith and Stulz (1985) argument is about losses

that firms expect to experience in the future. In fact, Graham and Smith (1999) document that existing

NOLs provide a tax disincentiveto hedge for firms with small expected losses (if a firm expects to lose


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money, hedging reduces "right tail" outcomes and the chance that the firm will use its existing NOLs) but

provide an incentive to hedge for firms that expect to be profitable. Thus, variables based on existing

NOLs are too simple to capture incentives that result from the shape of the tax function, and may even

work backwards for expected loss firms. In addition, existing NOLs may measure financial distress orsome other firm characteristic, rather than a tax incentive to hedge.

Rather than using a NOL variable, we use the Graham and Smith approach to explicitly

measure tax function convexity. This technique quantifies the convexity-based benefits of hedging by

determining the tax savings that result from reducing volatility. We first calculate the expected tax liability

for a "full volatility" case, and then recalculate the expected tax liability with volatility reduced by 5%; the

difference between these two numbers represents the convexity-based tax benefit of hedging. We

choose a 5% volatility reduction to be consistent with the risk reduction observed by Guay (1999) when

firms introduce hedging programs. Our qualitative results do not change if we use a 1% or 3% volatility

reduction.

For the full-volatility case, we calculate the expected tax liability from t-3 (to account for

carrybacks) to t+18 (to account for carryforwards). To determine tax liabilities over this range, we

forecast earnings through period t+18. The forecasts assume that taxable earnings follow a random

walk with drift and that innovations are normally distributed, with mean and variance calculated from

firm-specific historical data through period t.3 The tax liability calculation incorporates carrybacks,

carryforwards, the Alternative Minimum Tax, and the progressive corporate tax schedule. We repeat

the experiment 49 additional times for each firm-year in the sample, starting each time with a new

forecast. We average across the 50 different scenarios to determine the expected tax liability. By

considering 50 different paths, we capture the interaction between earnings uncertainty and the

aforementioned features of the tax code.

Next, we recalculate the expected tax liability after modifying each of the 50 paths by reducing

volatility by 5% in year t+1. We measure tax function convexity as the expected tax savings resulting

3Our reported analysis bases volatility on sales revenue. Although Graham and Smith (1999) show that convexitydoes not differ substantially for different measures of earnings, previous readers of our paper suggested that taxableearnings might be affected by a firm's past hedging program, while sales revenue should not be directly affected.Therefore, we base our analysis on sales revenue volatility. Our qualitative results are unchanged if we base volatilityon taxable earnings.


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from the 5% volatility reduction, scaled by sales revenue during year t. Positive values for tax convexity

indicate that hedging to decrease volatility reduces expected tax liabilities, implying a convex tax

function. Negative values imply tax function concavity. Our variable is a more precise measure of tax

function convexity than has been available to previous empirical derivatives studies.There are countervailing influences that work against detecting corporate hedging in response to

tax function convexity. Graham and Smith (1999) show that the firms that are most likely to have

convex functions are small, have expected income near zero, and alternate between profits and losses.

These firms may find the fixed costs of setting up a hedging program prohibitive, and consequently not

hedge.4 In addition, the option value of equity may provide the shareholders of these firms with

incentives to increase volatility, opposite the incentive provided by the tax code.

B. The relation between hedging and debt ratios

B.1. Debt ratios measure financial distress

If financial distress is costly (whether from direct bankruptcy costs, such as legal fees, or indirect

costs, such as business disruption), and volatility increases the chance of encountering distress, then

volatility can reduce firm value. Smith and Stulz (1985) argue that hedging can increase firm value by

reducing volatility and the probability of distress. (As we discuss in more detail below, Froot,

Scharfstein, and Stein (1993) extend the Smith and Stulz argument by endogenizing distress costs and

show that hedging can reduce the underinvestment problem resulting from the deadweight costs

associated with external financing.) Stulz (1996) emphasizes the role of hedging in preventing left-tail

outcomes that would cause distress and force firms to bypass investment opportunities or otherwise fail

to exploit their competitive advantages.

Dolde (1995), Berkman and Bradbury (1996), Haushalter (2000), Gay and Nam (1999), and

Howton and Perfect (1999) use the debt ratio to measure expected costs of distress and find that higher

debt ratios lead to greater hedging (see Table I). Most studies interpret this relation as evidence that

greater expected financial distress costs cause greater hedging. This interpretation assumes that firms

with higher debt ratios face higher probabilities of encountering financial distress. We include the debt

4Bodnar et al. (1996) find the costs of establishing and maintaining a derivatives program exceed the expectedbenefits as the second most common explanation of why some firms do not use derivatives.


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ratio in our analysis, defined as total debt divided by the book value of assets.

We also directly measure expected distress costs with a variable that accounts for both the

probability of distress and the associated cost if distress occurs. To calculate this variable, we multiply

the debt ratio by the equity market-to-book ratio. The probability of financial distress increases with thedebt-asset ratio, and the cost of distress (if encountered) increases with the market-book ratio. We

expect to observe a positive relation between this variable and derivatives use if firms hedge in response

to costs of financial distress. Gczy et al. (1997) use the product of the debt ratio and the market-book

ratio in their analysis, although they interpret the variable as a proxy for underinvestment costs. Gczy et

al. find a positive relation between the decision to use foreign currency derivatives and the product of

the debt and market-book ratios.

We examine two other variables related to costs of distress. Firm profitability might be inversely

related to hedging if less profitable firms have a higher probability of encountering distress. Conversely,

the option value of equity might encourage unprofitable firms to hedge less than their non-distressed

counterparts. We measure profitability as the pre-tax return on assets (ROA). We also denote firms that

might be experiencing current (or recent) financial distress with NOL carryforwards scaled by the book

value of assets.5

B.2. Hedging leads to increased debt capacity

When we examine explanatory variables based on the debt ratio, we follow other studies and

interpret the debt ratio as a measure of the expected costs of distress, which is a causal determinant of

hedging policy. However, Stulz (1996), Ross (1997), and Leland (1998) suggest an alternative reason

that debt ratios and hedging practices may be positively correlated: hedging, by reducing the volatility of

income and/or reducing the probability of financial distress, increases debt capacity. If firms add

leverage in response to greater debt capacity, the associated increase in interest deductions reduces tax

liabilities and increases firm value. Thus, the ability to increase debt capacity provides a tax incentive to

hedge.

5We also examine the credit rating of senior debt as a measure of the probability of distress. Including credit rating inour empirical specification reduces the sample size, and yet the variable is not statistically significant, so we do notinclude credit rating in our reported specifications. We also do not report a specification that includes a dummyvariable indicating if a firm has a credit rating because the variable is not statistically significant.


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Leland (1998) implies that hedging increases value through two different channels related to the

debt ratio. The principal gains from hedging come from "the fact that lower average volatility allows

higher leverage with consequently greater tax benefits." A secondary hedging gain comes from "lower

expected default rates" and distress costs, resulting from unused debt capacity. That is, the majority ofthe gain comes from increased leverage/tax deductions but a portion of the increased debt capacity goes

unused, resulting in lower distress costs and higher value. Ross (1997) also argues that the reduction in

expected distress costs is less important than the tax shield available from increased leverage.

In sum, theory suggests that the hedging/leverage causality can go both ways: hedging can lead

to increased debt capacity, but higher leverage (to the extent that it increases the probability of distress)

can increase the incentive to hedge. Therefore, in part of our analysis, we model the hedging/capital

structure decision as a simultaneous system, which is appropriate if these two corporate policies are

jointly determined. (Haushalter (2000) and others argue that this is the case.) In the regressions with

hedging as dependent variable and debt on the right hand side, we interpret a positive coefficient as

evidence that leverage leads to increased hedging due to higher expected costs of distress. In the

regressions with debt as dependent variable and derivatives use on the right hand side, we interpret a

positive coefficient as evidence that hedging leads to increased debt capacity and tax deductions.

C. Underinvestment costs and the incentive to hedge

Myers (1977) and Myers and Majluf (1984) describe circumstances in which a firm might

reject positive net present value (NPV) projects (i.e., underinvest). Bessembinder (1991) and Froot et

al. (1993) propose hedging as a solution to the underinvestment problem. 6

Bessembinder (1991) assumes that a firm simultaneously determines a hedging policy and debt

level before selecting its optimal level of investment. He shows that in the absence of hedging, the firm

may underinvest because too much of the incremental value from investment accrues to debtholders.

However, if the firm can credibly commit to a hedging policy at the time of the debt decision, the

underinvestment problem is attenuated because the value of debt becomes less sensitive to incremental

investment. Shareholders are beneficiaries of the improved contracting terms with debtholders (or other

6Mayers and Smith (1987) model the purchase of insurance as a means of reducing underinvestment.


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fixed claimants).

In Froot et al. (1993) firms can use internal and/or external funds to finance investment projects.

The authors assume that financing costs increase with the level of external financing, and that the

marginal benefit of investment declines with the level of investment. Volatility is costly in this environmentbecause if internal funds are relatively scarce in some states of nature, positive NPV projects may be

rejected (if the marginal cost of external funds exceeds the marginal benefit to shareholders in these

states). Hedging effectively allows a firm to shift internal funds into states where they would otherwise be

scarce. If internal funds are cheaper than external funds, hedging therefore permits the company to

finance more valuable investment projects and increase firm value.7

Theory implies that underinvestment is most severe for firms with valuable investment

opportunities, which we quantify with the market-book ratio. Several other empirical studies examine

the relation between market-book and hedging and find no relation (see Table I). As mentioned in

Section I.B.1, we include the product of the market-book ratio and the debt ratio in our specification,

which Gczy et al. (1997) define as a measure of underinvestment costs. We also use R&D spending

scaled by the book value of assets to measure growth options. Nance et al. (1993), Dolde (1995),

Gczy et al. (1997), Allayannis and Ofek (1998), and Gay and Nam (1999) all find that hedging

increases with R&D spending. Finally, we include cash capital expenditures on property, plant, and

equipment, scaled by the book value of assets to control for the relation between hedging and current

investment spending.

D. Managerial risk aversion and the incentive to hedge

Risk aversion among managers and/or shareholders can provide an incentive to hedge (Stulz,

1984; and Smith and Stulz, 1985). If managers have concave utility functions, and the variability of their

compensation is related to the volatility of corporate income or cash flows, then corporate volatility can

be costly. If managers can not effectively hedge corporate volatility in their personal accounts, or if it is

7Tufano (1998) argues that managers might hedge to avoid scrutiny of negative NPV pet projects by externalcapital markets. Providers of external capital would not fund these pet projects. However if managers use hedging toensure the availability of internal capital, then the projects might be funded. Tufano thus suggests that hedging canlead to overinvestment. However, Tufano notes that if "pet project" agency costs are relatively low, thenunderinvestment concerns will dominate.


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cheaper for the firm to hedge than it is for managers, then corporate hedging can improve managerial

welfare. Therefore, it can be value maximizing for a firm to hedge for the benefit of managers if doing so

reduces the risk premium managers demand, and therefore reduces their required compensation. A

similar argument can justify corporate hedging of the risk faced by ill-diversified corporate insiders withlarge shareholdings.

We use three variables to test whether manager/shareholder risk aversion affects corporate

hedging: 1) the number of executive stock options held by the CEO, 2) the natural logarithm of CEO

stock value, and 3) the presence of multiple classes of common stock. Stock options introduce a

convexity between managerial wealth and stock value, which offsets the concavity in the manager's

utility function. This in turn makes the manager behave in a less risk averse manner, which reduces the

need for corporate hedging. Therefore, hedging should be negatively related to CEO option holdings.

In contrast, the value of common stock increases linearly with firm value. Thus, a managers

holdings of common stock do not counteract the concavity of his/her utility function. A manager with

large stockholdings has incentive to engage in risk averse behavior. Therefore, we predict that hedging

activity is positively related to the value of CEO stockholdings. Finally, firms with multiple classes of

shares often have a controlling group with superior voting rights. If management or ill-diversified

shareholders are represented in the controlling group, managerial or shareholder risk aversion is more

likely to affect corporate actions. We include a dummy variable that equals one if a firm has multiple

classes of shares and hypothesize a positive relation between this variable and corporate hedging.

Tufano (1996) and Schrand and Unal (1998) find evidence that hedging increases with

managerial shareholdings and decreases with managerial option ownership, consistent with the

hypotheses outlined above. Other studies (e.g., Gczy et al., 1997; and Haushalter, 2000) find no

evidence that managerial risk aversion or shareholdings affect corporate hedging. We use the variables

defined above to maintain consistency with these prior studies. However, such simple variables may not

measure precisely the incentive effects of stock and option holdings. Therefore, we also calculate the

more elaborate delta and vega variables defined in Core and Guay (1999). These variables measure

the change in a managers wealth as stock price and volatility change, respectively, given his or her

stock and option portfolios. We find (in unreported analysis) that the Core and Guay variables are not

significantly related to corporate hedging in our samples, so, to permit comparison of our analysis to


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previous work, the results we report below are based on the three simpler variables.

E. Other incentives to hedge

DeMarzo and Duffie (1991) and Breeden and Viswanathan (1998) argue that there areinformational asymmetries between managers and shareholders. DeMarzo and Duffie conclude that

corporations should sometimes hedge based on private information that can not be costlessly conveyed

to shareholders. Breeden and Viswanathan argue that high-quality managers have an incentive to hedge

away uncertainty about managerial performance so that the market can draw more precise inference

about their ability. To measure the degree of informational asymmetry, we use the percentage of each

firms shares that are owned by institutions as of September 1994, based on 13-f filings reported by

CDA Spectrum. If firms owned primarily by institutions face less informational asymmetry of the type

assumed by DeMarzo and Duffie (1991) and Breeden and Viswanathan (1998), their theories imply

that high-institution-ownership firms should hedge less. Gczy et al. (1997) find the opposite, namely

that firms with high institutional ownership are more likely to hedge with currency derivatives.

Most prior studies find that the likelihood of using derivatives increases with firm size. A positive

size effect is consistent with firms not hedging with derivatives unless the benefits are larger than the fixed

costs of establishing a hedging program. In contrast, Haushalter (2000) finds a negative relation between

size and hedging, given that the firm hedges. Conditional on hedging, a negative relation is consistent

with the extent of hedging increasing with informational asymmetry and financial distress costs. We

measure firm size as the natural logarithm of total assets.

Nance et al. (1993) note that "hedging substitutes" can reduce the need for hedging with

derivatives. For example, dividend restrictions might allow a firm to retain sufficient liquidity to make

hedging unnecessary. Likewise, holding liquid assets may reduce the need to hedge. Dividend yields

(Nance et al., 1993) and liquidity ratios (Tufano, 1996; and Gczy et al., 1997) have both been shown

to be negatively related to derivatives usage. We also examine the effect of dividend yield and liquidity

on derivatives hedging.

Gczy et al. (1997) find that the likelihood of using currency derivatives is positively affected by

the use of other types of derivatives, suggesting that there are scale economies to running a derivatives

program. Therefore, we include a dummy variable indicating interest rate (currency) derivatives usage in


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the tests of currency (interest rate) hedging. In unreported multivariate analysis, we find that the

existence of interest rate derivatives positively affects currency hedging but not vice versa. Therefore,

our reported regressions include an interest rate dummy variable in tests of currency hedging but not a

currency derivatives dummy in tests of interest rate hedging.As mentioned at the beginning of Section I, some papers study the factors that make using

interest rate swaps in conjunction with short term debt preferable to using long term debt. While our

focus is on what makes volatility costly, we control for this other explanation for the use of swaps. We

include the sum of short-term and floating-rate debt (as a percentage of total debt) in our regressions to

control for the effect of such debt on interest rate derivatives use. (Analogously, for the foreign currency

sample, we control for the importance of foreign sales relative to total sales.) To control for another

explanation of why firms use swaps and short term debt, we examine the level of credit ratings to see if

low-quality firms use IR derivatives to avoid the "credit quality spread" associated with issuing long-term

debt (Bicksler and Chen, 1993). Finally, we also examine changes in future credit ratings, to see if firms

with favorable private information use short-term debt and IR derivatives until their credit rating

improves (Titman, 1992).8 Neither of these last two hypotheses is supported by our interest rate

derivatives tests, and yet including the credit rating reduces the sample size, so we do not include credit

ratings in our reported results.

II. Derivatives data and hedging variables

A. Sample formation

We analyze corporate derivative holdings as of calendar-year-end 1994 or fiscal 1995. This

time frame is chosen because, prior to December 1994, financial statement disclosures were generally

8Simkins (1997) tests Titmans (1992) hypothesis that firms use interest rate swaps because of asymmetric

information about their credit quality. Titman's theory implies that firms with credit ratings just below investmentgrade, that know their rating will be upgraded soon, borrow short-term with floating rates. They then enter intointerest rate swaps that effectively fix the interest rates on their debt obligations until the good news about theircredit quality is revealed. Our interest rate sample is not designed to test Titman's hypothesis; therefore, it is notsurprising that we do not find a relation between credit rating changes and IR derivatives hedging. Simkins' (1997)sample is designed to test this hypothesis, and she finds evidence consistent with Titman's (1992) predictions.


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inadequate to analyze the extentof derivatives hedging.9 In 1994, the Financial Accounting Standards

Board (FASB) issued SFAS 119 in an attempt to improve derivative disclosures by U.S. corporations.

SFAS 119 mandates that firms disclose information on notional values of derivative contracts,

including the direction of the position, across several categories.

10

SFAS 119 became effective for fiscalyears ending after December 15, 1994 for firms with assets greater than $150 million.11 Firms are

required to specify if derivatives are held for trading purposes or, if for non-trading reasons, the purpose

of the holdings. We examine only derivatives held for non-trading purposes.

We obtain the information about each firms fiscal year-end derivatives ownership from 10-K

forms filed electronically in the SECs Electronic Data Gathering and Retrieval (EDGAR) database

during March-December 1995. (An example of one firms derivatives disclosure is shown in Appendix

A.) This population consists of 3,232 firm-filings. We search the footnotes and Managements

Discussion and Analysis (MD&A) of each 10-K filing for word strings such as hedg, swap, and

derivative. If a reference is made to any of the search terms, we read the surrounding text to confirm

that it refers to derivative holdings. Given the time-consuming nature of data collection from these filings,

we examine a random sample of 855 firms selected from the initial list of filers. Out of these 855 firms,

we retain observations that meet the following criteria:

(1) fiscal year ends December 15, 1994 through October 31, 1995,

(2) complete set of annual financial statements including footnotes is available,

(3) the firm is not a subsidiary of another firm in the sample,

(4) the firm's income is taxable at the corporate level,

(5) the firm is listed on the Compustat annual database, and

(6) the firm discloses the notional value of its derivative holdings, if any.

Out of the 531 observations that meet these six criteria, we divide the data into two non-mutually

9Gczy et al. (1997) note this limitation in their analysis of corporate foreign currency derivatives during 1991. They

consider notional values of derivatives from financial statements to be unreliable due to aggregation across different

types of derivatives (as was commonly done prior to December, 1994).

10Smithson et al. (1995, p. 147) define notional value (or notional principal) as principal that is not paid or receivedat contract maturity but is instead used only to calculate the cash flows paid and received. The notional value of aderivatives contract is typically similar, if not equal, to that of the underlying asset or liability being hedged.

11SFAS 105 and 107 require firms to declare if they use derivatives, even if their assets are less than $150 million.


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exclusive groups (as described in the next section): firms that face ex ante interest rate risk (404 firms),

and firms that face ex ante currency risk (242 firms). Seventy-four of the firms in the FX sample are not

included in the IR sample, and 168 firms are in both samples.

Thirty-five percent of the firms in the IR sample use interest rate derivatives. Over 43% of FXsample firms report that they use currency derivatives (see Table II). Both samples contain observations

from all major industrial classifications. Manufacturing firms (SIC codes 22-39) are common in both

samples, 40% and 62% of the IR and FX firms, respectively. Not surprisingly, banking and investment

firms are the most frequent users of IR derivatives. Transportation, construction, and mining firms also

use IR derivatives more often than average. Other than the large number of manufacturing firms, the FX

sample is represented by a relatively small numbers of firms in other industries.

B. Definition of ex ante risk exposure

By focusing on firms that face ex ante risk, we can interpret the absence of derivatives as a

choice not to use derivatives, rather than possibly indicating a lack of exposure to hedgeable risks. So

that we can study the use of both interest rate and currency derivatives, we define two separate

samples: 1) firms with ex ante foreign exchange risk exposure; and 2) firms with ex ante interest rate risk

exposure. Similar to previous research, we define firms to have ex ante currency exposure if they

disclose foreign assets, sales, or income in the Compustat Geographic segment file, or disclose positive

values of foreign currency adjustment, exchange rate effect, foreign income taxes, or deferred foreign

taxes in the annual Compustat files.

We define ex ante interest rate exposure in two separate ways. We start by noting that interest

rate derivatives are often used to hedge the interest cash flows from debt liabilities. Therefore, financial

leverage is a possible source of interest rate risk. In the first definition of interest rate risk, we classify

firms as facing interest rate risk if their debt-assets ratio is greater than 10%.12While this cutoff point is

arbitrary, only ten of the 127 firms with debt-assets ratios less than 10% use IR derivatives. Our results

are qualitatively similar if we define IR exposure using a cut-off of 0%, 5%, or 15%.

The alternative definition of ex ante interest rate risk is based in part on the sensitivity of

12Fenn et al. (1996) find that debt holdings significantly affect the use of IR derivatives, which we interpret asevidence that debt holdings are a reasonable measure of IR exposure.


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operating income to interest rates. Specifically, we regress changes in operating income on changes in

the six-month LIBOR rate. (Note that operating income does not usually contain income resulting from

interest rate derivatives, and therefore should not be directly affected by the endogenous decision to

hedge with interest rate derivatives.) Based on the sign of the regression coefficient, we classify firms ashaving positive, negative, or zero operating exposure to interest rates. Zero exposure occurs when the

regression coefficient is not significant at the 10% level. For this definition, a firm faces ex ante interest

rate risk if it meets any of the following criteria:

1) zero operating exposure to interest rate changes, and positive amounts of floating debt (i.e.,

short-term and/or floating-rate debt),

2) negative operating exposure to interest rate changes, or

3) positive operating exposure to interest rate changes, and less than 50% of debt is floating.

(If there is sufficient floating debt, it can offset the positive operating exposure to interest

rates, so a firm would not face ex ante interest rate risk.)

Our qualitative results are similar regardless of how we define ex ante interest rate risk exposure. The

results we present below are based on the first definition of interest rate risk.

C. Measuring derivatives hedging

We gather notional values for each of three major derivatives categories: interest rate, currency,

and commodity.13We classify derivative positions as long or short. A long interest rate position is

one that benefits from rising interest rates, such as an interest rate swap that pays a fixed rate and

receives a floating rate. Conversely, a short interest rate position benefits from declining interest rates. A

long currency derivative position benefits from price increases of a currency other than the U.S. dollar,

while a short position benefits from decreasing foreign currency prices. If a position is not clearly long

or short, we classify it as unsure.

We measure derivative holdings several ways. One measure is the total notional value of

derivative contracts held by each firm for non-trading purposes. Total notional values have recently been

13We include the commodity holdings for informational purposes but they should be interpreted cautiously. Manycommodity instruments are not considered derivative financial instruments under SFAS 119 because of thepossibility of physical delivery (such as with commodity futures contracts). Thus, the use of commodity derivativesis likely understated in our data. We do not investigate commodities in detail.


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used in Berkman and Bradbury (1996), Allayannis and Ofek (1998), and Gay and Nam (1999). We

calculate total notional values for IR holdings and, separately, total notional values of FX holdings. We

present summary information about total notional values (in Tables III and V) but do not use this

variable in our regression analysis (except in one robustness check).While total notional value effectively gauges derivatives ownership, it may not accurately

estimate derivatives hedging if a firm holds offsetting contracts. The distinction between ownership and

hedging is important when testing theories of risk management. Therefore, for our second derivatives

variable, we calculate the absolute value of the net derivatives position in each category. The net

position is the difference between each firms long and short positions in interest rate and, separately,

individual currency derivatives (and thirdly, commodities).14 For interest rate hedging, we add basis

swaps (interest rate swaps that are essentially an exchange of floating rate indices) to the absolute

difference between long and short positions. The net derivatives variable is the dependent variable in our

primary regression analyses.15

Finally, to contrast our analysis with studies that examine the yes/no hedging decision, we

construct a binary variable. Firms that hold derivatives for non-trading purposes are assigned a value of

one for the binary variable, and all other firms are assigned a zero.

Three important issues affect how precisely our variables measure corporate hedging. First,

derivative holdings may measure speculative activity, not hedging. Taken literally, SFAS 119 requires

firms to explicitly state if they speculate with derivatives. Many firms provide statements such as

derivatives are used for risk management purposes only; none of our sample firms state that they

speculate. Further, our variables are defined using only those derivatives disclosed as being held for

non-trading purposes. Consequently, we classify firms that use derivatives for non-trading purposes as

14The total notional value used in previous derivatives studies might classify $100 million long and $50 million shortas $150 million. In contrast, we net the two figures to determine a net position of $50 million. Wong (1997) finds thatnet notional values are related to foreign currency exposure in 1995.

15For example, consider a firm with notional values of $100 million long interest rate, $50 million short interest rate, $20

million long British pounds, and $75 million short Japanese yen. This firms net position in IR (FX) derivatives is $50

($95) million. We use absolute values because hedging to maximize firm value may require a firm to go long in one

derivatives category but short in another.


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"hedgers" and those that do not use derivatives as "non-users."16 Second, firms can hedge with

operational strategies, such as building a manufacturing facility in a locale that is the source of foreign

currency risk, or issuing convertible debt. Our study focuses on hedging with derivatives, rather than on

operational hedging strategies.Finally, as noted by Smith (1995), different firms can hold the same notional value of derivatives

and still have very different hedging practices. For example, two firms may hold $10 million in

derivatives, but one has one-year swaps and the other seven-year swaps. The firm with the one-year

swap might appear to hedge less than its counterpart with the seven-year swap. However, if the first

firm is hedging a liability that matures in one year while the other firm is hedging a liability that matures in

seven years, then both firms are hedging appropriately. Current financial reporting guidelines do not

require firms to disclose the underlying asset and/or liability that is being hedged with a derivative

contract, so we are unable to determine whether firms employ a maturity-matching hedging policy. To

the extent that notional values do not fully reflect corporate hedging practices, our data are noisy, which

works against our ability to document hedging incentives.

Table III presents aggregate measures of total and net derivative positions for the IR and FX

samples (Panels A and B, respectively). The mean and median notional values of all derivative positions

are $2.8 billion and $210 million in the IR sample, and $2.75 billion and $171 million in the FX sample.

The net derivative positions are significantly smaller: both samples have mean and median values of

approximately $700 million and $125 million, respectively.

Table III shows that 180 out of 404 firms in the IR sample disclose some type of derivative

holdings, and 142 hold IR derivatives. We can calculate net IR derivative positions for 131 firms. For

the 142 IR derivative users in this sample, the mean (median) notional values of IR derivatives is $3.0

($0.213) billion, or 16.9% (8.2%) of total assets. The mean (median) net IR position is $728 ($110)

million, or 9.5% (5.5%) of total assets.

One hundred thirty-eight out of the 242 firms in the FX sample use some type of derivative. Of

16Several studies lead us to believe that most corporate derivatives are held as hedging instruments. Guay (1999)finds that initiation of corporate derivatives use is associated with declines in various measurements of firm risk.Tufano (1996) uses extremely accurate data to describe the derivative holdings of U.S. gold mining firms and finds noevidence of speculation. Hentschel and Kothari (1998) find no evidence that derivatives use increases firm risk.However, Bodnar et al. (1996) find that corporate management teams sometimes allow their "market view" to influencehedging decisions, implying that there may be an element of speculation in samples of corporate derivative holdings.


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these 138 firms, 105 use currency derivatives, with mean (median) holdings of $684 ($80) million. From

this set of currency derivative holders, we can calculate net currency derivatives for 64 firms.17 The

mean (median) net currency position among these firms is $195 ($67) million.

III. Univariate analysis of hedgers vs. non-users

Panel A of Table IV summarizes the characteristics of the firms in the IR and FX samples.

Comparisons between derivative hedgers and non-users are presented in Panel B.

Hedgers are much larger than non-users, which is consistent with the fixed costs of derivatives

hedging acting as a barrier to small firms (see Panel B). Interest rate hedgers are more likely to use

currency derivatives, and vice versa, which is consistent with there being scale economies to corporate

hedging. Institutional investors are more important investors for hedgers than non-users, contrary to

information asymmetry rationales. CEOs of derivative-using firms hold more options and wealth in their

firms stocks than do CEOs of non-users. Hedgers have significantly lower book-market ratios (based

on the Wilcoxon rank-sum test). This suggests that hedgers have greater investment opportunities, which

is consistent with the Froot et al. (1993) underinvestment argument and the analysis of Allayannis and

Weston (1998). Dividend yields are higher for derivative hedgers than for non-users, consistent with the

Nance et al. (1993) argument that dividend curtailment is a substitute for hedging. Currency hedging is

negatively related to liquidity, which is consistent with liquidity serving as a hedging substitute. In the FX

sample, the likelihood of hedging increases with the percent of sales from foreign sources.

We find weak evidence of financial distress motives to hedge, as suggested by results for the

interaction of debt ratio with the market-book ratio. In both samples, derivative hedgers have higher

values for this variable, with the differences significant using means in the IR sample and a Wilcoxon

rank-sum test in the FX sample. The results for the tax convexity variable and debt ratio are not

consistent with tax-related hedging rationales. The differences in the R&D ratio indicate that firms with

greater growth options are more likely to hedge with FX derivatives.

Table V summarizes the correlations between the independent variables and the three measures

17A relatively large number of currency positions are "unsure" because the disclosures for currency derivativesoften lack the detail of the IR disclosures. We exclude from regression analysis all firms that have positive totalderivatives but are missing a net derivatives position.


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of scaled IR and FX derivative holdings. Firm size and institutional ownership are positively related to all

three derivatives variables in both the IR and FX categories. CEO stock value and option holdings are

also positively related to the hedging variables. The financial distress variable (interaction of debt and

market-book) is positively related to the IR variables and net currency derivatives. The debt ratio ispositively correlated with the two continuous measures of IR derivative holdings, as well as with net

currency derivatives. FX derivative use increases with foreign sales. The correlation coefficients are not

consistent with the hypothesis that firms hedge in response to tax function convexity. In unreported

analysis, we find that total and net derivatives positions have a correlation of 0.49 (0.69) in the IR (FX)

sample.

IV. Multivariate analysis of corporate hedging

In this section, we use multivariate analyses to test the joint influence of the explanatory variables

on corporate derivatives hedging. We start by examining the extent of hedging using a Tobit analysis.

These results are then contrasted with those from a combination of probit analysis and truncated

regression as suggested by Cragg (1971). The section concludes with an in-depth analysis of tax

motives to hedge.

A. The extent and likelihood of derivatives hedging

A.1. IR derivatives hedging

Tobit regression: We use a Tobit specification to analyze the factors that affect the extent of

derivatives ownership. This econometric model is appropriate when the dependent variable is left-

censored at zero. The Tobit model takes the form

Yi*= 'Xi+ ui where ui~ NID(0,

2)

Yi= Yi*if Yi

*> 0

Yi= 0 if Yi* 0 (1)

The dependent variable, Yi*, is unobservable if its true value is negative.18 The vector of independent

18Although the dependent variable never takes a value below zero, "negative hedging" can occur if firms use

derivatives to speculate. If this occurs, the parameter estimates may be biased towards zero, in which case the Tobit

specification lacks power to reject the null hypothesis of no relation between the dependent and explanatory


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variables,Xi, includes the explanatory variables discussed previously and industry indicator variables for

the classifications described in Table II. We conduct unreported Tobit regressions on the full model

specification. However, for brevity, the reported results are based on specifications that exclude the

insignificant industry dummy variables, as well some other insignificant explanatory variables. Our majorconclusions are not affected by excluding these variables.

Model IR 1 of Table VI, Panel A presents slope estimates from a Tobit regression using net IR

derivatives (scaled by the book value of assets) as dependent variable.19 The debt ratio and the

interaction of debt with market-book are both positively related to IR hedging. These findings are

consistent with firms hedging in response to large expected costs of distress. Firms with low ROA

hedge more, which is also consistent with the financial distress motive to hedge. In contrast, the negative

coefficient on the NOL carryforward variable indicates that firms reduce hedging if they have recently

accumulated losses. Although inconsistent with hedging in response to past distress, this relation may

indicate that the option value of equity discourages severely distressed firms from hedging. Our results

are more supportive of a financial distress motive to hedge than those found in most empirical studies,

perhaps because we examine a broad sample of firms. Haushalter (2000), Gay and Nam (1999), and

Howton and Perfect (1999) find that leverage ratios, but not other measures of distress, are positively

related to hedging activity. Tufano (1996), Gczy et al. (1997), and Allayannis and Ofek (1998) find

weak or no evidence that distress costs affect hedging.

We find a positive relation between R&D expenses and hedging. This is consistent with firms

hedging to minimize underinvestment problems when they have growth options (Bessembinder, 1991;

Froot et al., 1993). However, our analysis indicates that there is no relation between the market/book

ratio and hedging. Our results are consistent with other studies that find evidence consistent with the

underinvestment hypothesis based on R&D expenses, but no evidence based on market/book (see

variables. Given the requirements of SFAS 119, we believe that misidentification of derivatives positions in this

manner is at most a minor problem (see discussion in Section II.C).

19The parameter estimates from a Tobit regression represent the marginal effect of each regressor on the unobserved

dependent variable, Yi*. We are more interested in the marginal effect on the observed dependent variable, Yi. The

marginal effect of a change in the kthregressor is calculated by F(z)k, where F(z) is the normal CDF evaluated at

z='Xi/andXi is the vector of independent variables. The marginal effects are calculated at the means of the

independent variables (as described in Maddala, 1983).


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Table I). Like Gczy et al. (1997), we find a positive relation between hedging and the product of the

debt and market-book ratios.

The parameter estimate for the tax function convexity variable is negative and insignificant. This

result does not support the tax convexity motive for hedging. In Section IV.B, we investigate taxincentives to hedge in more detail.

CEO stockholdings are positively related to IR hedging in our sample. This result is consistent

with the linear payoff from equity contributing to risk-averse managerial behavior (Smith and Stulz,

1985). The reported IR results thus confirm in the broad cross-section what Tufano (1996) finds for

gold-mining firms and Schrand and Unal (1998) find among savings and loan companies. However, we

find no relation between stock holdings and hedging when we scale the holdings, or when we use the

Core and Guay (1999) compensation variables (not tabulated). Nor do we find a relation between IR

hedging and the number of options held by the CEO. Overall, the relation between hedging and

managerial risk aversion is at best weak.

Hedging increases with firm size. This result is consistent with fixed costs limiting hedging by

small firms, but not consistent with informational asymmetry leading to increased hedging. The positive

relation between hedging and institutional ownership is also not consistent with the informational

asymmetry hypothesis. This latter finding confirms in the broad cross-section what Gczy et al. (1997)

find for Fortune 500 firms. We also find that IR derivatives hedging increases with the importance of

floating rate debt. Finally, firms with dual classes of stock hedge more, although this result is not

statistically significant.

Robustness of Tobit analysis: Many extant hedging studies exclude financial firms (SIC codes

60-69) and utilities (SIC code 49) because financial firms use derivatives for both risk management and

trading purposes and utilities are regulated. In our paper, we only analyze derivatives that are held for

non-trading purposes to avoid problems associated with financial firms derivative dealer operations

(most banks explicitly disclose derivatives held for asset-liability risk management separately from other

derivative positions). Nonetheless, to benchmark our analysis against the extant literature, the Tobit

analysis is repeated excluding financial and utility firms. Excluding these firms does not materially alter

the reported results.

We repeat the Tobit regressions using total notional value as dependent variable, rather than net


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notional value, to see if netting long and short positions improves our specification. The log-likelihood is

significantly lower for this unreported regression. Also, the ROA and debt times market-book variables

are not significant when total notional value is used as dependent variable. These results indicate that

corporate hedging activity is more precisely measured by net positions than by total positions.There could be a positive relation between the use of IR derivatives and the debt variables

simply because high-debt firms have more liabilities to hedge and not because of financial distress. To

address this concern, we repeat the Tobit analysis, scaling the dependent variable by debt, rather than

by assets (see Model IR 1B). This specification thus measures hedging per dollar of debt. (Note that

this might "over correct" the problem and induce a negative coefficient on the independent variables that

involve the debt ratio because debt is in the denominator of the dependent variable). The results still

show a positive, significant relation between leverage and IR hedging, corroborating the Model IR 1

results.20

Many cross-sectional studies (Nance et al., Mian, and Gczy et al.) examine the yes/no hedging

decision. Given the large variation in extent of derivatives ownership (see Table II), a strength of our

analysis is that we use a continuous dependent variable, enabling us to incorporate more information into

the dependent variable. However, Tobit analysis implicitly assumes that firms make one hedging

decision, the choice of how muchhedging to perform. Strictly speaking, in the Tobit analysis, a zero for

the dependent variable reflects the outcome of the extentof hedging decision, rather than a decision not

to hedge.

Alternatively, the hedging decision might involve two steps. First, the firm decides whether or

not to hedge, and then, how much to hedge (if it hedges). The econometric approach suggested by

Cragg (1971) is used to model this two-step process (see Haushalter, 2000; and Allayannis and Ofek,

1998). The first step examines whether or not a firm hedges (using a probit model) and the second step

examines the extent of hedging, given that a firm hedges (using a truncated regression). In the Cragg

procedure, zero derivative holdings indicate a decision not to hedge, rather than the extent of hedging,

and so the truncated regression only uses observations with non-zero derivative holdings. Our goal here

20There could be a spurious negative relation between debt and derivatives use if foreign debt substitutes forcurrency hedging, as argued by Allayannis and Ofek (1998) and Gczy et al. (1997). To the extent that thissubstitution occurs, it reduces the power of our tests to detect a positive relation between hedging and debt.


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is not to determine how many steps are involved in the corporate decision to hedge. Rather, we present

analysis based on the Cragg two-step approach and contrast these results with the Tobit analysis.

Probit regression: Models IR 2 and 3 of Table VI present results of a binomial probit and

truncated regression, respectively. The signs and significance for the probit coefficients are generallysimilar to those for the Tobit analysis. The probit results indicate that large firms with greater investment

opportunities (as measured by R&D) are more likely to hedge with IR derivatives. The probability of

using IR derivatives is also positively related to the debt ratio. This result is consistent with expected

financial distress costs affecting the decision of whether to hedge with IR derivatives. Like in the Tobit

analysis, NOL carryforwards decrease the likelihood that a firm hedges with IR derivatives. Finally, the

value of CEO stockholdings is positively related to whether a firm uses IR derivatives, consistent with

the managerial risk aversion hypothesis. The decision of whether to hedge is not affected by tax function

convexity.

Truncated regression: The truncated regression in the second stage of the Cragg analysis

measures the extent of hedging activity. As in the Tobit analysis, the truncated regression indicates that

the extent of IR derivatives hedging is significantly affected by leverage and the debt ratio interacted with

market-book. Profitability is also negatively related with IR hedging in the truncated regression. These

findings suggest that the extent of corporate hedging is affected by the expected costs of financial

distress.

There are several differences between the Tobit and truncated regression results. The tax

convexity coefficient is significantly negative in the truncated regression, opposite what is predicted by

theory. The truncated regression coefficients for the R&D spending, NOL carryforwards, institutional

ownership, and CEO stock value are all insignificant, unlike in the Tobit analysis. As in Haushalter

(2000), size is negatively related to the extent of hedging with IR derivatives in the truncated regression.

The negative relation between size and hedging is consistent with the amount of hedging increasing with

the degree of informational asymmetry or distress costs, given that a firm hedges. Or, perhaps larger

firms are more naturally diversified through their operations and thus require smaller hedging positions.

The size result should be interpreted cautiously, however, because firm size (total assets) is the

denominator of the dependent variable.

One interpretation of the differences between the Tobit and truncated regressions is that the


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Tobit analysis blurs the distinction between the choice of whether to hedge with the decision about how

much to hedge. An alternative interpretation is that the truncated analysis loses valuable information

about the chosen extent of (zero) hedging for some firms. To investigate this latter possibility, we look

carefully at the SFAS 119 derivative disclosures. Thirty-four firms report recent hedging activity butcurrently (as of the financial statement date) are not holding derivatives. This is consistent with at least

some firms currently choosing zero for the extent of current hedging, a possibility that is ignored in the

truncated regression.

A.2. FX derivatives hedging

Tobit regression:21Model FX 1 in Panel B of Table VI summarizes the Tobit regression of net

FX derivatives (scaled by assets) on the explanatory variables. The FX sample is only half the size of

the IR sample, and we lose a fair number of FX derivative users because we cannot calculate net

currency positions. Nonetheless, like in the IR sample, we find hedging with currency derivatives

increases with size, debt ratios, R&D spending, and institutional ownership. FX hedging is also higher

when the firm uses interest rate derivatives. We find no relation between tax function convexity and FX

hedging. Unlike in the IR sample, we find a positive relation between hedging and pretax ROA, but no

significant relation with the product of debt and market-book. These FX results generally support the

distress and underinvestment rationales for hedging but not the informational asymmetry, tax convexity,

or managerial risk aversion hypotheses.

Probit regression: The probit regression results in Model FX 2 show that firm size, R&D

spending, and institutional ownership affect the decision to hedge with FX derivatives. Similar to Gczy

et al. (1997), we find that the use of interest rate derivatives and the importance of foreign sales are

positively related to the probability that a firm uses foreign currency derivatives (they examine foreign

income, not sales). Also like Gczy et al. (1997), the CEO stock and options variables are not

significantly related to currency hedging.

Truncated regression: Model FX 3 shows that, for firms that hedge with FX derivatives, the

21In addition to running separate IR and FX regressions, we perform an unreported regression pooling the IR and FXsamples, with the dependent variable equal to the sum of IR and FX hedging. This is appropriate if one believes thatIR and FX derivatives work equally well in reducing the effects of costly volatility. These results are qualitativelysimilar to those shown.


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debt ratio is positively related to the extent of hedging. This is consistent with the financial distress

hypothesis, however the coefficients on other variables do not support the distress argument.

Our results can be contrasted with Allayannis and Ofek (1998), who also perform a truncated

regression on the use of currency derivatives. Perhaps because we sample a broader cross-section offirms and calculate net positions, we find that the debt ratio, size, and ROA are all significantly related to

currency hedging, while Allayannis and Ofek do not. Like those authors, we find that currency hedging

is unrelated to CEO stock and options holdings.

B. Do tax incentives encourage firms to hedge?

We find a strong positive relation between leverage and the extent of hedging using both IR and

FX derivatives. Thus far, we have interpreted this as evidence that high leverage leads to increased

hedging because firms hedge more when the expected costs of distress are high. Stulz (1996), Ross

(1997), and Leland (1998) theorize that causality can also run the other way: hedging with derivatives

increases debt capacity, allowing firms to use more debt and increase firm value through increased tax

deductions. In this section, we jointly model the hedging/financing decision using simultaneous equations

in an effort to determine the direction of causality.

B.1 Simultaneous equations investigation of the link between hedging and debt capacity

In our simultaneous equations model, we use a two-stage estimation procedure similar to that

used by Gczy et al. (1997). In the first stage, separate regressions are performed for derivatives

hedging and the debt ratio. In the second stage, structural equations are estimated using the predicted

values from the first-stage regressions as explanatory variables.

For the first stage, the hedging specification is estimated with a Tobit model, and the debt ratio

equation is estimated with ordinary least squares (OLS). The debt specification uses independent

variables suggested by Titman and Wessels (1988) and Graham, Lemmon, and Schallheim (1998).22

The independent variables in the debt specification are described in Appendix B. Among other things,

22Titman and Wessels (1988) posit that a collection of variables may affect corporate capital structure: non-debt taxshields, asset structure, growth opportunities, asset uniqueness, firm size, income volatility, and profitability. Grahamet al. (1998) use variables measuring marginal tax rates, expected financial distress costs, probability of financialdistress, growth opportunities, asset structure, and industry.


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the debt equation explores whether the extent of derivatives hedging is an important determinant of debt

policy.

The estimated coefficients in the second-stage hedging equation (see Table VII, Panels A and

B) are similar to those presented in Table VI. Of particular interest, the coefficient on the predictedvalue of the debt ratio in Column 1 is positive and significant, indicating that high-debt ratios contribute

to the incentive to hedge with both IR and FX derivatives.

In the second-stage debt regression, the predicted extent of both IR and FX derivatives hedging

is positively related to the debt ratio (Column 2 of Table VII, panels A and B, respectively). 23To our

knowledge, this is the first evidence that hedging increases the debt ratio and consequently increases

value through the tax benefit of interest deductions.

While Leland (1998) and Ross (1997) suggest that firms hedge to increase debt capacity

because of tax incentives, this relation could also be driven by non-tax factors. For example, a

nontaxable firm might hedge to increase debt capacity and use the external funding to invest in profitable

projects, even though it does not benefit from the interest tax deductions. To investigate the relative

importance of tax and non-tax incentives in our "hedging causes debt" result, we include a variable that

interacts the hedging variable with the marginal tax rate, and repeat the second stage regressions. (We

use the simulated marginal tax rates computed by Graham et al. (1998).) For example, in the Table VII,

Panel A specification, we include predictedinterest rate hedging (NET_INTp*), the marginal tax rate

(MTR_BEF), and a new variable that interacts NET_INTp* with MTR_BEF.

In an untabulated regression for the IR sample, the results strongly suggest that tax incentives are

behind the hedging causes debt result: the coefficient on NET_INTp* is 0.096 (t-score of 2.8) and the

coefficient on NET_INTp* x MTR_BEF is 2.14 (t-score of 8.05). This indicates that the incentive to

hedge to increase debt capacity is positively related to the corporate marginal tax rate. Taking the partial

derivative with respect to NET_INTp*, the net effect of hedging to increase debt capacity is positive for

firms with tax rates greater than 4.4%, with the positive effect driven by tax incentives. In the FX

sample, the results are more difficult to interpret because the tax rate and the hedging variable

(NET_CURp*) are highly correlated (the correlation coefficient is 0.98 because most of the FX

23We find the same positive effect of "hedging causing debt" in an unreported regression that measures leveragewith debt-to-value, instead of debt-to-assets.


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hedgers have high tax rates). When both variables are included in a specification analogous to that

reported in Table VII, Panel B, the coefficient on NET_CURp* is positive and significant and the

interactive variable is insignificant. If we drop NET_CURp* and include only the interactive term, the

estimated coefficient is 2.21 (t-score of 2.51). These results are generally consistent with tax incentivesdriving the hedging causes debt result in the FX sample but we can not conclude statistically that this is

the case.

Finally, we contrast our simultaneous results with previous research. Gczy et al. (1997) do not

find that currency hedging significantly increases the debt ratio in their second-stage regression. Note

that our simultaneous system of equations tests whether the extent of hedging affects the debt ratio,

while Gczy et al. (1997) test whether the probabilityof hedging affects the debt ratio. In unreported

analysis, when we change our simultaneous system and use a binary hedging variable in the first stage

(like in Gczy et al. (1997)), we no longer find that currency hedging significantly increases the debt

ratio in the second-stage regression. This analysis indicates that it is not the yes/no decision of whether

to hedge, but rather how much a firm hedges, that increases debt capacity as suggested by Stulz (1996),

Ross (1997), and Leland (1998).

B.2. Comparing tax benefits from increased debt capacity vs. those from tax function convexity

Our evidence implies that firms hedge to increase debt capacity but not in response to tax

function convexity. Although there may be other benefits, the central motive for increasing debt capacity

in several models of corporate hedging is to increase tax deductions (e.g., Stulz, 1996; Ross, 1997; and

Leland, 1998). In this section, we quantify the size of the tax benefits provided by increased debt

capacity and contrast them with the potential (but apparently unexploited) benefits associated with tax

function convexity.

Hedging increases the average (median) firm's debt ratio by 2.9% (2.2%) in the IR sample, and

by 4.5% (3.0%) in the FX sample (see the first column of Table VIII). We calculate these figures by

multiplying the estimated influence of hedging on the debt ratio (i.e., the estimated coefficients for net

derivatives in the second-stage debt regressions) by each firms actual scaled net holdings of IR or FX

derivatives. The mean and median increases in the debt ratios are statistically different from zero

according to a t-test and a Wilcoxon rank-sum test, respectively.


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In column 2 of Table VIII we determine the tax benefit of the extra debt firms use when they

hedge by multiplying the incremental debt usage of each firm by its marginal tax rate. This is just an

application of the traditional corporate tax rate times debt formula to estimate the capitalized tax

benefits provided by debt (see APV approach in Brealey and Myers, 1996). The mean incremental taxbenefit provided by hedging is approximately $81 ($63) million in the IR (FX) samples, with median

values of $11.7 ($17.7) million.

In the third column of Table VIII, we scale each firms incremental debt tax benefit (DTB) from

hedging by its market value from the prior year. The mean (median) tax benefits of increased debt

capacity amount to 1.4% (0.7%) of firm value for IR sample firms and 1.4% (1.0%) for FX firms. If FX

and IR hedging are independent, this indicates that typical tax benefits of hedging from increased debt

capacity contributes between 1.7% and 2.8% to firm value, a value gain consistent with the numerical

examples in Leland (1998). The tax benefits are greater than 5% of value for some firms. To the extent

that there are also nontax benefits, these numbers are conservative estimates of the benefits of hedging

to increase debt capacity.

As a point of comparison, we calculate the tax benefits that would be provided if firms hedged

(i.e., reduce earnings volatility) in response to tax function convexity (see column 4 of Table VIII). 24

For the average firm, hedging to reduce the volatility of earnings by 5% would increase the value of the

firm by approximately 0.15% (assuming that the dollar savings from convexity are a perpetuity

discounted at 10%). This indicates that the tax incentive to hedge to increase debt capacity is more than

ten times larger than the incentive provided by tax function convexity. Therefore, it is not surprising that

the regression analysis documents a tax incentive to hedge to increase debt capacity but not an incentive

to hedge in response to tax function convexity.

V. Conclusion

We investigate whether firms use derivatives to implement risk-management strategies in a

manner consistent with increasing firm value. Although derivatives offer only one means for managing

24If we assume that firms with concave tax functions increase earnings volatility to reduce their expected tax bill, thenegative numbers in the last column of Table VIII would be positive. This would increase the mean slightly but notby enough to change our conclusions.


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risk, the relatively low transactions costs of engaging in a derivatives program make this an ideal setting

to study corporate hedging practices. For example, Brown (1999) studies an anonymous firm active in

currency hedging with derivatives. He estimates the annual costs associated with the currency hedging

program to be $3.8 million annually.

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This cost estimate is quite low compared to the average taxbenefits of hedging illustrated in Table VIII. Another reason to study derivatives when analyzing

corporate risk management is because they are disclosed in financial statements, while other hedging

strategies are more difficult to observe.

We find evidence that corporate hedging practices are consistent with optimal risk management.

Our results indicate that firms hedge in response to high costs of underinvestment and financial distress.

We also find that hedging increases firm value by increasing debt capacity and interest deductions. In

particular, we estimate that the tax benefits resulting from hedging add between 1.7% and 2.8% to firm

value.

In general, we find that small firms hedge less than do large firms. This result is inconsistent with

the notion that small firms face substantial informational asymmetry costs and therefore should hedge

more than large firms. Instead, this result may indicate that there are large fixed costs to implementing a

derivatives hedging program, and small firms are less likely to achieve sufficient benefits to offset this

cost.

We do not find any evidence that hedging increases with the convexity of the corporate income

tax function. This result is notable because we use the most precise measure of convexity presently

available. Our interpretation is that firms do not hedge in res

2000 - does corporate hedging increase firm value- an empirical analysis

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