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Similarity in Bond Covenants*
Gus De Franco
Rotman School of Management, University of Toronto
105 St. George Street, Toronto, M5S 3E6, Canada
Florin P. Vasvari
London Business School
Regent’s Park, London, NW1 4SA, United Kingdom
Dushyantkumar Vyas
Department of Management – UTM & Rotman School of Management
University of Toronto
105 St. George Street, Toronto, M5S 3E6, Canada
Regina Wittenberg-Moerman
The University of Southern California
3660 Trousdale Parkway, Los Angeles, CA, USA
September, 2015
* We have benefited from the comments and suggestions of Phil Berger, Doug Diamond, Doug Skinner
and seminar participants at Bocconi University, HEC Paris, London Business School, Tel-Aviv
University, the University of Chicago, the University of Mannheim, the University of Miami, the
University of Minnesota, the University of Southern California and the University of Toronto. We
gratefully acknowledge the financial support of The Initiative on Global Markets at the University of
Chicago Booth School of Business, Rotman School of Management, the University of Toronto, Carlson
School of Management, University of Minnesota, the AXA Research Fund, and the Social Sciences and
Humanities Research Council of Canada. This paper was previously circulated under the title “Sticky
Covenants.”
Similarity in Bond Covenants
Abstract
We examine the economic consequences associated with the inclusion of covenants with
similar terms in bond contracts. Using a unique Moody’s dataset that provides credit
analysts’ views on the restrictiveness of covenant terms, we develop measures that
capture similarity in bond covenant terms by comparing the restrictiveness of a bond’s
covenants with the covenant restrictiveness of previously issued peer bonds. Consistent
with a similarity in covenants reducing contracting and comparability costs to
bondholders, we document that bonds with more similar covenant restrictiveness receive
significantly lower yields at issuance. These bonds are also characterized by greater
liquidity in the secondary market and are more likely to be held by long-term bond
investors, such as insurance companies. Our results highlight an important trade-off
between the contracting and comparability costs of changing the restrictiveness of bond
covenants and the monitoring benefits provided by a more tailored set of bond covenants.
JEL classifications: G12, G14, G32, M49
Keywords: Bond Covenants, Covenant Restrictiveness, Similarity, Primary
Bond Prices, Secondary Bond Liquidity.
1
1. Introduction
Bondholders demand mainly event risk covenants (or “incurrence-based” covenants) that
restrict aggressive investments, asset sales, additional borrowings, excessive payments of
dividends, stock repurchases or distributions to junior debtholders. Although the terms of these
covenants display a high degree of similarity relative to previously issued bonds, as the corporate
law literature highlights (e.g., Kahan and Klausner 1993; Bratton 2006; Choi and Triantis 2012),
the economic determinants and consequences of this similarity have not been explored. Because
covenants are one of the primary contractual mechanisms employed by bond holders to protect
their wealth, in this paper we examine similarity in the restrictiveness (strength) of covenant
terms.
We hypothesize that bondholders will prefer the restrictiveness of a bond’s covenants to
be similar to that of previously issued peer bonds to avoid the significant costs associated with
modifying covenant specifications. One important set of such costs is the contracting cost, which
is caused by the need to spend more time and effort assessing how the amended covenants
protect bondholders’ wealth (e.g., Kahan and Klausner 1993, 1997; Bratton 2006; Wood 2011;
Choi and Triantis 2012). This cost is also the result of the greater litigation risk that arises from
new covenant restrictiveness terms. Because the diffused ownership of bond securities leads to
high contract renegotiation costs when covenants are breached, bondholders typically prefer
restrictiveness terms that have been previously interpreted, scrutinized and enforced by the
courts (Choi and Triantis 2012). Further, less similar (i.e., more unique) covenant terms lead to
higher comparability costs. In contrast to commonly used restrictiveness terms, new terms cannot
be benchmarked to the terms of previously issued bonds, leading to a loss of comparability. Less
comparability relative to other bonds in the market increases the information processing costs for
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bond investors as they need to exert more effort to evaluate the extent to which new covenant
specifications protect against credit risk and affect bond pricing (Kahan and Klausner, 1997).
Nonetheless, while similar bond covenants may provide savings with respect to
contractual and comparability costs, they could also increase bondholders’ risk by being less
effective in monitoring idiosyncratic agency problems specific to a particular borrower.
Consequently, because bond covenants protect against firm managers’ opportunistic actions on
behalf of shareholders, bond investors may prefer less similar (or more tailored) covenant
structures. We thus examine whether more similar covenant restrictiveness terms in new bond
contracts provide net benefits or costs to bondholders, as reflected in the bonds’ issuance yields.
In our tests, we employ a measure of covenant restrictiveness developed by Moody’s that
is available through the Moody’s Covenant Assessment database. Moody’s credit analysts
summarize the principal strengths and structural gaps in the protection provided by individual
bond covenants based on a detailed analysis of the covenants’ specifications. The typical
specification of each bond covenant begins with a prohibitory section that establishes the scope
of the restrictions. This section is followed by a provision, labeled proviso, which allows for an
exception to the restrictions in the prohibitory section, usually subject to conditions such as a
financial ratio test. The last section in the covenant specification presents the carve-outs, which
are additional exceptions to the prohibitory paragraph that are not required to satisfy the
proviso’s conditions. The proviso and the carve-out terms may significantly dilute a covenant’s
ability to protect bondholders. Each term used in the bond contract section that describes the
covenants, including the financial accounting terms and the ratios used, has an extensive
definition in a glossary, which varies across issues and sometimes across different covenants in
the same issue. Moody’s analysts use their market experience to assess a bond covenant’s
3
restrictiveness based on the comprehensiveness of the restrictions in the prohibitory section, the
strictness of contractual terms’ definitions (e.g., whether the financial ratio definitions provide
scope for managerial discretion), the flexibility in the financial ratios in the proviso section, and
the extent to which covenants provide both qualitative and quantitative carve-outs.
To measure covenant similarity, we compare the restrictiveness of a bond’s covenants, as
assessed by Moody’s analysts, to the restrictiveness of the respective covenants of bonds issued
by peer firms in the last 12 months. Because this restrictiveness measure captures the strength of
protection provided by each individual covenant, variation in this measure allows us to more
precisely capture the similarity in covenant restrictiveness than would a comparison between the
existence of a covenant in a bond contract and the existence of a covenant in a peer firm’s bond.
A firm is considered a peer if it is in the same sector and has similar credit risk (i.e., investment
or speculative grade rating category) as the firm under consideration. Our sample consists of 996
bonds for which we can estimate the relative similarity of bond covenant restrictiveness using the
Moody’s database. These bonds are issued by U.S. firms over the period from 2000 to 2009.
We start by investigating the determinants of similarity in bond covenants’
restrictiveness. We document that when a firm uses the same legal counsel as its peer companies,
covenant similarity is greater. In terms of economic significance, two bonds that are issued by
the same legal counsel have covenant similarity scores that are greater by approximately a one-
third standard deviation than the covenant similarity scores across two bonds that do not share
legal counsel. This result supports arguments in the corporate law literature that debt market
intermediaries contribute to the standardization and rigidity of debt contractual terms (Kahan and
Klausner 1993, 1997; Choi and Triantis 2012). We test but do not find evidence that covenant
similarity is greater if firms share the same underwriter with their peers, suggesting that
4
underwriters exhibit greater flexibility in adapting to new covenant terms relative to legal
advisers. We also find that firms with more comparable characteristics, such as size and
tangibility, have more similar covenants, consistent with the notion that firms with more similar
agency problems have more similar covenant structures.
In our primary analyses, we find that similarity in covenant restrictiveness is associated
with significantly lower bond yields at issuance. A one-standard-deviation increase in the
similarity of bond covenants’ restrictiveness to that of peer bonds is associated with a reduction
in bond spreads of 0.12% (or 5.7% of the mean spread in our sample). Given the average
principal value and maturity of our sample bonds, this effect translates into approximately $4
million in interest savings over the life of the bond issue. The negative association between
covenant similarity and bond yields at issuance is robust to the use of an instrumental variable
approach that accounts for the potential endogeneity of covenant terms with respect to bond
yields. Our findings suggest that, ceteris paribus, bond investors view positively covenant
restrictiveness terms that are more similar to the terms in previously issued bonds, as such terms
potentially contribute to lower contracting costs. Similar covenant restrictiveness terms also
increase comparability across different bonds, lowering the information processing costs for
bond investors. We also provide evidence that the similarity across the most elaborate and
complex covenants in the bond contracts — the covenants restricting payments to shareholders,
borrowings, and transactions involving the firm’s assets — is driving the bond yield results.
These covenant specific results provide additional support for the conclusion that the contracting
and comparability costs of changing bond covenant restrictiveness terms potentially exceed the
credit risk protection benefits provided by a more tailored set of bond covenants.
In supplementary tests that aim to better understand how similarity in covenant terms
5
affects bond yields, we investigate whether insurance companies, the largest bond investors in
the market, are more likely to own bonds with similar covenant restrictiveness. If a bond is
preferred by insurance companies, we expect this increased demand to lower its pricing. A
typical insurance company invests in a large number of bonds, usually holds them until maturity
with limited portfolio rebalancing and incurs capital penalties from regulators if the bonds
subsequently underperform. Therefore, it is likely to prefer bonds whose terms, along with the
expected level of credit protection, are comparable and involve predictable litigation risks.
Consistent with this conjecture, we find that bonds with more similar covenant restrictiveness
terms are characterized by a higher level of insurance company ownership in the quarter
following the bond’s issuance. In terms of economic significance, a one-standard-deviation
increase in similarity increases the share of the bonds absorbed by insurance companies by
2.96% (or 5.5% of the sample average of 53.9%). This finding reinforces the idea that covenant
similarity decreases the contracting and comparability costs incurred by bond investors.
We next investigate whether similarity in covenants’ restrictiveness terms is associated
with greater bond liquidity in the secondary market during the period immediately following a
bond’s issuance. We expect higher secondary market liquidity to provide a further partial
explanation for lower bond yields because investors demand illiquidity premiums when pricing
bonds (e.g., Chen, Lesmond and Wei 2006; Mahanti et al. 2008). We document that bonds with
more similar covenant restrictiveness relative to peers are indeed traded more often and to a
greater extent. In terms of economic significance, a one-standard-deviation increase in the
similarity of covenant restrictiveness is associated with a 6% increase in the mean bond trading
volume and a 19% increase in the mean number of transactions in our sample. Like the insurance
holdings results above, these bond trading results are consistent with the notion that covenant
6
similarity decreases investors’ information processing costs in the secondary bond market.
In the final set of supplementary analyses, we develop a time-series-based measure of
similarity in covenant restrictiveness by comparing the restrictiveness of a bond’s covenants with
that in bonds previously issued by the same firm. The economic trade-offs we investigate using
our main similarity measure—reducing contracting and comparability costs versus receiving less
customized credit protection—are also valid for time-series covenant similarity. Our ‘time-
series-based’ sample consists of 845 bonds for which we can estimate the similarity relative to
previous bond issues. We replicate our main determinants and yield tests using this time-series-
based measure and find robust results, strengthening the inferences from our main findings.
Our study contributes to the literature on covenant structure in debt contracts across
several dimensions. First, the extant prior literature has explored covenant structure primarily by
investigating the determinants of specific covenants and the number of covenants included in
debt agreements or the tightness of covenants in private loan contracts (e.g., Dichev and Skinner,
2002; Bradley and Roberts, 2004; Christensen and Nikolaev 2012; Chava and Roberts, 2008;
Drucker and Puri, 2009; Demerjian, 2011; Chava, Kumar and Warga 2010; Murfin 2012; Li et
al. 2015). Our study differs from and complements this other work by focusing on the important
role of a novel covenant characteristic, the similarity in covenant restrictiveness across different
bond issues. In particular, we find that similarity in covenant restrictiveness brings significant
economic benefits to the issuing firms, such as lower bond yields, greater secondary bond market
liquidity and greater interest from long-term investors such as insurance companies. The analysis
of insurance companies’ bond ownership is relatively unique given that there is very limited
evidence on how bond contract characteristics affect the investor base of bond securities at the
time of their issuance.
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Second, the prior literature motivates bond covenants primarily from the agency theory
perspective (e.g., Jensen and Meckling 1976; Myers 1977; Smith and Warner 1979; Masulis
1980; Dichev and Skinner 2002). To the best of our knowledge, our paper is the first to focus on
non-agency-based explanations for bond covenant structure (i.e., the contracting and
comparability costs associated with changes in covenant structure).1 More specifically, we
provide new evidence that emphasizes the importance of the economic trade-off between the
costs of changing the restrictiveness of bond covenants due to contracting and comparability and
the benefits arising from the higher credit protection provided by a tailored covenant structure.
Our findings that the costs associated with modifying covenant structures may outweigh the
benefits of a more tailored covenant structure suggest that the costs of modifying covenants may
be substantially larger than what the prior literature presumes.
Last, to the best of our knowledge, our study is also the first to describe the detailed
specification of bond covenants and to consider the strictness and comprehensiveness of
covenant terms when measuring the strength of bond covenants’ protection. Prior studies focused
on the inclusion of individual covenants in bond contracts or indices that count the number of
bond covenants (Malitz 1986; Begley 1994; Kahan and Yermack 1998; Nash, Netter and Poulsen
2003; Billett, King and Mauer 2007; Chava, Kumar and Warga 2010). Although prior literature
has advanced in exploring the specific terms of covenant structure in private loan agreements
(e.g., Beatty et al. 2008; Li 2012; Li et al. 2015), there is little evidence on how covenants are
structured in public bond indentures. We document the multifaceted structure of bond covenants
and highlight that the inclusion of individual covenants or the covenant count measures
1 Although the incomplete contracting theory provides additional explanations for the determinants of covenant
structure (e.g., Grossman and Hart 1986; Hart and Moore 1988; Aghion and Bolton 1992), it relates primarily to the
financial covenants used in private debt agreements (e.g., Christensen et al. 2015).
8
employed by prior studies may not appropriately capture the strength of bond covenants’
protection, given that covenants may include a weak prohibitory section or allow significant
exceptions to the restrictions they impose.
The next section develops our research question and reviews the related literature.
Section 3 describes our data and the measurement of covenant similarity. Section 4 presents an
analysis of the determinants of covenant similarity. It also discusses our primary tests and the
results of the consequences of covenant similarity in terms of yield spreads. Section 5 provides a
supplementary analysis of the additional consequences—secondary market liquidity and
insurance companies’ holdings—of covenant similarity. Our analysis using the time-series-based
measure of covenant similarity is in Section 6. Section 7 concludes.
2. Background and Hypotheses Development
2.1. Background on Bond Covenants
A bond’s covenant package is the primary contractual instrument available to
bondholders for protecting the value of their investment in the borrowing firm. The presence of
covenants mitigates the conflicts of interest between bondholders and equity holders by
preventing excessively risky activities, limiting cash flow diversions to equity holders and
preserving the relative priority of debtholders’ claims (e.g., Jensen and Meckling 1976; Myers
1977; Smith and Warner 1979; Aghion and Bolton 1992; Haugen and Senbet 1988). While
covenants provide credit protection benefits to bondholders, they also need to be flexible enough
to allow borrowers to efficiently run their financial, investment and operational activities during
the term of the bond. If bond covenants are not sufficiently flexible, they are likely to be violated
even if the borrower is financially healthy, leading to significant losses for bondholders.2
2 For instance, Grossman et al. (1997) find that the recovery rates on subordinated bonds that default is around 40%.
The low bond recovery rates in liquidation proceedings are mainly due to the presence of senior bank claims.
9
Bond issuances typically involve a large number of investors with limited incentives to
monitor the borrower on a continuous basis (Diamond 1984; Ramakrishnan and Thakor 1984).
The dispersion of these investors leads to high coordination costs and free riding incentives that
make renegotiations with borrowers in default extremely difficult and costly (Gertner and
Scharfstein 1991; Bolton and Scharfstein 1996). Consequently, bond investors prefer to use
relatively easy-to-monitor “incurrence-based” covenants that restrict specific investment and
financing activities of the bond issuers (e.g., restrictions on issuing more debt, distributing cash
to shareholders, selling assets, engaging in mergers and acquisitions, lending to subsidiaries).
Issuers only have to comply with these covenants if they proactively intend to take an action that
might break them. In contrast to bank lenders, bondholders do not typically include
“maintenance” (financial) covenants, which require the issuer to comply with specified financial
ratios on a regular basis.3 While these covenants could provide “early warning signals” about
credit risk changes, if they are breached when the issuer’s financial condition is not significantly
worsening, bondholders will find it costly to agree, on short notice, to covenant renegotiations.4
Bond contracts include three major groups of “incurrence-based” covenants that control
conflicts of interest between bondholders and equity holders. The first group restricts cash
distributions to shareholders via dividend payments or share repurchases. These covenants limit
outright expropriation as cash disbursements leave fewer assets to protect bondholders’ claims.
Retained cash can instead be made available to service the debt.5 The second group of covenants
3 Covenant packages in loan agreements include both maintenance and incurrence-based covenants. The relatively
small number of lenders in bank syndicates, high individual bank exposure, and the fact that these lenders operate
under reputational constraints, facilitate renegotiations of the loan agreements. Thus, bank lenders set maintenance
covenants tightly, triggering violations that allow ongoing loan renegotiations (Dichev and Skinner 2002; Chava and
Roberts 2008; Roberts and Sufi 2009; Nini, Smith and Sufi 2009, 2012; Roberts 2014). 4Although bondholders are represented by a trustee, its role is largely administrative. The bond trustee does not have
a fiduciary duty and cannot materially renegotiate a bond indenture on behalf of the bondholders. 5 These covenants can also help to resolve the managers’ incentives to under invest in growth opportunities (Myers
1977; Kalay 1982).
10
places limits on additional borrowing and the issuance of certain types of debt (e.g., secured or
senior debt). These covenants prevent an increase in default risk, which is associated with higher
leverage, ensuring that borrowers have the capacity to service their current debt obligations and
limit the dilution of bondholders’ claims generated by the issuance of debt that is equal to or
more senior than the bond. The third group restricts borrowers’ investment/divestment activities,
ranging from prohibitions on certain types of transactions, such as mergers, acquisitions or
sale/leasebacks, to restrictions on the disposition of assets, particularly at prices less than their
equivalent value. These covenants are designed to protect bondholders from transactions that
substitute less risky assets for riskier ones (Jensen and Meckling 1976; Galai and Masulis 1976).6
Covenants that restrict investments also mitigate shareholders’ incentives to overinvest in
negative present value projects instead of paying down the debt.
All bond covenants discussed above are “negative” covenants because they prohibit the
issuer from certain actions.7 The specification of each negative covenant in the bond contract
almost always begins with a prohibitory section that establishes the scope of the restrictions. For
example, the covenant might state that the issuer will not incur any additional indebtedness. The
prohibitory paragraph is typically followed by a provision section, labeled proviso, which allows
for an exception to the restriction in the prohibitory paragraph if certain conditions are met, such
as passing a financial ratio test. Continuing the previous example, the proviso could state that the
issuer can incur additional indebtedness if the consolidated fixed charge coverage ratio (CFCCR)
computed after the additional debt is taken remains above a specific threshold, such as 2:1. The
6 Some of these transactions often compound the risk by using excessive leverage to finance the purchase of risky
assets. For example, Asquith and Wizman (1990) and Warga and Welch (1993) provide evidence concerning the
negative effects on bondholder wealth that occurred during the leveraged buyout wave of the 1980s. 7 One covenant exception that requires affirmative action is the requirement for periodic financial reports. This
requirement ensures a steady flow of readily accessible information to current and prospective bondholders and is
present in almost all bonds in our sample.
11
last section in the specification of the bond covenant presents a set of carve-outs, which are
exceptions to the prohibitory paragraph in addition to the financial ratio exception set out in the
proviso. For instance, a typical carve-out for the covenant above is to allow the firm to issue
bank debt. Another common carve-out is to allow the firm to issue public debt with a face value
that is lower than a certain percentage of its consolidated tangible assets. The proviso and the
carve-outs have the potential to significantly dilute a covenant’s ability to protect bondholders
from wealth expropriation by equity holders or lenders with more senior claims to bondholders.
The descriptions of bond covenants’ terms and conditions in the bond contract are
extensive and, based on our reading of bond indentures, often span more than 20 pages. We
measure the restrictiveness of the covenants’ terms by relying on the views of Moody’s credit
analysts. Moody’s analysts critically review covenants’ terms and summarize the principal
protections and structural gaps of each individual covenant in a bond contract (Moody’s 2010).
For instance, to gauge the level of protection offered by a covenant that limits additional debt
issuance for a particular bond issue, Moody’s analysts evaluate a variety of qualitative and
quantitative factors, such as current credit market conditions, the financial condition of the
borrower and the actual specification of the covenant’s terms.
When assessing the terms of a covenant that sets limits on additional borrowings,
Moody’s analysts first pay attention to the definition of the financial ratios in the proviso. As
such, they negatively view covenants whose EBITDA definition allows add-backs of non-cash
charges and other items that give management the discretion to adjust the ratio in order to issue
more debt. For example, the assessment of the quality of the debt incurrence covenant in the
bond indenture of Atlas Pipeline Partners from February 2009 emphasizes that “certain
undefined terms such as ‘non-recurring items’ and ‘non-cash items’ give discretion to the issuer
12
in determining the presumptive cash flow under the covenant.”
Second, Moody’s analysts consider the headroom of the financial ratio in the proviso (the
difference between the ratio’s threshold and the ratio at the time of bond issuance). Third,
Moody’s analysts evaluate whether the carve-outs attached to the covenant are limited or
extensive. As examples, we summarize the headroom estimation and carve-out assessments for
the additional borrowing restriction covenant in the bond indentures of Meritage Homes
Corporation from October 2008 and K. Hovnanian Enterprises, Inc., from October 2007.
Appendix A provides the detailed calculations. Meritage Homes Corporation’s indenture
specifies that only one of the two financial ratios in the proviso section, either the CFCCR or the
consolidated net worth ratio, needs to be met. Under the first ratio test, the headroom is negative,
as the CFCCR of 0.52 at the time of bond issuance is below the ratio’s threshold of 2. This
negative headroom indicates that the firm cannot issue additional debt under the CFCCR test.
However, the consolidated net worth ratio test reveals sizeable positive headroom that allows
Meritage Homes Corporation substantial flexibility in issuing additional debt. Moody’s analysts
indicate that this flexibility significantly reduces the protection that the debt incurrence covenant
provides to bondholders. In contrast, for the Hovnanian Enterprises, Inc.’s indenture, there is
only one financial ratio test, CFCCR, which is set relatively tight (i.e., the headroom is relatively
low). Thus, the protection provided by the debt incurrence covenant is substantially enhanced.
The carve-outs of the Meritage Homes Corporation’s indenture are extensive and allow
the company to issue an additional $505.7M of debt (relative to consolidated total assets of
$1,619.8M), while still meeting the CFCCR or the consolidated net worth ratio tests in the
proviso section. For K. Hovnanian Enterprises, Inc., the carve-out allows the issuance of only
$60M of additional debt (relative to consolidated total assets of $5,363M), while still meeting the
13
CFCCR test, which further contributes to the strength of the covenant.
The measurement of covenant restrictiveness in public debt contracts and the extent to
which certain levels of covenant restrictiveness are common across firms have not yet received
any attention in the literature, mainly because of the difficulty in assessing the terms of
incurrence-based bond covenants. Prior empirical work has measured covenant restrictiveness by
relying on the total number of covenants or the presence of specific individual covenants (Billett,
King and Mauer 2007; Chava, Kumar and Warga 2010). However, an index that counts the
number of covenants or the presence of a covenant cannot fully capture the true level of the
covenant protection provided to bond investors. As illustrated above, bond contracts may include
poorly specified covenants (e.g., covenants with loose financial ratio definitions) or those with
substantial exceptions that render them ineffective. Hence, an evaluation of the covenant
restrictiveness and the comparative analysis of covenant structures across different bonds and
over time require a detailed examination of the covenants’ specifications.8
2.2. Consequences of Bond Covenants’ Similarity
We argue that bondholders will prefer bonds with covenant restrictiveness terms that are
similar to the restrictiveness terms of other bonds that were previously issued by a borrower’s
peers because more unique covenants could lead to higher costs of contracting and
comparability. The corporate law literature contends that parties involved in bond issuance
contribute to the rigidity of bond contractual terms because they incur high costs when
modifying these terms (e.g., Kahan and Klausner 1993, 1997; Bratton 2006; Wood 2011; Choi
8 A number of studies examine the covenant restrictiveness of syndicated loans by assessing the slack in financial
covenants (Dichev and Skinner 2002; Beatty and Weber 2006; Chava and Roberts 2008; Drucker and Puri 2009;
Demiroglu and James 2010; Murfin 2012). However, the slack can only be estimated with significant measurement
error due to the fact that lenders often make substantial adjustments to GAAP numbers when defining covenant
thresholds (Leftwich 1983; Dichev and Skinner 2002; Beatty et al. 2008; Li 2012). These adjustments also vary
across both different covenants in the same loan contract and different loan contracts. Further complicating the slack
estimation, financial covenant thresholds frequently change over the life of the loan (Li, Vasvari and Wittenberg-
Moerman 2015).
14
and Triantis 2012). Changes in bonds’ terms relative to terms that are widely used are likely to
involve additional time and effort because bondholders, especially those that have experience
with prior bonds, will need to understand and assess the implications of these adjustments.
An additional contracting cost of deviating from commonly used covenant restrictiveness
terms is the higher expected cost of litigating future disputes. Bond investors might be reluctant
to risk investing in bonds whose terms depart from contractual provisions that have been
previously interpreted, scrutinized and enforced by the courts (Choi and Triantis 2012).9 Judicial
opinions on prior commonly used covenants reduce uncertainty regarding the validity and
meaning of their covenant restrictiveness terms and the interaction of these terms with relevant
requirements in corporate, securities, and bankruptcy laws. This concern is particularly important
to bond investors, given that the diffused ownership of a bond security leads to high bond
contract renegotiation costs when covenants are breached.
In addition to inducing higher contracting costs, covenant restrictiveness terms that deviate
from common covenant specifications may significantly limit bond investors’ ability to compare
different bond securities. Kahan and Klausner (1997) argue that, by facilitating comparisons with
other bond issues, the use of common contractual terms reduces both the information collection
and processing costs that investors incur when evaluating a firm’s bond indentures. More
generally, studies such as De Franco, Kothari, and Verdi (2011) argue that the availability of
comparable information lowers the cost of acquiring information and increases the overall
quantity and quality of available information. Better comparable information allows investors to
exert less time and effort. In the primary bond market, familiar covenant terms in the bond
offering prospectus are likely to allow bond investors to quickly assess the risks relative to other
9 For example, in a series of cases, courts have clarified how an indenture clause should be worded in order to
subordinate the claims of junior creditors to unsecured senior creditors' claims for interest accrued after a bankruptcy
petition is filed (Kahan and Klausner 1997).
15
bond investments and decide whether and how much to invest in a new bond issue. In the
secondary market, for similar reasons, we expect these information processing efficiencies to
increase bond liquidity.10
Common covenant restrictiveness terms also facilitate more reliable
and comparable credit ratings across different bond issues since rating agencies use standardized
credit models that may fail to capture significant deviations in covenants’ terms (e.g., Benmelech
and Dlugosz 2009; Bozanic, Loumioti and Vasvari 2015). As a result, the ratings will provide
more relevant information to bond investors making investment decisions when covenant
restrictiveness terms are in line with previous bond issues.
We hypothesize that if bondholders save on these contracting and comparability costs when
the covenant restrictiveness terms of a new bond issue are more similar to those of the previous
bonds, then these cost savings will be reflected, at least partially, in lower bond yields. Our
prediction is motivated by the fact that more bond investors are likely to be attracted to bonds
with familiar terms. The competition generated by this larger set of investors increases the
demand for these bonds and lowers their pricing.
We note, however, that our empirical prediction regarding the impact of covenant
similarity on bond yields is not straightforward. To more effectively deal with borrower specific
agency problems, bond investors might prefer that a new bond issue include covenants tailored
to the borrower’s financial and operating condition. Such covenant terms may bring substantial
benefits to bondholders that offset the higher contracting costs of modifying covenant
specifications and the larger information collection costs triggered by the lower comparability of
tailored covenants. For instance, if the firm is operating in a volatile environment, a more
idiosyncratic covenant package can help preserve operating flexibility and avoid inefficient and
10
As another example, Benmelech and Dlugosz (2009) study the collateralized loan obligation (CLO) market and
observe significant uniformity in CLO structures, as investors demand. They suggest that uniformity reduces the
amount of time investors must spend analyzing new deals.
16
bond-value-destroying defaults. Similarly, if the firm’s financial condition contributes to a more
pronounced debt-equity-holder conflict of interest, a set of customized covenants terms that
deviate from the covenant terms used in the prior bonds of firms that do not face similar conflicts
is likely to be more effective in protecting bond investors’ interests. In sum, these arguments
suggest that more similar covenant restrictiveness terms could lead to higher bond yields if
bondholders are concerned that similar covenants may not provide effective protection against
firm specific agency problems.
3. Measurement of Similarity in Covenant Restrictiveness
In this section, we discuss how we measure the restrictiveness of covenant terms and how
we validate this measurement process. We then describe our measure of similarity in covenant
restrictiveness, our primary variable of interest.
3.1. Covenant Restrictiveness
We capture the restrictiveness of bond covenants using a novel dataset of individual bond
covenants’ assessments by Moody’s covenant analysts. Moody’s Covenant Quality Assessment
(CQA) service evaluates the covenant restrictiveness of each new bond issue, with the aim of
helping institutional investors make better investment decisions. Moody’s covenant analysts
assess eight key bond covenants that fit into the three covenant groups we discussed in Section
2.1. In the group that restricts distributions to shareholders, Moody’s includes restrictions on
payments to shareholders and other parties (Restricted Payments). In the group that limits
additional borrowing and the issuance of certain types of debt, Moody’s includes: restrictions on
debt issuance, reclassifications or retirement through asset sales (Debt Incurrence), restrictions
on debt issuance, reclassifications or retirement by any subsidiaries (Subsidiary Debt Incurrence)
and restrictions on the issuances of pledges to secure other subordinated debt (Liens). Finally, in
17
the group that restricts risky investment activities, Moody’s includes: restrictions on the sale of
assets (Asset Sales), restrictions on sale and leaseback transactions (Sale/Leaseback), restrictions
on mergers or asset conveyance (Mergers) and restrictions on changes in the ownership of the
issuer (Change of Control). In Appendix B, we define these covenants and provide a discussion
of how Moody’s assesses the quality of each. Depending on the level of protection provided, the
Moody’s CQA individual covenant scores receive values of 0 (does not exist), 1 (minimal
protection), 2 (moderate protection), or 3 (strong protection).
Since the measurement of covenant restrictiveness for bond contracts is a complex
exercise and involves subjective judgments, it is important to establish the validity of Moody’s
CQA scores.11
First, to help establish internal validity, in untabulated analyses we document a
strong correlation between carve-outs (an objective numerical measure) and CQA scores for a
subsample of covenants assessed by Moody’s for which we have both covenant quality scores
and quantitative information on carve-outs (i.e., the ratio of the carve-out amounts to total
assets). This test is conducted at both the individual covenant level and a combined level across
the three covenants in which there are significant carve-outs. The pairwise Pearson correlation
coefficients between the CQA scores and carve-outs for payment restrictions, debt restrictions,
investment restrictions, and at the combined level are -0.39, -0.58, -0.33 and -0.49, respectively
(all are significant at the 1% level). This negative correlation indicates that, as expected, greater
carve-out amounts lead to weaker covenant protection scores.
Second, to help establish external validity, in untabulated analyses we compare Moody’s
CQA scores to similar covenant quality scores provided by Xtract Research LLC, who also
11
Moody’s initiated the CQA database in 2006. Moody’s evaluated the covenant restrictiveness of bond securities
issued prior to 2006 and still outstanding as well as of those issued after 2006. Because the majority of bonds in our
research sample are issued prior to the initiation of CQA, it is unlikely that the covenant restrictiveness terms are set
in order to meet Moody’s covenant strictness standards.
18
assess covenant quality for speculative grade bonds. We match 328 bonds from these two
datasets and observe a strong positive correlation between the covenant quality assessments
provided by these two independent firms. As Xtract has only two categories, weak and normal,
we convert our Moody’s CQA scores to a binary score, using the median value of Covenant
Restrictiveness by rating category. We find that the scores of Moody’s and Xtract correspond to
each other in 79.6 % of cases (i.e., either both scores are weak or both scores are normal).
Finally, we establish additional construct validity by regressing Covenant Restrictiveness
on firm characteristics that prior research suggests are associated with debt covenants (e.g.,
Costello and Wittenberg-Moerman 2011; Christensen and Nikolaev 2012). Not surprisingly, we
find that covenant restrictiveness increases with firm credit riskiness: firm size and asset
tangibility are negatively related to covenant restrictiveness, while financial leverage is
positively related to covenant restrictiveness (untabulated). Further imparting construct validity
to the measure, we observe that covenant restrictiveness is lower (higher) for bonds that are rated
in the investment grade (high yield) category.
3.2. Measurement of Covenant Similarity
To measure the similarity of covenant restrictiveness, we compare the restrictiveness of a
firm’s bond covenants to the restrictiveness of a peer firm’s bond covenants. Relative to the
simple comparison of the existence of a covenant for a firm’s bond with the existence of a
covenant for its peer firm’s bonds, our approach of comparing covenant restrictiveness, a more
granular measure of covenant strength, should better capture the underlying construct of
similarity in covenant terms.
We develop the variable Covenant Similarity as follows. The measure is computed for
each firm i – peer j pair of bonds. A bond issue is included as a peer if it was issued over the past
19
12 months by a firm in the same sector and the same rating category (i.e., investment grade or
high yield) as those of the firm. The choice of peer is based on the idea that firms with similar
economic characteristics should have similar covenant structures. Bonds with no peer issues are
excluded from the analysis. For each of the eight covenants in the database, we take the absolute
difference of firm i’s and peer j’s bond covenant scores. For example, if both firm i’s bond and
its peer’s bond have identical covenant scores, the absolute difference is 0. If the firm’s bond has
a covenant score of 3 and the peer’s bond score is 1 (or vice versa) then the absolute difference is
2. This difference is calculated for each of the eight covenants and then the eight differences are
added up to create an aggregate absolute difference. This implicitly weights each covenant
difference equally. Last, we multiply the aggregated difference by -1, so that higher values
represent greater covenant similarity. To create a single firm i-level covenant similarity measure,
we take the mean of the scores across the firm i's – peer j's bonds for all peer issues of firm i.
This firm i-level variable, Covenant Similarity, is the primary measure used in our analysis of the
determinants of covenant similarity as well as the effects of covenant similarity on bond spreads.
The Moody’s CQA database covers 3,075 bonds issued during the 2000 – 2009 period.
After conditioning the sample on bonds issued by U.S. borrowers and those that require the
availability of the bond- and firm-level control variables used in our tests, we obtain an
underlying sample of 1,727 bond issues. Using these bond issues, we create the Covenant
Similarity values for a sample of 943 bond i observations for which we can obtain a peer that
meets the criteria discussed above. Table 1 summarizes the sample selection process.
4. Main Results
4.1. Descriptive Statistics
We provide descriptive statistics for the main variables used in our tests in Table 2. Panel
20
A presents our similarity-based variables at the bond i level. The overall covenant similarity
score indicates an on-average dissimilarity of 0.36 per covenant (= -2.842 total/8 covenants) for a
bond and its cross-sectional peers. In other words, the average dissimilarity per covenant is
approximately 1/10th
of the theoretical maximum possible dissimilarity of 3 (i.e., an extreme
situation where a bond has been assigned a covenant restrictiveness of 3 by Moody’s, whereas its
peers have been assigned a score of zero, or vice versa). We also notice that, on average, 12%
and 15% of the bonds are issued by the same legal counsel and underwriter, respectively. Panel
B presents the results of the firm and bond characteristics at the bond i level. The average bond
issue has about five covenants, a maturity of 13 years, and an offering amount of $587 million.
The average yield spread is 2.2%. Sample firms have a mean leverage ratio of 28% and
tangibility ratio of 74%.
In Panel C, we investigate the similarity in each individual covenant to determine which
covenants explain the overall covenant similarity score to a greater extent. The panel presents the
distribution of covenant similarity scores, which range from 0 to 3. For example, in the first row,
for covenant similarity calculated versus peer j’s bonds, in 11% of observations the covenant
restrictiveness is the same as the firm’s peers across all eight covenants. Concentrating on the
individual covenants, we notice that leaseback, change of control covenants, and liens are
relatively more dissimilar compared with the other covenants. For instance, in 30% of
observations the leaseback covenant restrictiveness is identical to that of its peers. In contrast, for
asset sales, mergers, payment, and debt restrictions, in over 80% of observations the firm’s
covenant restrictiveness is identical to that of its peers. The fact that a large proportion of the
covenants have the same level of restrictiveness as the covenants of previously issued bonds is
consistent with the ideas of debt contract rigidity (e.g., Bratton 2006; Kahan and Klausner 1993).
21
4.2. Determinants of Similarity in Covenant Restrictiveness
4.2.1. Tests. We start our analysis by examining the determinants of the covenant
restrictiveness similarity with respect to firm’s peers. Changes of covenant terms from prior bond
issues require legal advisors to spend more time reviewing, discussing and approving the new
terms. Given the institutional features of the legal profession such as hourly billing, additional
legal time translates into higher legal fees for the borrowing firms. Underwriters should also
prefer to have similar terms, all else equal. For example, if an underwriter needs to place a bond
issue with covenant restrictiveness terms that are different from those used in previously issued
bonds, the underwriter would need to spend additional time drafting the new covenants and
explaining them to investors. Given that legal counsels and underwriters would incur additional
costs for writing the debt contract if they were to draft different covenant terms for a new bond,
we expect that covenant restrictiveness similarity will be higher if a bond and its peers share the
same legal counsel or underwriter. We also expect that covenants’ restrictiveness will be more
similar when bond issuers face similar agency problems (i.e., the borrower and the peers have
similar characteristics). To investigate these predictions, we estimate the following regression:
Covenant Similarity = 0 +1 Similar Legal Counsel +2 Similar Underwriter
+ 3 Similar Firm Characteristics + 4 Firm Characteristics
+ 5 Bond Characteristics + 6 Lender Power + .
(1)
The first two independent variables capture the effect of external advisers on the
similarity in covenant restrictiveness. Similar Legal Counsel is first measured at the bond i-peer j
level. It is an indicator variable that captures whether the firm’s bond and its peers’ bonds are
advised by the same legal counsel, zero otherwise. To create the firm i-level variable, we take the
mean of the scores across the firm i-peer j bonds for all peers of firm i. The variable Similar
Underwriter is created analogously. We first assign it the value one at the bond i-peer j level if
22
the bonds share the same lead underwriter, and then we take the mean of these indicator
variables to calculate our firm i-level value. A positive coefficient on either variable is consistent
with corporate law literature predictions that debt market intermediaries contribute to the
standardization and rigidity of debt contractual terms (Kahan and Klausner 1993, 1997; Choi and
Triantis 2012).
As indicated above, covenant similarity is likely to be driven by the similarity of firms’
characteristics. Although we choose peers based on similar economic fundamentals (same sector
and same rating category and close in time to the bond issue), we further control for economic
similarity not captured by our choice of peers along the dimensions of firm size, tangibility,
leverage, and interest coverage. These differences are calculated between each firm i-peer j pair
of companies, and then we take the mean of these absolute differences and multiply by -1, so that
these measures capture similarity in firm fundamentals. We expect all these similarity variables
to obtain a positive coefficient, consistent with more similarity across firm characteristics being
positively associated with a higher similarity in covenant restrictiveness.
We also control for firm and bond characteristics associated with a borrower’s credit
riskiness and agency cost of debt. These variables are measured simply at the firm or bond level
and as such we do not have specific predictions for their coefficients, given that our variable of
interest is the similarity in covenant restrictiveness. (Untabulated analyses indicate that our
results are not sensitive to their exclusion.) Firm Characteristics include the firm’s size,
tangibility, leverage and interest coverage. Our Bond Characteristics include the time to
maturity, the principal amount of the bond offering, the number of covenants and whether the
debt is rated investment grade by at least one of the three major credit rating agencies. Last, we
control for Lender Power, which is an indicator variable for the years of tight credit supply as
23
proxied by the financial crisis period. During periods of a tight credit supply, bond investors are
likely to have stronger bargaining power and can therefore influence covenant structure to a
greater extent. We do not have a specific prediction for the Lender Power coefficient because
bond holders can benefit from both lower contracting and comparability costs via more similar
covenant restrictiveness as well as from stronger protection via more tailored (i.e., less similar)
covenants. For a more detailed description of these and other variables used in our tests, see
Appendix C. For all our tests, we cluster the standard errors at the firm level.
4.2.2. Results. We present the analysis of determinants of the similarity in bond covenant
restrictiveness in Table 3. Columns 1 to 3 present the results of estimating equation 1. We start
by examining the effect of debt market agents—legal counsel and underwriters—on covenant
similarity. In column 1, we exclude Similar Legal Counsel while column 2 excludes Similar
Underwriter. In column 3, we include both variables. As the results are similar across columns,
we focus on the column 3 results. The coefficient on Similar Legal Counsel is 0.975 and is
statistically significant (t-statistic = 2.25), consistent with firms who share the same legal
advisers having more similar covenant structures. In terms of economic significance, two bonds
that are issued by the same legal counsel have covenant similarity scores that are approximately
one-third standard deviation greater than covenant similarity scores across two bonds that do not
share the same legal counsel. We do not, however, find evidence that covenant structures are
more similar for two firms sharing the same lead underwriter. This evidence is consistent with
the notion that underwriters exhibit greater flexibility in adapting to new covenant terms relative
to legal advisers. In terms of similarity in firm characteristics, we provide evidence that similar
fundamentals (and hence potentially similar debt agency conflicts) lead to similar covenants. The
Similar Size and Similar Tangibility coefficients are both positive and statistically significant.
24
For the other control variables, we observe that covenant restrictiveness is less similar for
bonds with larger offering amounts. We surmise that since large bonds have a higher credit risk
and face more significant agency conflicts, bondholders are more likely to demand idiosyncratic
protection features, decreasing the similarity of the covenant restrictiveness terms. Further, large
bond issues are likely to be purchased by a more diverse group of investors, each with different
protection needs and levels of exposure that potentially contribute to more dissimilarity in the
restrictiveness of the covenant structures. Also, if the costs of adjusting the covenants are mainly
fixed, then these costs may be relatively less economically important for larger offering amounts.
Covenant structures are also more similar for firms with investment grade bonds. These bonds
tend to have lower levels of covenant restrictiveness in general and hence less opportunity to
differ between bonds. Investment grade bonds are also less risky, which may further decrease
bondholders’ demand for idiosyncratic protection terms.
As a robustness test, in column 4, we estimate the same specification but instead of at the
firm i level with one observation per bond, we estimate the specification at the bond i-peer j
level, with one observation for each bond i-peer j pair of bond issues. This increases the total
number of observations in the test to 7,308. We continue, however, to cluster the standard errors
at the firm level. The advantage of this specification is that we maximize the variation in the
measurement of our similarity variables, as opposed to the specification in column 1 where we
average the similarity scores for each bond issue. Inferences from this specification for the most
part mirror those in column 1. The coefficient on Similar Legal Counsel is positive and
statistically significant, consistent with firms who share the same legal adviser having similar
covenant structures. Similarity in firm size, tangibility and leverage is positively related to
covenant similarity. As in column one, bonds with larger offering amounts have less similar and
25
investment grade bonds have more similar covenant restrictiveness.
Overall, as expected, we find that bond covenant restrictiveness is more similar relative
to covenant restrictiveness in peer firms’ bond contracts when the same legal advisors are used
and when firm characteristics are more similar. This latter result suggests that when firms have
similar agency conflicts the covenant structures are more similar.
4.3. Covenant Similarity Consequences: Yield Spread
4.3.1. Tests. To determine whether similarity in covenant restrictiveness has significant
economic consequences, we examine the implications of the covenant similarity with respect to
the pricing of the bonds in the primary market. We estimate the following regression:
Spread = 0 +1 Covenant Similarity +2 Market Spread
+ 3 Firm Characteristics + 4 Bond Characteristics + .
(2)
Spread is the difference between offering yield of the bond issue minus the yield on the Treasury
bill with the closest maturity, obtained from Mergent FISD. The average yield spread is 2.2%.
This relatively tight spread is indicative of the predominance of investment grade bonds in our
sample. Our variable of interest is Covenant Similarity. We expect that greater covenant
similarity should be negatively associated with bond spreads if more similar covenant
restrictiveness provides net benefits to bondholders. Market Spread is the mean spread by rating
category for a particular quarter when the bond was issued, where the rating spectrum is divided
into four broad rating categories (i.e., AAA to Aaa2, Aa3 to A2, A3 to Baa2, and Baa3 to D). It
controls for market-wide fluctuations in spreads driven by macroeconomic factors as well as
differences in spreads that capture credit risk premiums across rating categories. Our firm
characteristics and bond characteristics include the same variables as in the previous test.
We estimate model 2 in two ways. Our first estimation uses OLS. We acknowledge the
difficulties in isolating the effect of similarity in covenants’ restrictiveness on yields due to the
26
potential endogeneity in the relation between covenant terms and bond pricing (e.g., Smith and
Warner 1979; Bradley and Roberts 2004; Costello and Wittenberg-Moerman 2011). To address
this concern, we employ an instrumental variable (IV) approach. This approach is based on the
simultaneous estimation of the covenant similarity determinants model (equation 1) and the
model of covenant similarity consequences (equation 2). To instrument covenant similarity, we
rely on Similar Legal Counsel, which reflects whether the bond and its peer bonds are issued by
the same legal advisor. In terms of strength and validity of the first stage, we find that Shea’s
Partial R2 for the first stage is relatively high at 32.17%. Further, we find that the Cragg and
Donald (1993) minimum eigenvalue statistic of 57.66 exceeds the most conservative Stock and
Yogo (2005) 5%-relative-bias critical value of 20.25, thereby rejecting the null hypothesis of a
weak instrument. As we report in column 1 of Table 3, this variable is a significant determinant
of covenant similarity. We do not expect this variable to be directly related to bond yields, as
there is no obvious reason to expect a strong association between the bond yield and the fact that
the legal advisor of the bond issue is the same as the advisor of the bonds of the peer firms.
4.3.2. Results. Table 4, Panel A, present the results of estimating equation 2. Column 1
presents the OLS results. Consistent with our predictions, we find that covenant similarity is
negatively related to bond spreads. The coefficient on Covenant Similarity is -0.046 with a t-
statistic of -2.86. In other words, a one-standard-deviation increase in the similarity of covenants’
restrictiveness is associated with a 0.12% reduction in the spreads (or 5.7% of the mean spread in
our sample). Given that the average bond issue in our sample has a principal value of $412
million and an average maturity of 8.27 years, the effect translates into savings for the borrower
of approximately $4 million over the life of the bond issue. This result indicates that similarity in
covenant restrictiveness leads to positive economic consequences for firms in terms of a reduced
27
cost of debt. In column 2, we present the 2SLS results. We notice a slightly reduced sample in
this test compared with OLS due to additional Compustat data requirements for peer firms to
calculate the first-stage bond covenant similarity scores. The results largely parallel the OLS
results. The variables that load in the OLS specification have comparable coefficients and
magnitudes of statistical significance in the 2SLS specification. In particular, the coefficient on
Covenant Similarity is -0.066 with a t-statistic of -2.33, consistent with a negative relation
between covenant restrictiveness similarity and bond spreads.
In terms of control variables, as expected, Market Spread is positively correlated with the
bonds’ Spread. We also observe that spreads are negatively related to tangibility and interest
coverage, but positively related to the bond’s maturity. These results are generally consistent
with prior research on debt pricing (e.g., Booth 1992; Beatty et al. 2002; Bharath et al. 2008;
Zhang 2008). Note that we do not find a significant relation between the yield and some other
firm-level characteristics. This is due to our control for market spread by rating category, which
subsumes the effect of firm characteristics on spread to the extent that these characteristics are
reflected in the rating. As support for this assertion, untabulated tests demonstrate that these firm
characteristics load in the expected direction if Market Spread is excluded from the specification.
4.3.3. Robustness. We perform a series of robustness tests that are presented in Panel B of
Table 4. Our equation 2 results that covenant similarity leads to reduced yield spreads are robust
to each of the following tests. First, firm i-level observations will vary in the number of peers
used to calculate Covenant Similarity. In column 1, we augment our test with the number of
peers. Second, in column two, we control for the level of covenant restrictiveness to make sure
that it, instead of the similarity in covenant restrictiveness, is not driving our result.12
Third,
12
Although we would expect stronger covenant protection to reduce debt pricing, empirical studies typically find an
insignificant coefficient on the variable reflecting the number of covenants or covenant restrictiveness in the debt
28
when calculating the aggregate covenant similarity, instead of weighing each covenant equally,
in column 3 we weigh each covenant based on the covenant importance suggested by Moody’s
(2013) and by our conversation with a Moody’s analyst.13
In additional untabulated analyses, we
also verify that the results reported in all three columns of Panel B are not affected by potential
endogeneity between yield and similarity in covenant restrictiveness. We repeat all analyses by
estimating 2SLS specification and find that the results are unchanged.
4.3.4. Tests by Individual Covenant. To provide further validity to the impact of covenant
similarity on bond spreads, in the next set of analyses we examine the effect of the similarity in
each individual covenant versus the bonds issued by peers. If covenant similarity is important
with respect to contracting and comparability costs, we should observe that an effect on yield
would also hold at the individual covenant level, especially for particularly complex covenants.
We re-estimate the regression in equation 2 using the similarity of each covenant. That is, we
replace the aggregate covenant similarity variable with a particular individual covenant similarity
value. All other independent and the dependent variables remain the same.
Table 5 provides the results from each regression by covenant. We find that of the eight
covenants, all coefficients on Covenant Similarity are negative as expected and four of them are
statistically significant. The consequences of covenant similarity are driven by the covenants that
pertain to payment restrictions, debt, liens and asset sales, suggesting that bondholders care about
similarity in different types of covenants, ranging from cash distribution to indebtedness and
capital expenditures. Three of these four covenants — the restrictions on payments, additional
pricing regressions (e.g., Bradley and Roberts, 2004) An insignificant coefficient on these covenant measures is
likely to be attributed to the endogenous relationship between debt pricing and the strength of covenant protection
(Costello and Wittenberg-Moerman 2011). 13
Our re-weighted measure uses the following weights for each covenant type: payment restrictions (25%), debt
incurrence (25%), change of control (5%), merger restrictions (5%), liens restrictions (20%), asset sales restrictions
(5%), leaseback restrictions (5%) and limits on subsidiary debt (10%).
29
debt and asset transactions — have the most complex specification and terms based on our
analysis of a random sample of 30 bond prospectuses. For example, for payment restrictions, the
terms of these covenants are at least 1000 words in length and reach 2700 words (on average).
Moody’s analysts also consider these covenants to be relatively more important than the others
(Moody’s 2013). Therefore, this evidence provides further support for our proposition that
covenant similarity potentially helps bond market participants save on information acquisition
and processing costs.
5. Additional Consequences of Covenant Similarity
In this section, we provide complementary analyses of how covenant similarity could
lead to reduced bond yields at issuance. In particular, we expect the effect of higher contracting
and the comparability costs associated with changes in covenant restrictiveness to also manifest
in the holdings of insurance companies and secondary trading. We expect these analyses to
reinforce our prediction that covenant similarity has important economic consequences.
5.1. Insurance Company Holdings
We analyze whether the presence of covenants with similar terms is associated with
higher bond ownership by insurance companies who are important long-term investors in the
corporate bond market. Schultz (2001) estimates that insurance companies collectively hold up
to 40% of U.S. investment grade corporate bonds. Becker and Ivashina (2014) also show that
insurance companies are the largest institutional holder of corporate and foreign bonds, with
bond holdings that in 2010 were $2.3 trillion more than those of mutual and pension funds
combined.14
Further, over 90% of insurance companies’ holdings are in fixed income securities
(Nissim 2010). If a bond attracts insurance companies, we expect this increased demand for the
14
Bessembinder, Maxwell and Venkataraman (2006) find that insurance companies are responsible for a significant
percentage of trading volume. Using data from TRACE during the second half of 2002, they document that
insurance companies have completed about 12.5% of the dollar trading volume.
30
security to significantly lower its pricing.
Insurance companies invest in a large number of bonds and hold them until maturity with
limited portfolio rebalancing. They also potentially incur capital penalties from regulators if the
bonds subsequently underperform. Given the significant and long-term investments being made,
insurance companies are likely to prefer bonds whose terms, along with the expected level of
credit protection, are comparable and involve predictable litigation risks. As a result, we expect
that they will be more likely to invest in bond issues with more similar covenants. To test this
notion, we use our peer-based sample to estimate the following regression:
Insurance Holdings = 0 + 1 Covenant Similarity + 2 Market Insurance Holdings
+ 3 Firm Characteristics + 4 Bond Characteristics + .
(3)
Insurance Holdings is the ratio of the par value of a bond held by insurance companies to the
total par value held by institutional investors in the quarter following the issuance of the bond.
We focus on the first quarter after bond issuance because as a bond becomes more seasoned, it
becomes less liquid, because inactive investors progressively absorb the original bond issue in
their portfolio and trading becomes thinner (Warga 1992). Untabulated analyses show that our
results are robust to the use of horizons of up to 12 months. Market Insurance Holdings is
measured analogously to the market-wide control variables in equation 2. Our firm and bond
characteristics remain the same as in previous tests.
We obtain bond ownership information from the National Association of Insurance
Commissioners (NAIC) starting from 2001 and match this data with bond specific data in the
Mergent Fixed Income Securities Database (Mergent FISD). NAIC provides detailed
information on every bond holding for each insurer at the end of each year and every bond
transaction that occurred in that year for each insurer. This dataset allows us to compute the
percentage of ownership by insurance firms in a particular bond following its issuance.
31
Descriptive statistics in Table 2 indicate that more than half of the par value of the bond is
typically owned by insurance companies during the quarter immediately after the issuance.
Column 1 of Table 6 presents the results of estimating equation 3 using OLS. The
Covenant Similarity coefficient is 0.011 and is statistically significant (t-statistic = 3.27). The
results are economically significant: a one-standard-deviation increase in similarity increases the
share of the bonds absorbed by insurance companies by 2.96% (or 5.5% of the sample average of
53.9%). This result supports our prediction that insurance companies prefer to invest in bonds
with covenant restrictiveness that is more easily comparable to the covenant restrictiveness of
peer bonds. This evidence is consistent with lower contracting and comparability costs incurred
by insurance companies when investing in bonds with similar covenant restrictiveness terms.
With respect to the control variables, in addition to the market-based variable of insurance
holdings, which is loading positively, insurance holdings are negatively related to firm size, the
number of covenants and the offering amount, and positively related to interest coverage and
bond’s time to maturity. Column 2 of Table 6 provides the 2SLS results, which are very similar
to the column 1 OLS results and produce comparable inferences.
Overall, the evidence indicates that when covenant restrictiveness is more similar to the
covenant restrictiveness in peer firms’ bonds, long-term investors such as insurance firms are
more likely to invest in bonds with these covenants. This finding provides a partial explanation
for our results that bond issuance yields are lower for bonds with more similar covenants.
5.2. Trading
If similarity in covenant restrictiveness eases the effort exerted by investors in
understanding the nuances of a bond contract, we would also expect it to reduce investors’
information processing costs. Hence, we predict that covenant restrictiveness similarity is
32
positively associated with the extent of bond trading and secondary market liquidity. Evidence
consistent with this prediction provides a further partial explanation for lower spreads because
greater liquidity should decrease expected illiquidity premiums and lead to lower yields at
issuance (e.g., Chen, Lesmond and Wei 2006; Mahanti et al. 2008).
To test this idea, we use our peer-based sample to estimate the following regression:
Trading = 0 +1 Covenant Similarity +2 Market Trading
+ 3 Firm Characteristics + 4 Bond Characteristics + .
(4)
Trading consists of two variables, Volume and Transactions, measured using bond trading data
provided by the Trade Reporting and Compliance Engine (TRACE) and NAIC.15
Volume is the
logarithm of the trading volume in the 30 days following the bond issuance, while Transactions
is the logarithm of the number of transactions over this period. We focus on a 30-day period
because the bonds are absorbed promptly into the portfolios of buy-and-hold large institutional
investors (e.g., insurance companies and pension funds) and do not trade (Warga 1992).16 The
average total volume traded during the 30-day period immediately after the issuance of a bond in
our sample is high: it reaches $263 million, which represents approximately 173 transactions.
We expect that increased covenant similarity is positively associated with bond trading. Market
Trading is measured analogously to the market-wide control variables in equation 2. When the
dependent variable is Volume, Market Trading is the mean trading volume by rating category for
a particular quarter, and it controls for market-wide fluctuations in trading volume as well as
differences in volume across rating categories. When the dependent variable is Transactions,
then Market Trading is defined analogously but by using trading transactions instead of volume.
15
TRACE did not cover all bonds trading in the secondary market until February 2005. As a result, we add bond
transaction data from NAIC, which is provided by the Mergent FISD database. If on a certain day, a bond issue does
not have any trades reported in TRACE but Mergent FISD indicates that a trade occurred, we include the Mergent
FISD trade information in our tests. 16
Our results are robust to shorter periods, such as 14 days.
33
Our firm and bond characteristics remain the same as in previous tests.
The results are presented in Table 7. The first two columns present the results when
Volume is the dependent variable, and the second two columns provide results when the
dependent variable is Transactions. The first and third columns are OLS, while the second and
fourth columns are 2SLS. The results are highly consistent across all columns, so for parsimony
we discuss the first and third column results. Covenant Similarity is positively related to Trading,
as hypothesized. The Covenant Similarity coefficient is 0.291 and statistically significant, albeit
at more modest levels (t-statistic = 1.75). In terms of economic significance, a one-standard-
deviation increase in similarity is associated with an increase in Volume of 0.796 (or 6% of the
average volume in our sample). Economic significance is much higher when trading is measured
as number of transactions, with a one-standard-deviation increase in similarity being associated
with an increase in Transactions that is 19% of the mean. As expected, Market Trading is a very
important determinant of firm-level trading. In terms of other control variables, bond trading is
greater for the bonds of firms that are larger and have lower leverage and those of larger
amounts, consistent with findings in the prior literature on bond liquidity (Chen, Lesmond and
Wei 2006; Mahanti et al. 2008).
In sum, our results show that more similar bonds are associated with higher trading,
likely due to low information acquisition and comparability costs. Consistent with bond investors
pricing secondary market liquidity, this increased liquidity provides a partial explanation for our
results that bonds with more similar covenants have lower bond yields at issuance.
6. Time-Series Covenant Similarity
While our primary tests are based on similarity to the bonds of peers, we also develop a
time-series-based measure of similarity in the covenant restrictiveness over time for a given firm.
34
The economic trade-offs we investigate in the above tests—reducing contracting and
comparability costs versus receiving less customized credit protection—are also valid for time-
series covenant similarity. On one hand, bondholders may benefit from lower information
collection and processing costs as well as higher comparability when the covenant restrictiveness
in the current bond is similar to that in a firm’s previously issued bonds with which bondholders
are already familiar. On the other hand, changes in firm fundamentals may encourage
bondholders to demand adjustments to covenant restrictiveness of the new bond issues.
We replicate our primary analyses of the determinants of covenant similarity and yield
spread tests using the time-series measure of similarity in covenant restrictiveness in Table 8.
Our time-series measure is calculated analogously to the peers’ covenant similarity measure
above, except that instead of comparing a bond to one issued by a peer firm, it is compared with
one issued by the same firm during the five years prior to the bond issue under consideration.
The five-year period allows for sufficient time to pass and increases the chances of the firm
having issued more than one bond over the period. For these tests, the other similarity
variables—Similar Legal Counsel, Similar Underwriter and Similar Firm Characteristics—are
calculated in an analogous manner to the time-series-based dependent variable. For example,
Similar Legal Counsel is an indicator variable that indicates whether the firm’s current and
previous bonds are advised by the same legal counsel, zero otherwise. Likewise, when we
calculate Similar Firm Size, the difference between the firm’s size when it issued the bond versus
its size when it issued the previous bond. The absolute difference is then multiplied by -1 to
capture similarity in covenant restrictiveness. Other Similar Firm Characteristics are calculated
the same way. Our expectations about the relationships between covenant similarity and its
determinants, as well as yield spread, remain unchanged. Our sample consists of 845 bond i
35
observations for the yield tests in which the firm has issued a previous bond that meets our
criteria. Data requirements for the construction of the time-series-peers-based similarity measure
yield a slightly smaller sample than that used for the cross-sectional peers-based tests.
Panel A of Table 8 provides some descriptive statistics for the time-series similarity
variables. The average covenant similarity of -0.768 calculated using time-series comparisons
with the firm’s previously issued bonds is close to four times higher than the average covenant
similarity calculated using cross-sectional peers of -2.842 (from Table 2). The overall covenant
time-series similarity score indicates an on-average dissimilarity of only 0.10 per covenant
(= -0.768 total/8 covenants) for a bond. In other words, covenants are “sticky” with respect to
bonds previously issued by the same firm compared to bonds issued by its peers. Sticky covenant
quality is likely to reflect sticky firm fundamentals. Similarly, we see significant time-series
stickiness in the choice of legal counsels and underwriters for bonds issued by the same firm. On
average, 47% and 20% of the bonds are issued by the same legal counsel and underwriter
respectively. As expected, the closeness in firm characteristics based on comparisons with the
same firm when it issued its previous bonds reflects higher similarity than when it is measured
against its peers (from Table 2).
Panel B provides the results of our determinants test, which focuses on factors that
explain the time-series-based measure of similarity in covenant restrictiveness. This time-series
specification is comparable to that of equation 1 except that the similarity variables, as described
above, are time-series-based. Our Panel B results provide further validating evidence, as the
inferences from these tests are highly comparable to those in our main determinants test in Table
3. The positive and statistically significant coefficient on Similar Legal Counsel shows that if the
firm used the same legal counsel for its previous bond issue, then the covenant restrictiveness of
36
the current bond is more similar to that of the firm’s previous bond. For the other control
variables, results are also generally consistent with the Table 3 results.
We next conduct the analysis of spreads using the time-series-based Covenant Similarity
measure. Except for this variable, all other independent and dependent variables remain the same
as those in equation 2. Panel C of Table 8 presents the results using our time-series version of
Covenant Similarity. The first column is based on OLS. The second column is based on 2SLS.
Across the two regressions, both coefficients on Covenant Similarity are negative and
statistically significant, as expected. In terms of economic significance, based on the coefficient
on Covenant Similarity in column 1, a one-standard-deviation increase in time-series similarity is
associated with a 0.24% reduction in spread (or 11% of the mean spread in our sample). This
result is consistent with (and slightly stronger than) the main yield spread test in Table 4.
Therefore, similarity in covenant restrictiveness over time also provides firms with a reduced
cost of debt. Overall, these tests using time-series covenant similarity provide results that are
parallel to those using our main measure of covenant similarity, reinforcing our main findings.
In untabulated robustness analyses, we examine whether the similarity in covenant
restrictiveness relative to that of covenants in bonds previously issued by the same firm is
partially due to bond shelf registrations under Rule 415 (SEC 1982). Shelf registrations permit
firms to file a single all-encompassing registration statement over a period of up to three years,
as opposed to individual registration statements for every security offering. While the covenant
structure is not part of the shelf registration prospectus, it is possible that bonds issued under the
same prospectus are more likely to have similar covenant restrictiveness. We control for this
effect by augmenting our Panel C test with a dichotomous variable that indicates whether the
bonds are issued within a span of three years from each other, which proxies for bonds issued
37
under Rule 415. Our results and inferences are robust to controlling for this variable.
7. Conclusion
We investigate the factors affecting the similarity of covenant restrictiveness terms across
bond issues and examine whether it is priced in the bonds’ yields to maturity at issuance. While
tailored and less similar bond covenants are potentially more effective in monitoring a borrower,
bondholders might prefer similar covenant terms to mitigate contractual and comparability costs.
These costs are generated when covenant terms are modified relative to the terms used in peers’
previously issued bonds.
Using a measure of covenant restrictiveness developed by Moody’s, which highlights the
principal strengths and structural gaps in the protection provided by individual bond covenants,
we show that covenant similarity is greater when bond issuers share the same legal counsel. We
also find that firms with similar economic features and business models have similar covenant
structures. In our primary set of analyses, we document that similarity in covenant restrictiveness
is associated with significantly lower bond yields at issuance, suggesting that bond investors
view more similar covenant terms positively, as such terms potentially lower contracting and
comparability costs across different bonds. Additional tests show that bonds with similar
covenant restrictiveness terms are characterized by a higher level of bond ownership by long-
term bond investors, such as insurance companies, and that for these bonds the secondary market
bond liquidity is greater following the bond’s issuance. These latter findings provide a partial
explanation for the lower bond issuance yields.
Our findings add to the literature on the covenant structure in debt contracts. We
highlight the important role of the similarity of covenant restrictiveness terms across different
bond issues. We show that similarity in covenant restrictiveness have significant economic
38
consequences for both bondholders and issuing firms, such as lower bond yields, greater
secondary bond market liquidity and greater interest from long term investors such as insurance
companies. We also emphasize non-agency-based explanations for the bond covenant structure.
In particular, we show that the contracting and comparability costs of changing covenant
restrictiveness terms may exceed the credit risk protection benefits that more tailored covenants
provide. We also offer new evidence on the multifaceted structure of bond covenants and the
comprehensiveness of the protection they offer. We thus extend studies on public bond
agreements that have focused on the inclusion of individual covenants in bond contracts or
indices that count the number of bond covenants, which are unlikely to accurately capture the
strength of bond covenant protection.
39
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42
APPENDIX A
Examples of headroom and carve-out estimations
Covenant Quality Assessment October 2, 2008
Meritage Homes Corporation
Limitation on Debt Incurrence
Headroom
The issuer shall not, and shall not permit any restricted subsidiary to, directly or indirectly, incur any
“indebtedness”, provided that the issuer or any restricted subsidiary may incur additional indebtedness (including
“acquired indebtedness”) if no default shall have occurred and be continuing at the time of or as a consequence of
the incurrence of the indebtedness and if, after giving effect thereto, either:
(a) the “consolidated fixed charge coverage ratio” would be at least 2.00 to 1.00; or
(b) the ratio of “consolidated indebtedness” to “consolidated tangible net worth” would be less than 3.00 to
1.00 (either (a) or (b), the “ratio exception”).
*Amounts in thousands
1. Consolidated fixed charge coverage ratio
“Consolidated fixed charge coverage ratio” means the ratio of
• “consolidated cash flow available for fixed charges” during the most recent four consecutive full fiscal quarters
for which financial statements are available (the “four-quarter period”) ending on or prior to the date of the
transaction giving rise to the need to calculate the consolidated fixed charge coverage ratio (the “transaction
date”) to
• “consolidated interest” incurred for the four-quarter period.
Estimation
*The indenture provides extensive definitions of “consolidated cash flow available for fixed charges” and
“consolidated interest,” which determine the estimation of these terms.
CONSOLIDATED CASH FLOW
AVAILABLE FOR FIXED CHARGES
Last Twelve Months
Net Income (316,164)
Provision for income taxes (178,676)
Amortization + Depreciation 15,338
Consolidated interest expense
Interest expense 17,625
Interest incurred 56,005
Other non-cash items reducing
net income
Real-estate related impairments 323,950
Goodwill-related impairments 102,538
Stock-based comp. 6,801
Tender-offer stock comp. exp. 10,866
Total 38,283
Consolidated fixed charge coverage ratio (CFCCR) = 38,283/ (17,625 + 56,005) = 38,283/ 73,630 = 0.52x
Thus, estimated headroom is 0.52x - 2.00x = (1.5)x, or null under the CFCCR Incurrence test.
2. Consolidated net worth ratio
“Consolidated net worth ratio” means the ratio of
• “consolidated indebtedness (long-term debt)” to
• “consolidated tangible net worth”
43
Estimation
*The indenture provides extensive definitions of “consolidated indebtedness (long-term debt)” and “consolidated
tangible net worth,” which determine the estimation of these terms.
Consolidated indebtedness = loans payable and other borrowings + senior and senior subordinated notes = 6,091 +
628,885 = 634,976
Consolidated tangible net worth = consolidated stockholders’ equity – consolidated intangible assets = 746,794 –
7,137 = 739,657
Consolidated indebtedness/ consolidated tangible net worth = 634,976/ 739,657 = 0.86x
Thus, estimated headroom is 3.00-0.9 = 2.1x under the consolidated net worth test.
Carve-outs [quantitative]
Notwithstanding the above, so long as no default shall have occurred and be continuing at the time of or as a
consequence of the incurrence of the following indebtedness, each of the following shall be permitted (the
“permitted indebtedness”):
• Indebtedness of the issuer and any restricted subsidiary under the “credit facilities” in an aggregate
amount at any time outstanding (whether incurred under the ratio exception or as permitted indebtedness)
not exceeding the greater of:
- $600.0 million; and
- the amount of the “borrowing base” as of the date of such incurrence;
• Indebtedness of the issuer or any restricted subsidiary in an aggregate amount not to exceed $25.0 million
at any time outstanding.
“Borrowing base” means, at any time of determination, the sum of the following without duplication:
(1) 100% of all cash and cash equivalents held by the issuer or any restricted subsidiary;
(2) 75% of the book value of “developed land” for which no construction has occurred;
(3) 95% of the cost of the land and construction costs including capitalized interest (as reasonably allocated
by the issuer) for all “units” for which there is an executed purchase contract with a buyer not affiliated
with the issuer, less any deposits, down payments or earnest money;
(4) 80% of the cost of the land and construction costs including capitalized interest (as reasonably allocated
by the issuer) for all units for which construction has begun and for which there is not an executed purchase
agreement with a buyer not affiliated with the issuer; and
(5) 50% of the costs of “entitled land” (other than developed land) on which improvements have not
commenced, less mortgage indebtedness (other than under a “credit facility”) applicable to such land.
Estimation
Borrowing base Corresponding item in
financial statement
Gross
Amount
x factor
100% of cash and cash equivalents Same 115,153 115,153
75% of book value of “developed land” (no construction) Finished lots and land
under dev.
544,191 408,143
95% of costs related to “units” (executed contracts) Homes under contract 357,304 339,439
80% of costs related to “units” (construction begun) Unsold homes 137,785 110,228
50% of costs of “entitled land” (improvements not begun) Land held for dev. 15,389 7,694.5
Total 980,658
Debt capacity under credit facility carve-out Amount
Total carve-out = greater of 600,000 and 980,658 980,658
Less
Credit facility (committed) (amended July 18, 2008) 500,000
Total debt capacity 480,658
44
Covenant Carve-out Amount
Indebtedness under the credit facilities in an aggregate
amount at any time outstanding (whether incurred under
the ratio exception or as permitted indebtedness) not
exceeding greater of $600.0 million and the amount of the
borrowing base (see borrowing base calculation below)
480,658
Indebtedness of the issuer or any restricted subsidiary 25,000
Total debt capacity 505,658
Total consolidated assets = 1,619,810
Total debt capacity = 505,658
Indenture carve-out as a percentage of total consolidated assets = 505,658/1,619,810 = 31.2%
Covenant Quality Assessment October 12, 2007
K. Hovnanian Enterprises, Inc.
Limitation on Debt Incurrence
Headroom
The issuer will not and will not permit any restricted subsidiary, directly or indirectly, to create, incur or assume
liability for or guarantee the payment of any indebtedness unless the FCCR (defined above) would be at least 2.0 to
1.0.
*Amounts in thousands
Consolidated fixed charge coverage ratio
“Consolidated fixed charge coverage ratio” means with respect to any determination date, the ratio of:
“consolidated cash flow available for fixed charges” for the prior four full fiscal quarters (the four quarter
period) for which financial results have been reported immediately preceding the determination date (the
“transaction date”), to
the aggregate “consolidated interest incurred” for the four quarter period.
Estimation
*The indenture provides extensive definitions of “consolidated cash flow available for fixed charges” and
“consolidated interest,” which determine the estimation of these terms.
CONSOLIDATED CASH FLOW AVAILABLE
FOR FIXED CHARGES Last twelve months
Consolidated Net Income (275,785)
Income Taxes (143,955)
Cost of sales interest 131,361
Depreciation 17,826
Intangible Amortization 94,854
Amortization of Bond Discounts 1,118
Other Interest 10,492
Compensation from Stock Options and Awards 21,135
Loss on Sale and Retirement of Property and Assets 307
Loss (Income) from Unconsolidated Joint Ventures 32,202
Impairment and Land Option Deposit Write-Offs 499,646
Total 389,201
45
CONSOLIDATED INTEREST INCURRED Last twelve months
Cost of Sales Interest 131,361
Other Interest 10,492
Amortization of Bond Discounts 1,118
Total 142,971
Consolidated Cash Flow Available for Fixed Charges / Consolidated Interest Incurred = 389,201 / 142,971 = 2.7
Thus, headroom is 2.7x – 2.0x = .7x under the Consolidated Fixed Charge Coverage Ratio.
Carve-outs [quantitative]
Notwithstanding the above, so long as no default shall have occurred and be continuing at the time of or as a
consequence of the incurrence of the following indebtedness, each of the following shall be permitted (the
“permitted indebtedness”):
Indebtedness under credit facilities in an aggregate amount not exceeding $1.5 billion; Indebtedness secured only by office buildings owned or occupied by Hovnanian or any restricted
subsidiary in an aggregate amount not exceeding $10 million; and
All other indebtedness of Hovnanian or any restricted subsidiary in an aggregate amount not exceeding $50
million
Estimation
Debt capacity under credit facility carve-out Amount
Total carve-out 1,500,000
Less:
$1.5 billion (unsecured revolving credit agreement through
May 11)
1,500,000
Total debt capacity 0
Covenant Carve-out Amount
Indebtedness under credit facilities not exceeding $1.5
billion
0
Indebtedness secured only by office buildings owned or
occupied by Hovnanian or any restricted subsidiary in an
aggregate amount not exceeding
10,000
All other indebtedness of Hovnanian or any restricted
subsidiary in an aggregate amount not exceeding
50,000
Total debt capacity 60,000
Total consolidated assets = 5,362,762
Total debt capacity = 60,000
Indenture carve-out as a percentage of total consolidated assets = 60,000/5,362,762 = 1.12%
46
APPENDIX B
Discussion of Primary Covenants
Moody’s evaluates how bond covenants mitigate risk in several areas. They focus on the
following covenants, which are the most common in bond indentures. We define these covenants below
and provide a discussion of how Moody’s assesses the quality of each.
Restricted Payments. The restricted payment covenant group is focused on limiting what the
issuer is allowed to do with cash or other assets. Bondholders want the firm to retain the cash and other
assets of the issuer and its restricted subsidiaries and allow them to exit the company only under limited
circumstances. Bondholders are concerned if cash transfers go to equity and subordinated creditors,
especially at a time when such distributions decrease the issuer’s ability to service its debt, increasing the
default risk and reducing the recovery prospects in liquidation. However, Moody’s view is that a value
transfer from bondholders can also occur more indirectly, through management’s valuation of non-cash
assets, transactions with its affiliates or the designation of non-restricted subsidiaries.17
The restricted payments covenant has the most complex structure. In the prohibitory paragraph,
the covenant may prohibit dividends on capital stock, stock repurchases, the early purchase or redemption
of debt that is subordinated to the bonds and the making of some investments.18
The covenant allows
some restricted payments in the proviso and the carve-outs; the amount that can be paid out by the issuer
as a restricted payment at any time is often referred to as the “restricted payment basket.” The covenant's
proviso often specifies that a restricted payment can be made conditional on a debt incurrence ratio test
(e.g., an interest coverage threshold is met). The restricted payment basket may be increased by a certain
percentage of the consolidated positive net income of the issuer and restricted subsidiaries (e.g., 50%), by
the issuance of equity or by the conversion of debt into equity; it will be reduced by the amount of
restricted payments actually made over time or by the consolidated negative net income of the issuer and
the restricted subsidiaries.
A strong restricted payment covenant allows the issuer to only begin making restricted payments
when the income basket is beginning to build up. In contrast, a weak structure would have a start date for
making restricted payments (which is typically the bond issue date) that follows the buildup date. This
weak structure will allow the income basket to accumulate income before the bond issuance date,
facilitating larger restricted payments. The covenant also provides limited protection if it includes
numerous and sizable carve-outs, facilitates managers’ opportunistic valuation of the non-cash assets in
the income basket or fails to limit transactions with affiliate entities that are not restricted. Transactions
with some affiliates may circumvent the restricted payment covenant by disguising a dividend-like
transaction with the form of a business transaction (e.g., royalty payments).19
A protective
17
Bond covenants limit the activities of the bond issuer, but only certain of its subsidiaries. Subsidiaries subject to
covenants are called “restricted subsidiaries” since their cash flows are contractually required to service the bond
debt. “Unrestricted subsidiaries” are subsidiaries that are not limited by bond covenants and their cash flows are not
contractually available to service the bond debt. They are excluded from covenant financial ratio definitions and
calculations. 18
These investment restrictions typically refer to investments in the debt or equity of other companies, even
providing guarantees for another company's debt. Capital expenditures or acquisitions of productive assets are not
restricted by this covenant. 19
Restrictions on transactions with affiliates are particularly important when the issuer is a private company
controlled by a small group of shareholders. A private company issuer is likely to request carve-outs for fees paid to
financial sponsors.
47
APPENDIX B (Continued)
Discussion of Primary Covenants
structure would permit only those transactions done on an arm’s length basis and, if above a reasonably
low threshold, would require a third-party fairness opinion. A Restricted Payment covenant will also
provide a weak protection if the designation of unrestricted subsidiaries does not need to comply with the
covenant.
Debt Incurrence. Increased leverage can negatively impact bondholders by reducing the cushion
of cash flow, increasing default risk as well as increasing management’s incentives to engage in
shareholder friendly actions. Restrictions on the incurrence of indebtedness are designed to protect
bondholders from these incremental risks by limiting the issuance of additional debt unless the issuer has
the demonstrated capacity to service all its debt, including the proposed new debt. Indebtedness is defined
more generally and includes debt, lease obligations, reimbursement obligations with respect to letters of
credit, obligations to redeem stock and guarantees provided by the issuer with respect to the indebtedness
of other entities.
The capacity to service the debt (including the new debt) specified in the proviso is usually tested
based on a comparison of cash flows to interest expense; this test is known as the “coverage” or “debt
incurrence” test. The basic incurrence test allows the issuer to incur additional debt if the issuer has a ratio
of EBITDA to cash and non-cash interest expense of at least 2 to 1. An alternative is a leverage test,
which evaluates the relationship of the issuer’s consolidated debt to its trailing 12-month EBITDA on a
pro forma basis.
Debt incurrence covenants may contain several carve-outs. First, most debt covenants allow an
exception for the issuer to incur bank debt (constructed around the issuer’s borrowing base using the level
of inventories and accounts receivables or limited to a specified dollar amount) and intercompany debt
with its restricted subsidiaries. Second, the covenant might permit the issuer to refinance debt outstanding
at the time of the indenture or issued after the indenture in order to limit the possibility of a default when
this debt matures. When refinancing debt, the issuer is typically not allowed to increase the principal
amount (except to the extent needed to pay related costs, e.g., accrued interest, premium and other
retirement costs), shorten the average life of the debt refinanced or refinance subordinated debt with
senior debt. Third, the covenant might specify a so-called “debt basket”, which is the dollar amount of
indebtedness that can be issued without regard as to whether the issuer has the necessary interest coverage
ratio.20
This basket is intended to protect the issuer in case of an “emergency”, in which it might need to
incur additional debt. Fourth, indentures include other exceptions that apply to a specific issuer. For
instance, an issuer that historically has acquired capital assets through capital leases might negotiate for
an additional exception that would permit such transactions in the future.
Moody’s classifies debt incurrence covenants as being more protective if the covenant has caps
on bank credit facilities, debt issued by restricted subsidiaries that guarantee the issuer’s debt or on
operating leases. Moody’s negatively views covenants whose EBITDA ratio in the debt incurrence test
allows add-backs of “non-cash charges” and other items that give management the discretion to adjust the
ratio in order to issue more debt or covenants that allow debt reclassifications (e.g., that reclassify debt
that falls under the debt basket carve-out into debt that falls under the debt incurrence ratio).
20
As these baskets are based on a percentage of consolidated total (or tangible) assets, they fluctuate with the
balance sheet.
48
APPENDIX B (Continued)
Discussion of Primary Covenants
Subsidiary Debt Incurrence. The discussion of the debt incurrence above is applicable here as
well, but instead of the parent firm, the perspective is that of any subsidiary of the parent company.
Liens. The limitation on liens covenant has primary importance when it comes to limiting the
dilution of bondholders’ claims. Bondholders do not want other creditors to have senior claims on assets
should the issuer become insolvent. In a subordinated note offering, the holders typically insist that the
issuer does not grant any liens to secure other subordinated debt. Conversely, the holders of senior notes,
in an effort to remain as senior as possible with respect to the issuer’s assets, restrict the issuer from
incurring liens (which include security interests, mortgages and similar contractual or legal
encumbrances) on its assets except for limited permitted exceptions, or unless it has a proviso stating that
the issuer should simultaneously grant an equal lien for the benefit of the bondholders.
Carve-outs with these exceptions usually appear in the definition of permitted liens. The bank
credit facility carve-out is the principal and usually the largest carve-out. Other typical carve-outs are
capital expenditures (“capex”) and a liens catch-all basket. In addition to these, carve-outs can deal with
financings under one or more of the categories of permitted debt, pre-existing or acquired liens, and
refinancings of already secured debt. An important point is to determine whether the assets that are
permitted to be subject to the liens should be limited (e.g., for asset finance, only the asset acquired
should be permitted to secure this debt, but for permitted bank debt, any assets of the issuer or its
restricted subsidiaries are typically permitted collateral).
The broader the scope of the prohibitory paragraph, the stronger the limitation of liens covenant
is, conditional that the carve-outs are not excessive. Protective covenants limit the secured credit facility
debt and specify that bank credit facilities cannot be refinanced with bonds of longer duration. These
secured bonds may subordinate the original bondholders.
Asset Sales. The limitation on asset divestitures covenant restricts the non-ordinary sales of assets
in the prohibitory paragraph unless, as stated in the proviso, certain use-of-proceeds criteria are met, such
as sales proceeds being used to either pay down debt or reinvest in assets that service the debt and that are
related to the issuer’s core business. Asset divestitures are a major concern because they could remove
core revenue-generating assets that support the debt service. Although the covenant requires that sales of
assets be made at fair value and a large percentage of the consideration be received in cash, the main
purpose of the covenant is to limit the uses of proceeds in the event that the issuer does sell assets.
A high quality asset sales covenant stipulates that about 70% of the income received from the sale
is in cash or “cash equivalents” and that this cash is retained in the company for a period of one year or is
used to pay down senior debt / pari passu debt and sets a reasonably low threshold for the carve-outs. A
weak asset sales covenant includes a substantial carve-out from the “cash equivalent” consideration or no
annual caps on asset sales.
Sale/Leaseback. This covenant limits the issuer’s ability to enter into sale-leaseback transactions.
A sale-leaseback transaction, in which the issuer sells an asset and immediately leases it back, is
economically very similar to a secured financing, since the issuer will receive sale proceeds (similar to
loan proceeds) and will make rental payments over the life of the lease (similar to loan repayments). The
proviso of this covenant generally permits an issuer to enter into sale-leaseback transactions only if the
49
APPENDIX B (Continued)
Discussion of Primary Covenants
issuer has the ability to incur the related indebtedness represented by the lease obligation and is able to
incur the lien on the property securing the lease.
Since the asset has been sold and is therefore not part of the issuer’s consolidated assets
subsequent to the sale (unlike a secured financing), this covenant contains the added requirement that the
issuer treat the sale proceeds as it would in connection to any other asset sale in which the use-of-
proceeds criteria may apply. Therefore, the assessment of the level of protection provided by this
covenant is similar to that of the asset sales covenant.
Mergers. The merger / asset conveyance covenant provides important event-risk protection
against increased leveraging. It is designed to ensure that the successor company in any major M&A
transaction involving the issuer assumes the obligations with respect to the bonds (i.e., that the bond
obligations follow the assets). The covenant's proviso allows mergers if the issuer is able to incur
indebtedness under a financial ratio test on a pro forma basis. This test may allow the issuer to engage in a
merger only if the debt incurrence ratio in the Debt Incurrence covenant is improving after the
transaction. Moody’s views the protection provided by this covenant as strong if the financial ratio test is
based on multiple financial ratios (e.g., a debt incurrence ratio test and an earnings-based test, computed
both before and after the transaction). Also, the protection is better if the debt incurrence test allows an
additional dollar of debt for each additional dollar of equity proceeds. More aggressive structures have
ratios of 2 to 1.
Change of Control. The change of the indenture’s control provisions are designed to allow the
bondholder, upon a change in the ownership of the issuer, to re-evaluate the investment in the issuer
represented by the bonds. The change of control covenant protects investors against a fundamental
corporate change as well as the risk of a highly leveraged transaction. If the bondholders for any reason
prefers to exit the investment when a change in control occurs, then the issuer is required to redeem the
bonds at a purchase price that is typically slightly above the principal amount of the bond. As a result, this
covenant is also called the change of control “put.” The change in ownership is deemed to occur if a
designated group of controlling shareholders fails to continue to own at any time a majority of the
outstanding voting stock of the issuer, if the issuer is liquidated or engages in a merger or acquisition that
substantially changes the ownership structure. In the case of public issuers, the permitted holders’
ownership may fall below 50% and could, in fact, fall all the way to zero in terms of voting percentage
ownership, without triggering a change of control. In this situation, a change of control would occur only
if persons other than the permitted holders acquire (typically) 35% or more of the voting power of the
issuer.
The covenant may include a proviso stating that a change of control occurs if a merger takes
place and the company is downgraded (the negative rating condition). The covenant might also specify a
carve-out that specifies a set of permitted holders. If a majority permitted holder sells to a minority
permitted holder, the bondholder cannot exercise its put option even though a change in control has
occurred.
A change of control covenant with strong protection is one that is triggered when “all or
substantially all” of the issuer’s assets are sold, a majority of the board is replaced or a liquidation /
merger occurs. The protection is enhanced when the covenant also includes “stock for stock” mergers.
50
APPENDIX C
Variable Definitions
Variable Definition
Similarity Variables
Covenant Similarity = For each bond issue, the sum of the individual covenant similarity scores, computed as
described below.
Covenant Similarity
Pay
= For bond issue-level tests, the average of the pairwise absolute differences between
restricted payments covenant strictness score assigned to a particular bond issue by
Moody's, and its peer bonds (cross-sectional or time-series peers). The covenant
strictness scores score range from 0 to 3, with higher values indicating better covenant
protection. For the ‘peer-based’ sample, a peer bond is defined as a bond within the
same sector and broad rating category (investment grade or high yield) issued within
the calendar year prior to the issuance of a bond under consideration. For the ‘time-
series-based’ sample, a peer bond is defined as a bond issued by the same firm within
five calendar years prior to the bond issue under consideration. The similarity scores are
multiplied by -1, so that higher values indicate higher similarity.
Covenant Similarity
Change of Control
= Covenant similarity score for the Change of Control covenant, calculated for each bond
using a method similar to the Covenant Similarity Pay score described above.
Covenant Similarity
Merger
= Covenant similarity score for the Merger covenant, calculated for each bond using a
method similar to the Covenant Similarity Pay score described above.
Covenant Similarity
Debt
= Covenant similarity score for the Debt covenant, calculated for each bond using a
method similar to the Covenant Similarity Pay score described above.
Covenant Similarity
Subsidiary Debt
= Covenant similarity score for the Subsidiary Debt covenant, calculated for each bond
using a method similar to the Covenant Similarity Pay score described above.
Covenant Similarity
Liens
= Covenant similarity score for the Liens covenant, calculated for each bond using a
method similar to the Covenant Similarity Pay score described above.
Covenant Similarity
Asset Sale
= Covenant similarity score for the Asset Sale covenant, calculated for each bond using a
method similar to the Covenant Similarity Pay score described above.
Covenant Similarity
Leaseback
= Covenant similarity score for the Leaseback covenant, calculated for each bond using a
method similar to the Covenant Similarity Pay score described above.
Similar Legal Counsel
(Underwriter)
= For bond issue-level tests, the average of an indicator variable that takes on a value of
one if the legal counsel (lead underwriter) for a firm issuing a particular bond issue and
its peer bond (cross-sectional or time-series peers) is the same, zero otherwise.
Similar Size (Tangibility)
[Leverage] {Interest
Coverage}
= For bond issue-level tests, the average of the pairwise absolute differences in Size
(Tangibility) [Leverage] {Interest Coverage} for a particular bond issue and its peer
bonds (cross-sectional or time-series peers). A cross-sectional peer bond is defined as a
bond within the same sector and broad rating category (investment grade or high yield)
issued within the calendar year prior to the issuance of a bond under consideration. A
time-series peer is defined as a bond issued by the same firm within five calendar years
prior to the bond issue under consideration. The similarity scores are multiplied by -1,
so that higher values indicate higher similarity.
(Continued)
51
APPENDIX C (Continued)
Variable Definitions
Variable Definition
Firm/Bond level Variables
Size = Logarithm of the firm’s total assets, from the quarter preceding the bond issuance.
Tangibility = Ratio of fixed assets to total assets, from the quarter preceding the bond issuance.
Leverage = Long-term debt to total assets ratio, from the quarter preceding the bond issuance.
Interest Coverage = Interest coverage ratio from the quarter preceding the bond issuance, calculated as
EBITDA over interest expense.
Investment Grade = Indicator variable that takes a value of one if the issue is rated investment grade by at
least one of the three major credit rating agencies, zero otherwise.
Covenant Restrictiveness = Sum of the bond-level covenant restrictiveness scores provided by Moody's ( i.e., the
sum of covenant strictness scores pertaining to payment restrictions, merger
restrictions, change of control, asset sales, sale-leaseback, debt, subsidiary debt, and
liens. The individual scores range from 0 to 3, with higher values indicating better
covenant protection (see Appendix A for details on each covenant).
Covenant Restrictiveness
Re-weighted
= Sum of the bond-level reweighted covenant restrictiveness scores. The covenant scores
are described in the definition of Covenant Restrictiveness above. Our re-weighted
measure uses the following weights for each covenant type: payment restrictions (25%),
debt incurrence (25%), change of control (5%), merger restrictions (5%), liens
restrictions (20%), asset sales restrictions (5%), leaseback restrictions (5%) and limits
on subsidiary debt (10%).
Number Covenants = Total number of bond covenants, as identified in the Mergent FISD database.
Offering Amount = Logarithm of principal amount of the bond offering.
Maturity = Logarithm of time to maturity, in number of years.
Lender Power = Indicator variable that takes a value of one if the bond is issued during the recent
financial crisis from 2007 to 2009.
Spread = Initial yield to maturity at the time of bond issuance, minus the yield to maturity of a
treasury-bill with the closest maturity.
Volume = Logarithm of total trading volume of a bond during 30 days immediately after issuance.
.Transactions = Logarithm of total number of trading transactions of a bond during 30 days
immediately after issuance.
Insurance Holdings = Proportion of the dollar par value of the bond held by insurance companies at the
quarter end after the bond issuance quarter.
Market Spread = Mean Spread for a particular quarter and rating category to which the bond belongs at
issuance. The four rating categories are as follows: AAA to Aaa2, Aa3 to A2, A3 to
Baa2, and Baa3 to D.
Market Volume = Mean Volume for a particular quarter and rating category to which the bond belongs at
issuance. The four rating categories are as follows: AAA to Aaa2, Aa3 to A2, A3 to
Baa2, and Baa3 to D.
Market Transactions = Mean Transactions for a particular quarter and rating category to which the bond
belongs at issuance. The four rating categories are as follows: AAA to Aaa2, Aa3 to
A2, A3 to Baa2, and Baa3 to D.
52
Market Insurance Holdings = Mean Insurance Holdings for a particular quarter and rating category to which the bond
belongs at issuance. The four rating categories are as follows: AAA to Aaa2, Aa3 to
A2, A3 to Baa2, and Baa3 to D.
Number of Peers = The number of peer bonds used to compute the covenant similarity score as described
in the definition of Covenant Similarity.
53
TABLE 1
Sample Selection
This table presents the sample selection procedure.
Total number of bond issues in Moody’s CQA database 3,075
Sample after deleting international and financial sector bonds 2,427
Sample after availability of bond-level variables 2,207
Sample of bond issues for which cross-sectional similarity scores could be computed 1,727
Sample after conditioning on availability of firm-level controls 996
54
TABLE 2
Descriptive Statistics
This table provides descriptive statistics for the variables used in our tests. Panel A presents the variables that
measure similarity relative to peer j’s bonds. Panel B presents the other variables that are measured at the firm i
level. Panel C presents the frequency distribution of covenant similarity variables. Variables are defined in
Appendix C.
Panel A: Similarity Variables
N Mean Median Std. Dev.
Covenant Similarity 996 -2.842 -2.053 2.732
Similar Legal Counsel 943 0.123 0.000 0.248
Similar Underwriter 943 0.149 0.000 0.233
Similar Size 943 -0.941 -0.868 0.609
Similar Tangibility 943 -0.202 0.170 0.165
Similar Leverage 943 -0.108 -0.082 0.197
Similar Interest Coverage 943 -8.568 -2.585 27.271
Panel B: Bond i-level Variables
Size 996 9.582 9.625 1.190
Tangibility 996 0.736 0.755 0.373
Leverage 996 0.277 0.260 0.140
Interest Coverage 996 5.051 2.693 9.107
Investment Grade 996 0.843 1.000 0.364
Number Covenants 996 5.080 5.000 3.476
Offering Amount 996 12.929 12.899 0.939
Maturity 996 8.274 8.205 0.620
Lender Power 996 0.126 0.000 0.331
Spread 996 2.235 1.787 1.615
Volume 996 12.899 18.635 10.858
Transactions 996 1.770 3.970 4.922
Insurance Holdings 877 0.539 0.617 0.334
Market Spread 996 2.326 2.001 1.339
Market Volume 996 18.306 19.313 4.503
Market Transactions 996 4.277 4.578 2.303
Market Insurance Holdings 877 0.454 0.474 0.255
Panel C: Frequency Distribution of Covenant Similarity Measures
Interval
0 (0,-1] (-1,-2] (-2,-3]
Covenant Similarity (scaled by eight) 11% 84% 6% 0%
Covenant Similarity Pay 83% 8% 5% 4%
Covenant Similarity Change of Control 44% 40% 13% 3%
Covenant Similarity Merger 86% 13% 1% 0%
Covenant Similarity Debt 82% 10% 5% 3%
Covenant Similarity Subsidiary Debt 70% 18% 7% 4%
Covenant Similarity Liens 49% 28% 16% 7%
Covenant Similarity Asset Sale 89% 8% 2% 1%
Covenant Similarity Leaseback 30% 43% 16% 12%
55
TABLE 3
Determinants of Covenant Similarity
This table investigates the determinants of similarity in covenant restrictiveness. We regress Covenant Similarity on
variables that measure similarity in intermediaries, similarity in firm characteristics, as well as the level of firm
characteristics and bond characteristics. In columns 1 to 3, Covenant Similarity is measured at the firm i level, in
which we take the mean of the covenant similarity scores across each firm i – peer j pair for all j peers of firm i. In
column 4, Covenant Similarity is the individual similarity scores across each firm i – peer j pair. We estimate OLS
regressions as a panel and cluster the standard errors at the firm level. Robust t-statistics are in brackets. ***, **, and
* denote significance at the 1%, 5% and 10% levels, respectively, using two-tailed tests. Variables are defined in
Appendix C.
Firm i level Firm i level Firm i level Firm i-Peer j level
(1) (2) (3) (4)
Similar Legal Counsel 0.988** 0.975** 1.212***
[2.27] [2.25] [7.49]
Similar Underwriter 0.223 0.111 0.116
[0.64] [0.32] [1.11]
Similar Size 0.700** 0.777*** 0.700** 0.383***
[2.49] [2.82] [2.48] [5.93]
Similar Tangibility 1.943*** 2.234*** 1.928*** 1.842***
[2.71] [3.10] [2.68] [6.27]
Similar Leverage 0.634 0.785 0.631 3.138**
[0.72] [0.84] [0.72] [2.10]
Similar Interest Coverage 0.001 0.001 0.001 -0.005
[0.23] [0.26] [0.23] [-1.48]
Size 0.017 0.012 0.016 -0.093*
[0.12] [0.08] [0.11] [-1.65]
Tangibility 0.108 0.143 0.107 -0.245
[0.28] [0.37] [0.27] [-1.09]
Leverage -0.137 0.056 -0.137 -0.862
[-0.11] [0.05] [-0.11] [-1.24]
Interest Coverage 0.003 0.000 0.003 -0.011*
[0.25] [0.01] [0.22] [-1.76]
Number Covenants 0.013 0.026 0.013 -0.149***
[0.28] [0.54] [0.26] [-4.46]
Offering Amount -0.357*** -0.339*** -0.355*** -0.199***
[-3.98] [-3.53] [-3.91] [-3.77]
Maturity 0.118 0.100 0.118 0.031
[1.23] [1.07] [1.23] [0.40]
Investment Grade 4.511*** 4.529*** 4.511*** 3.766***
[7.99] [8.03] [7.98] [9.79]
Lender Power -0.062 -0.098 -0.073 0.300*
[-0.28] [-0.46] [-0.34] [1.82]
Constant -2.336 -2.266 -2.359 -0.729
[-1.21] [-1.13] [-1.22] [-0.70]
Observations 943 943 943 7,308
Adj. R2 (%)
43.5% 42.8% 43.4% 28.9%
56
TABLE 4
Consequences of Covenant Similarity: Yield Spread
This table investigates the yield spread consequences of similarity in covenant restrictiveness. In Panel A, we
regress the bond’s offering yield on Covenant Similarity, controlling for market-wide spread, firm characteristics,
and bond characteristics. We estimate both OLS and 2SLS regressions. Covenant Similarity is measured at the firm i
level, in which we take the mean of the covenant similarity scores across each firm i – peer j pair for all peers of
firm i. In Panel B, we provide a set of robustness tests in which we augment the model with additional control
variables or use a different aggregation method to calculate Covenant Similarity. We estimate each regression as a
panel and cluster the standard errors at the firm level. Robust t-statistics are in brackets. ***, **, and * denote
significance at the 1%, 5% and 10% levels, respectively, using two-tailed tests. Variables are defined in Appendix
C.
Panel A: Main Test OLS 2SLS
(1) (2)
Covenant Similarity -0.046*** -0.066**
[-2.86] [-2.33]
Market Spread 0.979*** 0.959***
[20.82] [19.31]
Size -0.023 -0.013
[-0.72] [-0.39]
Tangibility -0.240** -0.237**
[-2.34] [-2.15]
Leverage -0.577 -0.670*
[-1.50] [-1.74]
Interest Coverage -0.011*** -0.011***
[-2.84] [-2.76]
Number Covenants 0.001 0.004
[0.09] [0.20]
Offering Amount 0.020 0.003
[0.54] [0.08]
Maturity 0.310*** 0.306***
[5.79] [5.35]
Constant -2.389*** -2.235***
[-3.84] [-3.48]
Observations 996 943
Adj. R2 (%)
67.3% 65.9%
(Continued)
57
TABLE 4 (Continued)
Consequences of Covenant Similarity: Yield Spread
Panel B: Robustness Tests
(1) (2) (3)
Covenant Similarity -0.047*** -0.047***
[-2.92] [-2.88]
Number of Peers 0.011***
[2.75]
Covenant Restrictiveness -0.020
[-1.22]
Covenant Similarity Re-Weighted -0.363***
[-3.36]
Market Spread 0.978*** 0.987*** 0.975***
[20.84] [20.63] [20.70]
Size -0.024 -0.027 -0.026
[-0.80] [-0.85] [-0.84]
Tangibility -0.292*** -0.267** -0.263**
[-2.89] [-2.51] [-2.55]
Leverage -0.525 -0.539 -0.629*
[-1.37] [-1.39] [-1.66]
Interest Coverage -0.011*** -0.011*** -0.011***
[-2.63] [-2.70] [-2.74]
Number Covenants 0.007 0.013 -0.002
[0.45] [0.69] [-0.10]
Offering Amount 0.024 0.014 0.025
[0.70] [0.40] [0.70]
Maturity 0.294*** 0.304*** 0.304***
[5.44] [5.70] [5.72]
Constant -2.413*** -2.085*** -2.326***
[-3.91] [-3.08] [-3.81]
Observations 996 996 996
Adj. R2 (%)
67.5% 67.3% 67.5%
58
TABLE 5
Yield Spread Test by Individual Covenant
This table investigates the yield spread consequences of similarity in individual covenant restrictiveness. We estimate the same OLS model as in Panel A of
Table 4 but use the covenant similarity score calculated for a single covenant relative to the respective covenant for its peers. Each column corresponds to a
single covenant similarity value. We estimate each regression as a panel and cluster the standard errors at the firm level. Robust t-statistics are in brackets. ***,
**, and * denote significance at the 1%, 5% and 10% levels, respectively, using two-tailed tests. Variables are defined in Appendix C.
Covenant Similarity calculated for
Pay
Covenant
Change of
Control
Covenant
Merger
Covenant
Debt
Covenant
Subsidiary
Debt
Covenant
Liens
Covenant
Asset Sale
Covenant
Leaseback
Covenant
(1) (2) (3) (4) (5) (6) (7) (8)
Covenant Similarity -0.197** -0.000 -0.245 -0.204*** -0.088 -0.134*** -0.221*** -0.023
[-2.51] [-0.01] [-1.55] [-2.63] [-1.29] [-2.96] [-2.87] [-0.57]
Market Spread 0.974*** 0.993*** 0.985*** 0.975*** 0.986*** 1.000*** 0.988*** 0.992***
[20.20] [22.08] [21.20] [20.35] [21.06] [22.35] [21.77] [21.88]
Size -0.024 -0.030 -0.026 -0.027 -0.027 -0.035 -0.037 -0.028
[-0.74] [-0.91] [-0.80] [-0.86] [-0.83] [-1.15] [-1.15] [-0.86]
Tangibility -0.222** -0.211** -0.224** -0.232** -0.228** -0.274*** -0.231** -0.205**
[-2.17] [-2.04] [-2.14] [-2.24] [-2.18] [-2.67] [-2.29] [-2.00]
Leverage -0.640* -0.502 -0.557 -0.596 -0.517 -0.527 -0.476 -0.499
[-1.67] [-1.21] [-1.40] [-1.53] [-1.28] [-1.29] [-1.18] [-1.21]
Interest Coverage -0.011*** -0.011*** -0.011*** -0.011*** -0.011*** -0.011** -0.011*** -0.011***
[-2.83] [-2.72] [-2.71] [-2.69] [-2.76] [-2.57] [-2.66] [-2.78]
Number Covenants -0.001 0.009 0.003 -0.002 0.004 0.012 0.008 0.009
[-0.08] [0.57] [0.21] [-0.13] [0.25] [0.76] [0.49] [0.59]
Offering Amount 0.035 0.039 0.035 0.034 0.037 0.033 0.036 0.036
[0.94] [1.07] [0.93] [0.92] [1.00] [0.88] [0.95] [0.96]
Maturity 0.303*** 0.298*** 0.301*** 0.303*** 0.306*** 0.289*** 0.303*** 0.300***
[5.70] [5.55] [5.64] [5.71] [5.67] [5.36] [5.64] [5.57]
Constant -2.406*** -2.458*** -2.415*** -2.367*** -2.494*** -2.310*** -2.386*** -2.467***
[-3.86] [-3.86] [-3.81] [-3.82] [-3.90] [-3.69] [-3.86] [-3.86]
Observations 996 996 996 996 996 996 996 996
Adj. R2 (%)
67.2% 66.8% 66.9% 67.2% 66.9% 67.1% 67.0% 66.8%
59
TABLE 6
Consequences of Covenant Similarity: Insurance Company Holdings
This table investigates the consequences for insurance company holdings of similarity in covenant restrictiveness
relative to the covenants of peer companies. We regress the holdings of insurance companies on Covenant
Similarity, controlling for market-wide insurance holdings, firm characteristics, and bond characteristics. We
estimate each regression as a panel and cluster the standard errors at the firm level. Robust t-statistics are in
brackets. ***, **, and * denote significance at the 1%, 5% and 10% levels, respectively, using two-tailed tests.
Variables are defined in Appendix C.
OLS 2SLS
(1) (2)
Covenant Similarity 0.011*** 0.022***
[3.27] [3.31]
Market Insurance Holdings 0.883*** 0.865***
[-25.99] [22.77]
Size -0.031*** -0.040***
[-3.51] [-4.38]
Tangibility -0.009 -0.003
[-0.37] [-0.12]
Leverage -0.059 -0.009
[-0.93] [-0.13]
Interest Coverage 0.003*** 0.003***
[3.27] [3.24]
Number Covenants -0.009*** -0.008***
[-3.37] [-2.88]
Offering Amount -0.047*** -0.035***
[-4.27] [-2.98]
Maturity 0.053*** 0.047***
[4.65] [4.02]
Constant 0.689*** 0.683***
[3.57] [3.55]
Observations 877 825
Adj. R2 (%)
67.4% 67.0%
60
TABLE 7
Consequences of Covenant Similarity: Trading
This table investigates the trading consequences of similarity in covenant restrictiveness relative to the covenants of
peer companies. We regress the bond’s trading volume and number of transactions on Covenant Similarity,
controlling for market-wide trading, firm characteristics, and bond characteristics. We estimate each regression as a
panel and cluster the standard errors at the firm level. Robust t-statistics are in brackets. ***, **, and * denote
significance at the 1%, 5% and 10% levels, respectively, using two-tailed tests. Variables are defined in Appendix
C.
Dependent Variable = Volume Dependent Variable = Transactions
OLS 2SLS OLS 2SLS
(1) (2) (3) (4)
Covenant Similarity 0.291* 0.740* 0.130* 0.323*
[1.75] [1.90] [1.79] [1.95]
Market Volume 0.806*** 0.843***
[15.06] [14.67]
Market Transactions 0.805*** 0.833***
[13.80] [12.97]
Size 1.399*** 1.288*** 0.741*** 0.696***
[3.35] [2.88] [4.06] [3.57]
Tangibility 0.676 1.212 0.389 0.624
[0.59] [0.98] [0.77] [1.16]
Leverage -20.759*** -19.755*** -8.595*** -8.235***
[-5.03] [-4.09] [-4.86] [-3.97]
Interest Coverage -0.057 -0.058 -0.030 -0.032
[-1.09] [-1.08] [-1.21] [-1.27]
Number Covenants 0.160 0.264 0.094 0.144
[0.97] [1.31] [1.28] [1.60]
Offering Amount 0.818* 1.007** 0.588*** 0.678***
[1.89] [2.12] [2.82] [3.05]
Maturity -0.145 -0.386 -0.242 -0.338
[-0.30] [-0.77] [-1.18] [-1.56]
Constant -19.082*** -19.071** -12.234*** -12.256***
[-2.61] [-2.47] [-3.80] [-3.61]
Observations 996 943 996 943
Adj. R2 (%)
27.5% 24.6% 34.5% 32.0%
61
TABLE 8
Time-Series Covenant Similarity This table replicates the main determinants and yield spread analyses using a ‘time-series-based’ measure of
Covenant Similarity, which compares the restrictiveness of a bond’s covenants to the covenant terms in bonds
previously issued by the same firm. This sample consists of 845 bonds for which we can estimate the similarity
relative to previous bond issues. Panel A presents the descriptive statistics for the similarity variables, which are
measured relative to firm i’s previous bond. Panel B presents the determinants analysis. Panel C presents the yield
spread analyses. We estimate OLS regressions as a panel and cluster the standard errors at the firm level. Robust t-
statistics are in brackets. ***, **, and * denote significance at the 1%, 5% and 10% levels, respectively, using two-
tailed tests. Variables are defined in Appendix C.
Panel A: Descriptive Statistics
N Mean Median Std. Dev.
Similarity Variables
Covenant Similarity 845 -0.768 0.000 2.017
Similar Legal Counsel 783 0.471 0.500 0.441
Similar Underwriter 783 0.199 0.000 0.306
Similar Size 783 -0.306 -0.216 0.296
Similar Tangibility 783 -0.082 -0.059 0.089
Similar Leverage 783 -0.060 -0.045 0.058
Similar Interest Coverage 783 -4.886 -1.884 9.840
(Continued)
62
TABLE 8 (Continued)
Time-Series Covenant Similarity
Panel B: Determinants of Covenant Similarity
Firm i level
(1)
Firm i level
(2)
Firm i level
(3)
Similar Legal Counsel 0.508** 0.513**
[2.38] [2.47]
Similar Underwriter -0.076 -0.123
[-0.26] [-0.43]
Similar Size 0.735 0.628 0.727
[1.31] [1.10] [1.31]
Similar Tangibility 0.241 0.391 0.275
[0.18] [0.30] [0.21]
Similar Leverage 4.174 4.498 4.236
[1.55] [1.61] [1.58]
Similar Interest Coverage 0.005 0.005 0.005
[0.44] [0.37] [0.44]
Size 0.060 0.021 0.059
[0.62] [0.21] [0.61]
Tangibility 0.697* 0.692 0.699*
[1.70] [1.65] [1.70]
Leverage -0.114 -0.010 -0.12
[-0.11] [-0.01] [-0.12]
Interest Coverage 0.007 0.006 0.008
[0.52] [0.47] [0.53]
Investment Grade 0.023 0.035 1.552**
[0.33] [0.50] [2.23]
Number Covenants -0.184* -0.147 0.024
[-1.76] [-1.38] [0.34]
Offering Amount 0.151** 0.142** -0.186*
[2.38] [2.32] [-1.77]
Maturity 1.554** 1.622** 0.155**
[2.22] [2.37] [2.55]
Lender Power -0.241 -0.254 -0.235
[-1.07] [-1.11] [-1.05]
Constant -1.828 -1.744 -1.817
[-1.34] [-1.25] [-1.34]
Observations 783 783 783
Adj. R2 (%)
17.4% 16.2% 17.4%
(Continued)
63
TABLE 8 (Continued)
Time-Series Covenant Similarity
Panel C: Consequences of Covenant Similarity: Yield Spread
OLS 2SLS
(1) (2)
Covenant Similarity -0.097*** -0.241**
[-3.09] [-2.30]
Market Spread 0.989*** 0.943***
[18.43] [15.68]
Size -0.035 -0.016
[-0.79] [-0.31]
Tangibility -0.213* -0.101
[-1.70] [-0.58]
Leverage -0.600 -1.089*
[-1.15] [-1.90]
Interest Coverage -0.015*** -0.015**
[-2.62] [-2.30]
Number Covenants 0.005 -0.002
[0.23] [-0.09]
Offering Amount -0.002 -0.042
[-0.05] [-0.73]
Maturity 0.356*** 0.365***
[5.97] [5.78]
Constant -2.352*** -2.018**
[-2.92] [-2.15]
Observations 845 783
Adj. R2 (%)
65.7% 61.4%
