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Covenant Thresholds and the Agency Costs of Debt

Adam B. Badawi⇤

School of Law, Washington University in St. Louis

September 10, 2014

Note: Early draft with preliminary results. Please do not cite or circulate.

Abstract

The finance literature has characterized debt covenants as a mechanism that can

help manage the agency conflicts between creditors and shareholders. While there is

some evidence concerning the relationship between bond covenants and shareholder

influence, there is little research on the association between lender covenants and

shareholder control. After suggesting why the context of bond covenants presents

substantially di↵erent problems than those present in bank lending, this paper de-

velops evidence about the relationship between loan covenant slack and shareholder

influence. Using active institutional ownership to proxy for that influence, this paper

shows that there is a negative association between covenant slack and shareholder con-

trol. That relationship changes, however, in the presence of entrenched management.

This evidence supports the agency-conflict model of debt covenants and it suggests

that lenders may use those covenants to channel shareholder e↵ort toward monitoring

that may benefit both lenders and shareholders.

⇤e-mail: [email protected].

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1 Introduction

Debt contract covenants have conventionally been viewed as a mechanism to reduce the

agency costs associated with the issuance of that debt (Jensen and Meckling, 1976). In the

context of bank lending, these covenants often specify the thresholds for financial metrics and,

should circumstances trigger the covenant, the contracts typically give lenders the right to

accelerate debt payment. As the research on these provisions shows, the amount of influence

they provide to creditors is considerable (Chava and Roberts (2008) and Demiroglu and

James (2010)). Even prior to meeting the thresholds, managers appear to alter investment

strategy in response to covenants (Nini et al., 2009). Once triggered, creditor influence

is even more dramatic because the contracts typically give them the right to accelerate

debt payment. Creditors use this leverage to alter firm behavior in ways that reflect their

sensitivity to default risk. That can include stark changes in investment policy and can also

lead to changes in management (Nini et al., 2012).

While existing research has explored the setting and use of loan covenant thresholds,

there is less evidence regarding the relationship between loan covenant thresholds and the

makeup of a firm’s shareholders. Institutional shareholders are of particular interest because

they are better able to wield influence in the firm (Shleifer and Vishny, 1986). Their large

holdings give them both the incentive to monitor and the power to influence firm decisions.

This paper explores the relationship between active institutional ownership and a central

measure of the ability of creditors to assert control—the amount of slack in the net worth

covenants in bank loans.

The relationship between creditor and shareholder control is an open empirical question.

The agency cost literature provides a number of well-rehearsed reasons to expect conflict

between creditors and shareholders. Shareholders may press for the firm to take on more risk

through asset substitution or through activity in the takeover market (Jensen and Meckling

(1976) and Nash et al. (2003)). Creditors are likely to resist these activities insofar as they

increase the probability of default. To the degree that these conflicts predominate, one should

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expect creditors to press for more control when shareholders are better able to influence firm

decisions. Doing so may also bring the benefit of channeling shareholder monitoring into

areas where their collective interests are more likely to be aligned.

But there is also reason to believe the preferences of shareholders and creditors overlap in

significant ways. Both parties have an interest in preventing management shirking because it

can decrease the value of the firm while increasing default risk (Barclay and Holderness (1992)

and Huddart (1993)). This potential alignment of interests may lead creditors to increase

covenant slack when shareholders have influence over the firm. By doing so, creditors can

reduce the expected monitoring and negotiating costs that accompany tighter covenants.

Lender covenant slack is an attractive variable for understanding the extent of interest

conflict with shareholders due to the nature of the control rights the a covenant violation pro-

vides. Unlike targeted restrictive covenants—which prevent specific actions such as dividend

payments of a certain size—the debt acceleration rights triggered by a financial covenant

provide what amounts to plenary control over the firm. The lender thus saves the need to

negotiate and draft detailed restrictions while still gaining the prospect of significant control.

There is some evidence about the relationship between bond covenants and shareholder

power (Chava et al., 2010), but the corporate governance e↵ects of bond covenants and loan

covenants are likely to di↵er substantially. While bond agreements often allow for acceler-

ation of payment, monitoring by bond holders tends to be much more passive. This light

monitoring is a consequence of a substantial collective action problem faced by bondhold-

ers and the lack of legal and monetary incentives for bond trustees to pursue violations of

covenants (Kahan and Rock, 2009). Trustees owe no fiduciary duties to bondholders and

are unlikely to reap large rewards in the event they do recover for holders. Moreover, courts

tend to read bond covenants narrowly, which further complicates their enforcement. As a

consequence, bond trustees will rarely, if ever, use the leverage that a covenant violation

provides to insist on operational changes. Demands will instead center on payment of the

accelerated debt or an appropriate settlement amount. The limited monitoring and control

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rights of bond holders is likely to mean that their attempts to impact governance is unlikely

to go farther than the impact contract provisions have on firm behavior.

Lenders, in contrast, have the leverage to implement much more significant change be-

cause their acceleration rights and intense monitoring capabilities can provide de facto control

over the firm. As the corporate law literature has long emphasized, this control has to come

from somewhere; authority gained by one firm constituency necessarily limits the power of

others (Bainbridge (2006) and Bebchuk (2005)). The relationship between loan covenant

slack and the degree of shareholder influence should thus provide insight about the degree

of interest conflict or alignment when ultimate control of the firm is at stake.

The evidence developed here supports the agency-conflict model. As there is a larger

presence of both transient and dedicated institutional investors in the period prior to a bank

loan, there appears to be a lower amount of net worth covenant slack in those loans. This

observation is consistent with the view that a larger base of active shareholders can lead

to an insistence by creditors on stronger control rights. To the degree that these investors

will make use of that influence to push for more risk and return, lending covenants may

reflect that concern. To help minimize concerns that covenant slack and active ownership

are jointly determined, I use index membership and measures of liquidity as instruments for

active institutional control. These instruments provide results that are similar to the initial

regressions.

The potential agency conflicts between creditors and shareholders are likely to be at

their height when it comes to acquisition activity. Creditors may worry that the increase in

leverage that accompanies these transactions will increase default risk (Warga and Welch,

1993). They may also have concerns that acquisitions will lead to the subordination of ex-

isting debt.1 Shareholders, alternatively, may prefer this activity insofar as it results in the

payment of a control premium or the potential for higher profitability. The governance liter-

ature has throughly examined the extent to which management entrenchment—as measured

1Creditors may not dislike so-called insuring, conglomerate mergers that increase firm diversification andhence decrease default risk.

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by the presences of mechanisms such as staggered boards and poison pills–a↵ects takeover

agency concerns and firm value (Gompers et al. (2003) and Bebchuk et al. (2008)).

Two results from this literature on entrenchment provide a prediction for the relationship

between loan covenant slack and takeover protection. First, there is evidence that institu-

tional ownership and takeovers are complements (Cremers and Nair, 2005). The presence of

these shareholders, who can more easily monitor and exert influence, may facilitate acquisi-

tion activities by pushing managers to find partners or actively solicitingbids. This research

implies that conditions for takeovers may be ripe when institutional ownership is high and

takeover protection is low. Creditors can be expected to be especially concerned in these

circumstances.

The second result suggests that loan contract terms may respond to the threat of

takeovers. Chava et al. (2009) show a positive relationship between manager entrenchment,

as measured by the widely used G and E indices, and loan yields. This evidence indicates

that lenders price some of the risk related to the possibility of takeovers. Lenders may also

use covenant slack as a mechanism to govern takeover risk. The leverage that tight covenants

provides should lead to an ability inhibit acquisition activity when the risk of that activity

is high.

Putting these two results together leads to the prediction that covenant slack is likely to

be tighter when institutional ownership is high and management entrenchment is low. As

entrenchment increases, however, the risk of takeovers may recede. In the presence of reduced

takeover risk, creditors may, all other things being equal, be more tolerant of the lesser control

that comes with loose covenant slack. The evidence bears out this prediction. Conditional on

a high amount of dedicated institutional ownership, there is a negative relationship between

management entrenchment and covenant slack.

This paper proceeds as follows. The next section reviews the literature on how parties

set covenant thresholds and what evidence there about the relationship between creditors

and shareholder agency conflict. In discussing the relationship between covenants and the

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interests of equity, debt, and management, this section also discusses potential hypothe-

ses. Section 3 describes the data and outlines the empirical model. Section 4 presents the

results from the cross-sectional regressions and then details attempts to address potential

endogeneity. Section 5 makes some concluding remarks.

2 Literature Review and Theory Development

The ability of debt covenants to help manage agency costs are a central component

of the agency-centric view of the firm (Jensen and Meckling, 1976). Covenants generally

restrict managers by granting substantial control rights to creditors when circumstances

trigger those covenants (Baird and Rasmussen, 2006). This e↵ect can incentivize managers

to avoid default risk and it can help channel shareholder monitoring to areas where their

interests overlap with those of creditors.

The theoretical literature on the role of covenants has helped to spur a series of empirical

investigations into the structure of debt covenants (Bradley and Roberts (2004) and Murfin

(2012)) and the e↵ect of those covenants on firm behavior. There is a significant amount

of evidence that covenants do have ex ante and ex post constraining e↵ects on manager

behavior. When a covenant metric is close to the relevant threshold, managers may adjust

investment activity to avoid a violation (Dyreng (2009) and Dichev and Skinner (2002)).

The debt covenant hypothesis maintains that managers may manage financials in a way

that avoids violation, although there is also some evidence that creditors can control that

behavior through contract (Roberts and Sufi, 2009). When violations do happen, even a

waiver by the creditor can result in substantial changes to the operation of the firm, including

the replacement of management.

While there has been relatively little investigation of the relationship between shareholder

influence and lender covenants, there is some evidence of the relationship between shareholder

influence and bond covenants. Chava et al. (2010) find that increases in shareholder power

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are associated with restrictions on dividend payment and on subsequent financing. They

do not, however, find an association with shareholder power and investment restrictions.

Zhang and Zhou (2013) find a negative relationship between the overall restrictiveness of

bond covenants and institutional influence. They also show a negative relationship between

shareholder influence and a category of covenants that includes prohibitions on payouts,

mergers, assets sales, and some investment-related activity.

It is unclear, however, that the lack of evidence concerning the relationship between

shareholder power and investment restrictions in bond covenants has much application in

the context of more active lending. While lenders and creditors are likely to want to mini-

mize default risk, their means for doing so di↵er substantially. Bondholders face substantial

collective action problems (Schwarcz and Sergi, 2008). That di�culty makes not only makes

it di�cult to monitor, it makes it di�cult to use the threat of acceleration to implement

operational changes. In theory, bond trustees are supposed to represent the interests of

bondholders, but they typically cannot act until 25 percent of bondholders grant them per-

mission. And even when that occurs, there are few incentives in place to motivate the trustee

to act due to limited financial rewards. Moreover, the legal requirements are controlled by

contract rather than through generally more restrictive fiduciary duties.

These limitations on bondholder action may drive a reluctance to insist on investment-

related restrictions in covenants. Unlike restrictions on actions that more directly conflict

with bondholders interests–such are prohibitions on dividends and new debt–some degree

of investment may serve bondholder interests. Without close monitoring, however, those

bondholders are unlikely to be able to di↵erentiate between investments they favor and

those that they dislike.

The ability of lenders to monitor more actively likely means that they have more options

when it comes to altering investment behavior. As theoretical models of covenants show, the

ability to acquire information helps to understand why lenders use covenants. By allowing

for the possibility of control rights, lenders can use any signals generated between the signing

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of the contract and the triggering of a covenant to determine whether to shut down a project.

This benefit of covenants for lenders does not, however, provide a concrete prediction

with respect to how shareholder influence will a↵ect the setting of those covenants. To the

degree that lender and shareholder interests overlap, lenders may allow more slack when

shareholders can wield influence in the firm. By doing so, lenders may benefit from the

influence that shareholders can provide. Allowing more covenant slack should decrease the

cost to lenders through a lower cost of monitoring and a lower likelihood of having to negotiate

the consequences of a covenant violation.

Alternatively, if conflict concerns predominate, lenders may prefer tighter slack in order

increase the likelihood of their control over the firm. A tripwire that grants lenders control

when firm equity falls below a certain level should help to discourage shareholders from taking

equity-destroying actions that they may prefer. For example, a large dividend payment might

trigger the covenant and lead to lender control. Likewise, creditors may be more sensitive to

downside risk with a tighter covenant and hence that may help to diminish asset substitution

(Christensen and Nikolaev, 2012). Because a tighter covenant dissuades shareholders from

pressing for actions that will trigger that covenant, there may be an added benefit that they

channel their influence towards actions that benefit both themselves and lenders.

As other commentators have noted, how the conflict and overlap of creditor and share-

holder interests will manifest themselves in creditor restrictions will ultimately play out is

an empirical question (Zhang and Zhou, 2013). As an oft-cited Moody’s Investor quote puts

it: “While there is substantial overlap between creditor and shareholder interests, there

also are important potential conflicts.” Given the theoretical indeterminacy, the goal of the

analysis that follows is to shed empirical light on the nature of this relationship in the context

of lender agreements.

It is more straightforward to make a prediction about the interaction of active shareholder

ownership and management entrenchment. As discussed at the outset, there is evidence of

a positive association between the degree of shareholder influence and acquisition activity.

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Cremers and Nair (2005) show that a portfolio of firms that have large ownership by active

shareholders (public pension funds) and low takeover protection and shorts companies with

similar ownership, but low takeover vulnerability, earns large, positive abnormal returns. A

portfolio that purchases low pension fund ownership firms that is vulnerable to takeovers

and shorts firms with low ownership and significant takeover protection earns no significant

abnormal returns. This evidence is consistent with the view that active shareholders may

play an important role in encouraging activity in the takeover market (Shleifer and Vishny

(1986) and John and Kedia (2006)).

Creditors can be expected to worry about potential acquisition activity. These transac-

tions can increase default risk by increasing leverage and subordinating existing debt (Warga

and Welch, 1993). In the context of lending, there is evidence that banks incorporate these

concerns into their agreements. Chava et al. (2009) show that firms with less entrenchment

and stronger shareholder rights pay a significant loan premium over firms that are less likely

to be subject to shareholder influence. This research suggests that banks are sensitive to the

influence that shareholders might wield and price loans accordingly.

These two findings imply that creditor concerns about mergers are likely to be most acute

when shareholders have influence and takeover protection is low. That environment may be

especially conducive to the takeover activity that lenders fear. One potential response to

those concerns is to increase the chance of exerting control. Lenders can do this by tightening

the amount of covenant slack in the loan because doing so means that they can use the

looming threat of debt acceleration to counter shareholder attempts to influence acquisitions.

Takeover protection—such as poison pills and staggered boards—should, however diminish

some of these acquisition related concerns.

This theory suggests the following hypothesis:

H0: Conditional on high active shareholder ownership, there should less covenant slack

when firms have little takeover protection in place.

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3 Data and the Empirical Model

This section describes the data collected and the empirical model used to examine the

relationship between equity ownership and covenant slack. I begin with the loans reported to

Loan Pricing Corporation’s (LPC) DealScan loan database. The database includes details

on the levels of certain covenants including the threshold for net worth and tangible net

worth covenants. Covenant information is, however, reported at the package level rather

than at the facility level.2 There is an obvious lack of independence between the facilities

within the same package and, as a consequence, I use the package as the unit of observation.

The amount of the package is the sum of the amounts of all the facilities in the loan package.

The financial and stock index data come from Compustat, which I link to the Dealscan

database using the file provided by Roberts and Chava (Chava and Roberts, 2008)). I Win-

sorize all continuous financial variables at 1 percent and 99 percent to reduce the influence

of outliers. I calculate Z-Score using the formula developed by Altman (1968). Credit rating

and index membership information comes from S&P and CRSP supplies the relevant stock

liquidity data. I obtain the data on institutional ownership from the 13-F filings compiled by

Thompson Reuters and I group the institutions using the categorization created by Bushee

(1998).

The Bushee categorizations break down institutional investors into three categories: ded-

icated, transient, and quasi-indexers. Dedicated institutions have concentrated holdings and

do not trade that often. Transient institutions have diversified holdings and trade frequently.

Quasi-indexing institutions have diversified holdings and seldom trade.

Bebchuk et al. (2008) provide the data on E-Index. This is a measure that sums the

number of six entrenchment measures adopted by the firm. Four of those measures limit

shareholder voting power: staggered boards, limits to shareholder amendments of the by-

laws, supermajority requirements for mergers, and supermajority requirements for charter

amendments. The other two are protections against hostile o↵ers: poison pills and golden

2Packages are a group of loans, lines of credit, or facilities, that share documentation.

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parachutes. I also use the G-Index created by Gompers et al. (2003) to evaluate the robust-

ness of the entrenchment analysis. The G-Index sums 24 measures of management power.

The regressions with the largest number of observations have 1415 total loan packages

that span from 1993 to 2010 from 858 separate firms. Table 1 presents basic summary

statistics for the financial data. The financial statistics are from the quarter prior to loan

origination, which should help to capture the information available to lenders at the time of

contracting.

The primary variable of interest is the amount of slack in the net worth covenant each

loan package. To increase the number of observations, I use covenants based on total net

worth and those based on tangible net worth. Following a method similar to Ertan et al.

(2013), I define the slack variable as the amount of slack–the relevant metric (total or tangible

net worth) less the amount of the covenant threshold— divided by the standard deviation of

the metric from the previous eight quarters. Higher values of the variable represent a high

amount of slack.

I remove all loans that appear to be in violation in the quarter of origination, I remove

all loans for firms that report negative book value in the 10-K filed prior to the loan, and

I omit financial firms. In addition, I use the Sufi and Smith’s data on covenant violations

to identify any firm that has violated a covenant in the previous eight quarters and I omit

those firms. Finally, to help limit the possibility that that covenant slack is the product of

di�cult-to-observe financial distress I limit firm loans to the largest loan taken out by the

firm per calendar year.

There is some concern that limiting covenant slack to net worth covenants may introduce

measurement error because contracts often contain other covenants that may be even tighter.

A significant complication is that the Dealscan database uses a fairly rough grouping of fifteen

covenant categories (Demerjian and Owens, 2013). Some research suggests that the net worth

covenants are a strong measure of slack because the definition of net worth is most likely

to be uniform across loan contracts (Dichev and Skinner, 2002). If this evidence is correct,

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there is a tradeo↵ between the additional information that incorporating other covenants

provides and the additional measurement error that comes with those other covenants. I

limit the variable to net worth covenants, with the acknowledgment that any measure will

include some error.

As one method of addressing the potential imprecision of the net worth covenant, I

incorporate information about the number of covenants to create an additional dependent

variable. To do so, I divide the net worth slack measure by the root of the number of

financial covenants in the contract. As the number of covenants increases, this measure of

slack decreases.

The primary specification for the regressions is as follows:

COV SLACKi,t = ↵i + �t + �Xi,t + �INSTOWNi,t�1 + ✏i,t (1)

where i indexes borrowers, �t captures year-quarter fixed e↵ects, Xi,t attempt to control

for observable borrower and contract characteristics, INSTOWN are the various measures

used to capture shareholder influence, and ✏i,t is the error term. Every regression uses robust

standard errors adjusted for firm-level clustering.

A chief concern is that shareholder influence and covenant slack may be jointly determined

and that will result in biased estimates of �. For example, institutions may base their

purchase decisions on the basis of the expected flexibility that future loans provide. To

attempt to mitigate this concern, I use lagged values of shareholder ownership (four quarters

prior to loan origination). These past values should provide some indication to lenders of the

degree of shareholder influence, but their temporal distance from the loan means it is less

likely that institutional ownership turns on anticipated covenant slack. The section below

on robustness checks and endogeneity explores these concerns in greater detail.

The controls in Xi,t follow previous research on how borrower characteristics relate to

loan contract terms. To reflect borrower risk, I use fixed e↵ects for S&P long-term debt

ratings at the time of issuance, as well as logged net worth, EBITDA/assets, book-to-market

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ratio, leverage, and Z-score. The contract controls include logged values of the total facility

amount, the maturity of the loan, and an indicator variable for whether the loan is secured.

Some specifications include fixed-e↵ects for loan purpose, which include working capital, loan

repayment, and takeovers.

4 Institutional Ownership and Covenant Slack

4.1 Baseline Results

This section presents the results from the baseline regressions that explore the relation-

ship between institutional ownership and covenant slack. This analysis uses separate and

combined measures of active ownership. The combined active ownership variable sums the

amount of transient ownership and dedicated ownership and terms that variable active own-

ership. While dedicated and transient owners are likely to have some conflicting interests—

say, with respect to short-term and long-term results—both groups can be expected to wield

more influence than passive (quasi-indexing) shareholders.

Tables 2 & 3 present these baseline results. I use both measures of covenant slack as

dependent variables. Table 2 provides results for the separate measures of institutional own-

ers with and without the controls for loan purpose. The results show negative coe�cients

associated with both types of active ownership. The coe�cient for transient owners is sta-

tistically significant in all four specifications while the coe�cient for dedicated owners is

only significant in the specifications that use the second measure of covenant slack. These

results provide evidence that the relationship between covenant slack and active control is

negative. The insignificance of degree of passive ownership buttresses the inference that this

relationship is confined to active ownership of equity. This evidence—that transient and

dedicated shareholders, but not quasi-indexers, exert influence over the firm—is in line with

other studies that use these measures of shareholder control (Aghion et al., 2013).

Table 3 uses the combined measure of active ownership. The relationship is stronger—

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in the sense that standard errors are lower—when comparing all active ownership against

passive ownership. In all four specifications, the coe�cient for active ownership is negative

and is significant at the one-percent level. These results provide substantial support for the

agency conflict view; as active institutional ownership increases there is a negative relation-

ship with the amount of covenant slack. In these specifications, the percentage of passive

ownership is again insignificant across all four regressions. This lack of significance provides

more evidence that it is only active ownership that has a relationship with covenant slack.

The results for the other controls are generally in line with previous studies on the

determinants of loan contract provisions. As one might expect, there is negative relationship

between the size of loan and the amount of covenant slack, which implies that larger loans

may require closer monitoring (Murfin, 2012). There is a positive and significant relationship

between logged net worth, a measure of firm financial strength and covenant slack. Though

unreported, the credit rating fixed e↵ects exhibit a positive relationship between the strength

of that rating and covenant slack, which again one would expect. Finally, there is positive

relationship between maturity and slack, which is consistent with other studies that examine

these relationships.

The existing evidence on covenants and growth opportunities—as proxied by book-to-

market ratio—is more mixed. Bradley and Roberts (2004) find that firms with higher growth

prospects set stricter covenants. Alternatively, Demiroglu and James (2010) show that higher

growth firms get more covenants, with looser thresholds. The evidence here provides some

support for the Bradley and Roberts view because higher book to market values (i.e. lower

growth firms) are associated with more covenant slack.

4.2 Takeover Protection and Covenant Slack

The baseline results show a relationship between both dedicated and transient institu-

tional owners and tighter covenant slack. If the association is a result of lenders worrying

about shareholder influence, there might be a di↵erent set of concerns attached to each of

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these groups. Some research shows that transient investors care more about short-term re-

sults than those with longer investment horizons (Bushee, 1998). Lenders may worry that

short-term investors will press for actions that will increase default risk in the near term.

An example would be choices that increase short-term earnings, but do so through choices

that imperil overall stability. Dedicated investors may not press for these sort of short-term

results, but they may be better able to wield influence due to their long-run relationships

with mangers.

While dedicated shareholders may share the interests that creditors have in avoid-

ing short-term default risk, their preferences may diverge more sharply when it comes to

takeovers. Dedicated shareholders may be able to use their better information about the

firm—as opposed to transient shareholders—to market transactions to potential acquirers. In

these circumstances, creditors may worry about those transactions, especially when takeover

protections are low. As those takeover protections increase, those concerns may recede.

To examine this relationship, I create indicator variables for whether a firm is in the

highest quartile of dedicated, transient, or active share ownership. I interact the indicator

for highest quartile of for each of these categories with E-Index and regress it against both

measures of covenant slack along with the controls.3 Table 4 presents the results for the

highest quartile of dedicated ownership. The table shows a negative relationship and statis-

tically significant relationship between high dedicated ownership and covenant slack persists.

But the interaction variable shows that, conditional on high dedicated ownership, there is

a positive association with covenant slack as management entrenchment increases. That

positive association is statistically significant at the five-percent level using both measures

of measures and in the specifications that include and do not include the contract controls.

Unreported regressions for the highest quartile of transient and active owners show no such

e↵ect. Moreover, the relationship with dedicated owners is robust to use of the alterna-

3Coverage for the E-Index and G-Index is not as wide as the Dealscan database. Consequently, thenumber of observations is substantially smaller in these regressions. Both these indices use the IRCC database(now Riskmetrics), which includes the approximately 1500 companies in the SP 500, SP MidCap, and SPSmallCap indices.

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tive, G-Index; unreported regressions show the same positive association interacted high,

dedicated quartile variable and the G-Index.

These results provide support for the hypothesis that conflict between dedicated share-

holders and lenders is higher when takeover risk is larger. As entrenchment provides some

measure of protection against a leverage-increasing acquisition, creditors may be less insis-

tent on the greater prospect of control that comes with tighter covenant slack. In addition

to shedding some light on the creditor control and takeover risk, this result also provides

support for the view that dedicated shareholders may be more apt than other institutional

shareholders to facilitate takeover activity.

5 Robustness and Endogeneity Concerns

The results in Tables 2, 3, and 4 are generally robust to alternative specifications. This

includes the substitution of year-quarter fixed e↵ects for the year fixed e↵ect and the use of

Fama-French 48-category fixed e↵ects in place of the 10-category fixed e↵ects. In some cases

the standard errors are larger when using those fixed e↵ects, but in all cases the variable

active shareholder ownership shows a statistically significant and negative relationship with

both measures of covenant slack.

The selected financial controls are an additional concern. The primary specifications

rely on logged net worth, EBITA/Assets, leverage, book/market, and Z-score as these are

controls commonly used in debt covenant research. Some other models use additional or

alternative variables such as current ratio, fixed charge, and logged sales. Including all of

these variables with the existing controls, as well as substituting some of them for others,

does little to change the results. The core result concerning active institutional ownership

persists in all of these specifications. The standard errors are larger for some of the other

core results, but the signs and magnitudes of the coe�cients are similar in all specifications.

An additional concern is the lack of identification in the regressions thus far. Omitted

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variable bias along with the potential joint determination of covenant slack and institutional

ownership may render the coe�cients biased and inconsistent. The former is a problem if

lenders and institutions are selecting on the basis of unobserved variables. The latter is

an issue if, for example, institutions anticipate potential covenant slack and make equity

purchase decisions on that basis. Using lagged values of institutional ownership provides

some guard against this possibility, but the potential for joint determination persists.

To attempt to mitigate these concerns, I use instrumental variables for institutional

ownership. To be e↵ective as an instrument, a variable must satisfy both the relevance

condition—it is correlated with the potentially endogenous regressor—and the exclusion

restriction—its e↵ect on the dependent variable is limited to its e↵ect on the potentially

endogenous regressor.

I look to the existing literature for instruments. Inclusion in the SP 500 has been used in

several studies as one instrument for institutional demand for shares (Aghion et al. (2013) and

Beber et al. (2012)). The rationale is that institutional managers are often evaluated against

the performance of indices. Consequently, they may favor stocks in those indices when

making purchasing decisions. In the case of institutions subject to ERISA, this pressure

may be especially strong because failure to meet indexed performance standards can lead to

legal liability. At the same time, inclusion in the SP 500 is unlikely to be related to covenant

slack. The SP selection process typically seeks firms that are representative of certain sectors

of industry. Given that standard, it is unlikely that expected financial flexibility in future

loans motivates the choice.

Other studies use measures of liquidity as an instrument for institutional demand (Zhang

and Zhou, 2013). The theory is that institutions wishing to build large holdings in a firm’s

equity will, all else equal, be drawn to the lower cost associated with highly liquid firms.

Moreover, if the threat of institutional exit is an e↵ective governance mechanism, liquidity

should facilitate that channel (Edmans, 2009). While stock liquidity may have a relationship

with default risk, it is unlikely that lenders look to that variable when deciding on covenant

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slack. Available evidence suggests that lenders look to more direct financial measures to

determine strictness, such as current ratio, leverage, and fixed charge coverage (Murfin,

2012). To proxy for liquidity, I take the average of daily turnover (shares traded/shares

outstanding) in a window that begins two years prior to loan origination and ends one year

prior to loan origination. I also use the proportion of non-zero trading days for the year

prior to the last day of the fourth quarter prior to loan origination.

Table 5 presents the second stage results from two-stage least squares estimation using two

di↵erent groups of the instruments. The first and second regressions use SP 500 membership

and lagged average daily turnover as instruments. The third and fourth regressions use SP

500 membership, the lagged turnover variable, and lagged non-zero returns as instruments.

In each of these specifications, the coe�cient for the share of active ownership is negative

and significant at the one-percent level. 4 These estimates help to mitigate concerns that

the core result in the model is the product of joint selection of covenant slack and active

ownership.

6 Concluding remarks

This paper finds evidence that there is a negative relationship between loan covenant slack

and the amount of active institutional equity ownership. These findings, which are robust

to alternative specifications and persist when attempting to control for endogeneity, support

the agency-conflict model of debt covenants. The evidence also shows that management

entrenchment may ease some of these conflict fears. That finding suggests that the takeover

risk associated with active institutions may be an especially important driver of agency

conflict between lenders and shareholders.

4In all four regressions, the first-stage F-statistic for the excluded instruments exceeds ten.

18

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Table 1: Summary Statistics

Mean SD p10 p50 p90Slack 3.268 3.599 0.502 2.061 7.467Slack/sqrt(Num. of Cov.) 2.081 2.431 0.290 1.244 4.893Lag. Share Dedicated 0.086 0.102 0 0.052 0.227Lag. Share Transient 0.156 0.137 0.013 0.119 0.351Lag. Share Indexers 0.296 0.204 0.056 0.260 0.597Lag. Share Active 0.241 0.174 0.036 0.211 0.482No Rating 0.669ln(Net Worth) 19.382 1.375 17.717 19.345 21.069ln(Amount) 18.632 1.333 16.811 18.721 20.292ln(Maturity) 3.653 0.601 2.485 3.784 4.094Secured 0.550EBITDA/Assets 0.035 0.028 0.011 0.035 0.062Leverage 0.238 0.168 0.006 0.236 0.465Book/Market 0.612 0.496 0.209 0.499 1.102Z-Score 2.979 4.443 0.799 1.926 6.112Purpose: Takeover 0.141Purpose: Work. Cap. 0.554Purpose: Repayment 0.228Observations 1415

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Table 2: Covenant Slack and Institutional Ownership by Type

(1) (2) (3) (4)Slack Slack/

p#Cov. Slack Slack/

p#Cov.

Lag. Share Dedicated -1.439 -1.407 -1.540 -1.472(1.067) (0.710)⇤⇤ (1.065) (0.708)⇤⇤

Lag. Share Transient -2.595 -1.583 -2.547 -1.553(0.748)⇤⇤⇤ (0.500)⇤⇤⇤ (0.750)⇤⇤⇤ (0.503)⇤⇤⇤

Lag. Share Indexers 0.587 0.238 0.557 0.210(0.809) (0.524) (0.795) (0.511)

ln(Net Worth) 0.854 0.577 0.882 0.591(0.157)⇤⇤⇤ (0.105)⇤⇤⇤ (0.162)⇤⇤⇤ (0.109)⇤⇤⇤

ln(Amount) -0.851 -0.600 -0.925 -0.638(0.147)⇤⇤⇤ (0.101)⇤⇤⇤ (0.157)⇤⇤⇤ (0.109)⇤⇤⇤

ln(Maturity) 0.557 0.259 0.619 0.300(0.185)⇤⇤⇤ (0.125)⇤⇤ (0.185)⇤⇤⇤ (0.125)⇤⇤

Secured -0.196 -0.188 -0.241 -0.211(0.236) (0.147) (0.232) (0.147)

EBITDA/Assets 2.550 1.096 3.290 1.630(2.955) (2.075) (2.931) (2.068)

Leverage -0.415 -0.379 -0.333 -0.342(0.680) (0.440) (0.687) (0.447)

Book/Market 0.548 0.349 0.579 0.374(0.218)⇤⇤ (0.132)⇤⇤⇤ (0.221)⇤⇤⇤ (0.135)⇤⇤⇤

Constant 2.840 3.645 3.997 4.293(3.086) (2.210)⇤ (2.968) (2.127)⇤⇤

Observations 1415 1415 1415 1415R2 0.138 0.187 0.145 0.193Year Fixed E↵ects Yes Yes Yes YesCredit Rating Fixed E↵ects Yes Yes Yes YesIndustry Fixed E↵ects Yes Yes Yes YesContract Purpose Fixed E↵ects No Yes No Yes

This table presents OLS results with fixed e↵ects. Dependent variable in the first and third regressions is theamount of covenant slack divided by the standard deviation of the relevant metric in the eight quarters prior to loanorigination. The dependent variable in the second and fourth regressions is the initial slack variable divided by thesquare root of the number of covenants. Some variables, including all the fixed e↵ects, have been omitted for brevity.Heteroskedasticity-robust standard errors are clustered by borrowing firm and are reported in parentheses. ***, **,and * denote significance at the 1%, 5%, and 10% confidence levels, respectively.

24

Table 3: Covenant Slack and Active Institutional Ownership

(1) (2) (3) (4)Slack Slack/

p(#Cov.) Slack Slack/

p(#Cov.)

Lag. Share Active -2.159 -1.517 -2.167 -1.523(0.592)⇤⇤⇤ (0.397)⇤⇤⇤ (0.590)⇤⇤⇤ (0.396)⇤⇤⇤

Lag. Share Indexers 0.539 0.230 0.514 0.207(0.806) (0.522) (0.791) (0.509)

ln(Net Worth) 0.849 0.577 0.878 0.591(0.157)⇤⇤⇤ (0.105)⇤⇤⇤ (0.162)⇤⇤⇤ (0.109)⇤⇤⇤

ln(Amount) -0.850 -0.600 -0.925 -0.638(0.147)⇤⇤⇤ (0.101)⇤⇤⇤ (0.157)⇤⇤⇤ (0.109)⇤⇤⇤

ln(Maturity) 0.554 0.258 0.617 0.300(0.185)⇤⇤⇤ (0.125)⇤⇤ (0.185)⇤⇤⇤ (0.125)⇤⇤

Secured -0.199 -0.189 -0.244 -0.211(0.237) (0.147) (0.232) (0.147)

EBITDA/Assets 2.407 1.074 3.173 1.621(2.972) (2.076) (2.949) (2.070)

Leverage -0.420 -0.379 -0.335 -0.342(0.680) (0.440) (0.686) (0.446)

Book/Market 0.561 0.351 0.590 0.375(0.218)⇤⇤ (0.132)⇤⇤⇤ (0.221)⇤⇤⇤ (0.135)⇤⇤⇤

Constant 3.010 3.670 4.148 4.305(3.071) (2.196)⇤ (2.956) (2.114)⇤⇤


This table presents OLS results with fixed e↵ects. Dependent variable in the first and third regressions is theamount of covenant slack divided by the standard deviation of the relevant metric in the eight quarters prior to loanorigination. The dependent variable in the second and fourth regressions is the initial slack variable divided by thesquare root of the number of covenants. Some variables, including all the fixed e↵ects, have been omitted for brevity.Heteroskedasticity-robust standard errors are clustered by borrowing firm and are reported in parentheses. ***, **,and * denote significance at the 1%, 5%, and 10% confidence levels, respectively.

25

Table 4: Dedicated Ownership and Managerial Entrenchment

(1) (2) (3) (4)Slack Slack/

p(#Cov.) Slack Slack/

p(#Cov.)

DEDHIQ -1.715 -1.137 -1.733 -1.155(0.783)⇤⇤ (0.518)⇤⇤ (0.779)⇤⇤ (0.518)⇤⇤

E Index -0.112 -0.0602 -0.112 -0.0627(0.173) (0.110) (0.175) (0.111)

DEDHIQ*EIndex 0.602 0.376 0.592 0.373(0.274)⇤⇤ (0.179)⇤⇤ (0.272)⇤⇤ (0.179)⇤⇤

ln(Net Worth) 0.675 0.566 0.689 0.567(0.273)⇤⇤ (0.181)⇤⇤⇤ (0.278)⇤⇤ (0.184)⇤⇤⇤

ln(Amount) -0.673 -0.480 -0.718 -0.485(0.221)⇤⇤⇤ (0.164)⇤⇤⇤ (0.240)⇤⇤⇤ (0.177)⇤⇤⇤

ln(Maturity) 0.635 0.342 0.707 0.378(0.313)⇤⇤ (0.212) (0.320)⇤⇤ (0.214)⇤

Secured 0.249 0.0545 0.234 0.0532(0.399) (0.238) (0.388) (0.233)

EBITDA/Assets 4.174 2.336 5.026 2.912(7.799) (4.972) (8.010) (5.108)

Leverage -1.546 -1.351 -1.421 -1.331(1.192) (0.798)⇤ (1.223) (0.811)

Book/Market 1.910 1.139 1.919 1.150(0.617)⇤⇤⇤ (0.385)⇤⇤⇤ (0.624)⇤⇤⇤ (0.388)⇤⇤⇤

Constant 1.413 1.860 2.026 1.927(5.344) (3.850) (5.211) (3.779)


This table presents OLS results with fixed e↵ects. Dependent variable in the first and third regressions is the amount ofcovenant slack divided by the standard deviation of the relevant metric in the eight quarters prior to loan origination.DEDHIQ is an indicator for whether the firm is in the highest quartile of dedicated institutional ownership. The depen-dent variable in the second and fourth regressions is the initial slack variable divided by the square root of the numberof covenants. Some variables, including all the fixed e↵ects, have been omitted for brevity. Heteroskedasticity-robuststandard errors are clustered by borrowing firm and are reported in parentheses. ***, **, and * denote significance atthe 1%, 5%, and 10% confidence levels, respectively. 26

Table 5: Results of Two-Stage Least Squares Regressions

(1) (2) (3) (4)Slack Slack/

p(#ofCov.) Slack Slack/

p(#ofCov.)

Lag. Share Active -6.426 -4.430 -6.357 -4.354(2.045)⇤⇤⇤ (1.337)⇤⇤⇤ (2.050)⇤⇤⇤ (1.339)⇤⇤⇤

ln(Net Worth) 1.026 0.683 1.023 0.681(0.182)⇤⇤⇤ (0.124)⇤⇤⇤ (0.180)⇤⇤⇤ (0.122)⇤⇤⇤

ln(Amount) -0.852 -0.584 -0.853 -0.585(0.158)⇤⇤⇤ (0.107)⇤⇤⇤ (0.159)⇤⇤⇤ (0.108)⇤⇤⇤

ln(Maturity) 0.650 0.305 0.650 0.304(0.196)⇤⇤⇤ (0.130)⇤⇤ (0.196)⇤⇤⇤ (0.129)⇤⇤

Secured -0.213 -0.180 -0.212 -0.179(0.238) (0.151) (0.238) (0.151)

EBITDA/Assets 4.474 2.246 4.453 2.222(3.302) (2.311) (3.321) (2.323)

Leverage -0.669 -0.613 -0.666 -0.609(0.724) (0.478) (0.724) (0.479)

Book/Market 0.522 0.296 0.524 0.298(0.284)⇤ (0.177)⇤ (0.278)⇤ (0.173)⇤

Constant -0.448 1.541 -0.399 1.597(3.267) (2.288) (3.270) (2.286)

Observations 1335 1335 1335 1335R2 0.124 0.173 0.125 0.174Year Fixed E↵ects Yes Yes Yes YesCredit Rating Fixed E↵ects Yes Yes Yes YesIndustry Fixed E↵ects Yes Yes Yes YesContract Purpose Fixed E↵ects Yes Yes Yes Yes

This table presents results from the second stage of two-stage least squares regressions. Dependent variable in the first andthird regressions is the amount of covenant slack divided by the standard deviation of the relevant metric in the eight quartersprior to loan origination. In the first two regressions active ownership is instrumented by membership in the S& P 500 and thelagged value of average daily turnover in the y�2 to y�1 window. The third and fourth regressions add the average non-zeroreturns in the y � 1 quarter as an additional instrument. The dependent variable in the second and fourth regressions is theinitial slack variable divided by the square root of the number of covenants. Some variables, including all the fixed e↵ects,have been omitted for brevity. Heteroskedasticity-robust standard errors are clustered by borrowing firm and are reported inparentheses. ***, **, and * denote significance at the 1%, 5%, and 10% confidence levels, respectively.

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