Why do Firms Issue Guaranteed Bonds? Fang Chen, Jing-Zhi Huang, Zhenzhen Sun, Tong Yu * October 4, 2017 * Chen is at the College of Business, University of New Haven. Huang is at the Smeal College of Business, Pennsylvania State University. Sun is at the School of Business, University of Massachusetts at Dartmouth. Yu is at the Car H. Lindner School of Business, University of Cincinnati. Emails: [email protected], [email protected], [email protected], and [email protected]. We appreciate the comments from Van Son Lai, Mike Eriksen, and the participants of the International Finance and Banking Society 2015 Conference, the 2015 Midwestern Finance Conference, and the 2017 Financial Management Association Meetings. All errors are our own.
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Why do Firms Issue Guaranteed Bonds?
Fang Chen, Jing-Zhi Huang, Zhenzhen Sun, Tong Yu∗
October 4, 2017
∗Chen is at the College of Business, University of New Haven. Huang is at the Smeal College of Business,Pennsylvania State University. Sun is at the School of Business, University of Massachusetts at Dartmouth.Yu is at the Car H. Lindner School of Business, University of Cincinnati. Emails: [email protected],[email protected], [email protected], and [email protected]. We appreciate the comments from Van Son Lai,Mike Eriksen, and the participants of the International Finance and Banking Society 2015 Conference, the2015 Midwestern Finance Conference, and the 2017 Financial Management Association Meetings. All errorsare our own.
Why do Firms Issue Guaranteed Bonds?
Abstract
Corporates typically use affiliated firms as guarantors to issue guaranteed bonds, combining
external financing with “internal” credit enhancements. Our finding shows that issuers with
fewer tangible assets or lower credit rating are more likely to issue guaranteed bonds. More-
over, firms with more pronounced debt overhang problems and greater managerial agency
problems tend to issue guaranteed bonds. While on average the use of guarantees improves
bond ratings, it has little impact on bond initial yield spreads.
One of the latest developments in the corporate bond market is the emergence of guaranteed
corporate bonds, also known as credit enhanced corporate bonds. Guaranteed corporate
bonds accounted for about fourteen percent of newly issued corporate bonds in terms of the
issuance amount in 1993-2012. With the guarantee arrangement, guarantors make payments
to bond investors in case of issuer defaults. Partly owing to the recent financial crisis, the use
of credit enhancement has received substantial attention (e.g., Arora, Gandhi and Longstaff,
2012; Demyanyk and Van Hemert, 2011). The spotlight is nevertheless on the packaging of
credit enhancement with commercial loans, mortgage- and asset-backed securities, municipal
bonds, and sophisticated structured products.1 Little is known about the use of guarantees
in the corporate bond market.
Guarantees used in the corporate bond market are an interesting hybrid. Guaranteed
bonds are typically insured by third party guarantors, making them different from traditional
internal credit enhancement devices which improve bond rating by pledging collaterals, im-
posing covenants to restrict issuers’ activities or offering senior securities. Even so, since
guarantors, the third party “insuring” guaranteed bonds, are either parents or subsidiaries
of issuers, guarantees are neither an external arrangement to bond issuance.
Motivated by the fact that guaranteed bonds are typically issued by affiliated firms with
a trivial explicit guarantee cost, we introduce hypotheses that associate guaranteed bond
issuance with debt overhang and agency problem. It is well noted that financial constraints
limit corporates’ ability to borrow debt from investors.2 Guarantees improve the bond
creditworthiness and corporate financing ability. However, among variety of ways to enhance
the bond creditworthiness, it is not clear which factors were the driving force for firms to
choose guarantee. Given the unique feature of internal-arrangement insurance and trivial
1On the applications of credit enhancements in mortgage backed securities, see Ashcraft and Santos,2009; Griffin and Tang (2012); Arora, Gandhi and Longstaff (2012). Related to the applications of creditenhancement in municipal bonds, refer to Braswell, Nosari and Browning (1982), Kidwell, Sorensen andWachowicz (1987), Nanda and Singh (2004).
2For the literature regarding the effect of financial constraints, see Kaplan and Zingales (1997), Lamont,Polk and Saaa-Requejo (2001), and Baker, Stein and Wurgler (2003).
1
cost, we propose that the motivation of using guarantees in overcoming financial constraints
is in two folders. On one hand, under the assumption that the use of guarantees lowers
corporate required debt payments, we show that guaranteed bond issuance alleviates financial
constraints due to debt overhang by increasing firm equityholder value. On the other hand, in
a parent-subsidiaries context, agency problem stemming from misaligned incentives between
parent firms and the subsidiaries is regarded as one of the main reasons for the inefficiency
(Bolton and Scrafstein, 1998; Scharfstein and Stein, 2000; Ozbas and Scharfstein, 2010;
Holod, 2012). In an inefficient internal market, the capital allocation may not obey the rule
on project NPVs. Rather, firms undertake projects benefiting issuing companies but harmful
to affiliated guarantors.
The simple story leads to clear empirical predictions. First, firms with greater finan-
cial constraints are more likely to issue guaranteed bonds. Second, holding the firm rating
constant, firms with more pronounced debt overhang problem are more inclined to use guar-
antee. Third, firms with greater agency problems rising from the misaligned incentives
between the parent firms and the subsidiaries have higher odds of issuing guaranteed bonds
after considering the firm rating factor.
Empirical findings offer supports to the above predictions. While we do not find evidence
that the likelihood of using guarantee is significantly related to three conventionally used
financial constraint proxies, we show firms with poorer credit rating or less collateral are
more likely to use guarantee on bonds. This is in line with the financial constraint expla-
nation. Moreover, we find that firms with greater debt overhang problem are more likely
to issue guaranteed bonds. That is, firms’ debt overhang, measured by the current value of
bondholders’ rights to recoveries in default (Hennessy, 2004; Hennessy et al., 2007), is found
to be significantly positively associated with the odds of issuing guaranteed bonds. Further,
we present the evidence that guaranteed bond issuance may be a consequence of empire-
building of the parent firms or “corporate socialism” among the subsidiaries. Specifically,
firms with more severe agency problems featured with higher free high cash flow and lower
growth opportunities are more inclined to issue guarantee bonds.
2
We perform two sets of additional analyses regarding guaranteed bond issuance for ro-
bustness. In the first, we differentiate between firms issuing guaranteed bonds only and
firms alternatively issuing guaranteed and non-guaranteed bonds within a financial year.
The result of multinominal logistic analysis shows that debt overhang is the main driver
for issuing guaranteed bonds only as well as rotating between guarantee and non-guarantee
bonds. Interestingly, the agency problem plays a significant role in the firms’ odds in firms
issuing guaranteed bonds only, not in firms issuing both guaranteed and non-guaranteed
bonds. In the second analysis, we address the concern that COMPUSTAT data reflects the
consolidated financial information of corporates with a parent-subsidiary structure. We use
the minority interest to estimate the financial variables at the parent firm level and then
rerun the determinants analysis. Using the estimated income at parent firm level, we distin-
guish the operating firms from the financial holding firms. The result of the regressions with
estimated variables at parent firm level and the dummy variable for the operating firms is
consistent with that of the regression with the consolidated financial data.
Given the fact that guaranteed bonds are issued with alternative drives, one may wonder
whether the rating agency and the market have captured the incentives. We shed light on
this question by performing further analysis to test the sequential rating and yield effects
of guaranteed bond issuances. The result reveals that on average guarantee improves bond
ratings but has no effect on initial yield spreads. More interestingly, when we respectively
examine the individual effects of issuers’ financial constraints, debt overhang, and managerial
agency problems on the relation between guarantee use and bond yield spreads, we find that
guarantees used by bond issuers facing greater financial constraints or with more pronounced
debt overhang indeed reduce yield spreads, while guarantees used by bond issuers with more
severe managerial agency problems increase yield spreads. The offset of two effects provides
a plausible explanation for no effect on yield spreads from guarantees overall.
To summarize, guarantees enhance corporate debt capacity by allowing issuers to reach
collateral resources beyond corporate borders. Such resources, however, are from affiliated
firms. Our study focuses on the hybrid nature of guaranteed bonds. We show that, acting
3
like a double-edged sword, guaranteed bonds have the advantage to expand corporate debt
capacity and alleviate debt overhang but its use may aggravate the agency conflict between
parent companies and subsidiaries. The findings add to the stream of research on the effi-
ciency of the internal capital market (Bolton and Scharfstein, 1998; Scharfstein and Stein,
2000; Ozbas and Scharftein, 2010).
The remainder of the paper is organized as follows. Section 2 provides the institutional
background of guarantees used in the corporate bond market and reviews the relevant liter-
ature. In Section 3, we introduce the hypotheses. Section 4 describes our sample and data
used in the empirical analysis. Section 5 presents empirical findings. Section 6 concludes.
2 Background
We begin this subsection with an example of a guaranteed corporate bond. On September
12, 2000, MGM Mirage issued a 10-year 8.5% senior bond using all its wholly owned do-
mestic subsidiaries to provide a guarantee. The aggregate par value of the bond issuance is
850,000,000 USD. The guarantee is an unsecured senior obligation of the guarantor. At the
time of bond issuance, MGM Mirage has a rating right below the investment grade: Ba1 by
Moody’s3 while the newly issued bond is rated at an investment grade, BBB- by S&P and
Baa3 by Moody’s.
The use of guarantees on newly issued bonds has increased substantially since its inception
in the early 1990s. Reported in Table 1, based on par value, the market share of the
guaranteed bonds in all US corporate bonds issued in a year rises from 1.4% in 1993 to 18%
in 2012. Guaranteed bond issues peaked in 2009, with 37% of US corporate bonds being
guaranteed. The aggregate par value of US corporate bonds during the period 1993-2012 is
roughly $17 trillion, of which 14% (i.e., $2.3 trillion) were issued with guarantees.
Based on the Mergent Fixed Income Securities database (Mergent FISD), guarantees
3Issuer ratings are assessed based on issuers’ ability to honor senior unsecured financial obligations andcontracts. Issuer ratings share the same scheme as corporate bonds. Based on Moody’s rating scheme, Baa3is the lowest investment grade.
4
are one of three types of credit enhancements for corporate bonds, in addition to bond
insurance and letters of credit. In terms of issuance amount, guaranteed bonds account
for over 96% of corporate bonds with credit enhancement in the period from 1993 to 2012.
Corporate bonds issued with bond insurance and letters of credit merely account for 3% and
less than 1%, respectively, of the market. Documented in Nanda and Singh (2004), bond
insurance is frequently used in the municipal bond market; roughly 50% of municipal bonds
are packaged with bond insurance. Nanda and Singh (2004) suggest that the tax-exempt
benefit of municipal bonds can be extended through third-party insurance, and is the main
reason for the frequent use of bond insurance in municipal bonds. Corporate bonds are not
eligible for tax exemption, thus tax benefit does not provide incentive to corporates to use
guarantee on bonds.4
The super majority of guarantors of guaranteed corporate bonds are either parent com-
panies or subsidiaries of bond issuers. A clear advantage of using internal resources from
affiliated firms to guarantee a corporate bond is its efficiency – making use of available corpo-
rate resources. While a parent firm and its subsidiaries are separate legal entities, guarantee
bounds their risk together. For example, without guarantees, if subsidiaries are in default,
subsidiary bondholders do not have any recourse to the parent companies unless the parent
companies are involved in some wrong-doing (Thomson, 1991). With a guarantee from the
parent company, the subsidiary debtholders have recourse to its parent guarantors should
the subsidiary default. In practice, most of the guarantees to the public issuers are provided
jointly by most or all of their domestic subsidiaries. The guarantees are normally senior
obligations of the guarantors, ranked equally with all other existing and future senior debt
of the guarantors in right of payment. It is also a common practice to contain the covenants
in the indenture to limit the payments of the guarantors, such as dividend payout, share
repurchase or making principle payment prior to the schedule, among other arrangements.
Consequently, this arrangement helps to reduce credit risk of guaranteed bonds.
Alternative types of credit enhancements differ in issuance expenses. In early years the
4Our sample only contains 4 bond issues backed by bank letter of credits, out of 11,226 corporate bondsissued with credit enhancements. As a result, we focus our comparison on bond guarantees and insurance.
5
parent/subsidiary guarantee was treated as an internal arrangement which requires a filing
to the Securities and Exchange Commission (SEC) (no such filing requirement for insurers
or banks when they offer credit enhancements). Nevertheless, the SEC filing expense for
guaranteed bonds was as trivial as a few thousand dollars. The requirement of filing was
abandoned by the SEC in 2003, thus no more filing expense is associated with guarantees.
The other direct floatation cost is the guarantee fee. As the internally arranged guarantees
are considered as an arm’s-length transaction, parents/subsidiaries guarantee fee is seldom
included in the contract. In contrast, the insurance fee is explicit and ranges from 0.5 to
2.0 percent of total debt (Cole and Officer, 1981). In summary, as an internal arrangement,
guarantees to corporate bonds virtually have no direct cost. This is different from bond
insurance and letters of credit, which typically involve explicit expenses. Nevertheless, as
indicated in the later analysis, the use of guarantees is not costless – indirect costs may arise.
Like the example discussed in the beginning of the subsection, credit ratings of guaranteed
bonds differ from those of bonds with insurance or letters of credit. At the time when
bonds are issued, bond insurers and letters of credit providers typically have an AAA rating.
Therefore bonds backed up by insurance or letters of credit have an AAA rating. By contrast,
guarantors and guaranteed bonds have their ratings varying from AAA as the highest to D
as the lowest.
Moreover, the interconnection between issuers and guarantors has a potential effect on
credit ratings of bonds. For example, if a parent rating is ‘CCC+’ or lower while a subsidiary
has a stand-alone credit rating of ‘B-’ or higher, the subsidiary’s final credit rating could
be lowered accordingly due to the concern of extraordinary negative intervention from the
parent firms. Guarantee strengthens the interconnection. When the subsidiary, acting as a
guarantor, is downgraded, the rating agency would subsequently reevaluate the bond and
lower the rating of the guaranteed bond. The liability entails the default risk to the guarantor.
For example, Vitro, the largest manufacturer of glass containers and flat glass in Mexico,
suffered a dramatic decline in operating income as a result of the global economic and
financial crisis that began in 2008. The decline in its operating income caused Vitro to
6
default on certain financial obligations, including $1.216 billion in outstanding notes. Those
notes were unsecured, but guaranteed by certain subsidiaries of Vitro, including some located
in the United States. The default caused the involuntary bankruptcy of its U.S. subsidiaries
(Porzecanshi, 2011).
3 Hypothesis Development
When firms have free access to capital, guarantees and credit enhancements could play a
little role in the corporate bond market and they would not be introduced in the first place.
The real market, nonetheless, is far from being perfect. As noted in the existing literature,
financial constraints (Kaplan and Zingales, 1997; Lamont, Polk and Saaa-Requejo, 2001;
and Baker, Stein and Wurgler, 2003) and debt overhang (e.g., Hennessy, 2004; Hennessy
et al., 2007) are major detriments to corporate financing activities and their investments.
By issuing guaranteed bonds, firms internalize external funding activities. Therefore, the
choices between guaranteed and non-guaranteed bonds, therefore, reflect corporate status
quo prior to bond issuance.
First consider the effect of financial constraints on the issuance of guaranteed bonds.
Consider a financially constrained firm has a positive NPV project. The project’s NPV is q
(> 0) before adjusting the funding cost. Owing to financial constraints, the firm relies on
capital infusion to materialize the investment opportunity. There is a wedge between the
cost of internal capital and that of external capital, ci and ce respectively. The value of the
project, q, is between ci and ce. That is, ci < q < ce. Clearly, the firm would invest in the
project when it has internal capital but it has to forgo the opportunities when it has to raise
capital externally.
Using subsidiaries as guarantors, corporates issue guaranteed bonds to lower the external
capital cost thus undertake the positive NPV project. Consequently, we expect that the
greater financial constraints, the stronger incentive of the firm to use guarantees. This gives
rise to the first hypothesis.
7
H1. Firms with more financial constraints are more likely to issue bonds with guarantees,
all else being equal.
An alternative driver for a firm to forgo a positive NPV project is the so-called debt
overhang problem. First suggested by Myers (1977), equityholders could forgo the positive
NPV project if the return of such investment goes to bondholders. Note that debt overhang
is harmful to both bondholders and equityholders because when rationally expecting equi-
tyholders to have the underinvestment incentive, potential bondholders would be reluctant
to lend their money or charge a high cost of debt at issuance. Myers (1977) suggests various
remedies, such as including protective covenants to restrict equityholders’ activities in order
to alleviate such a debt overhang problem. In spite of variations, the essential purpose of
the proposed remedies renders equityholders less likely to forgo positive investment projects.
Aligned with this idea, Stulz and Johnson (1985) suggest that firms may issue secured bonds
to reduce the debt overhang problem in the sense that because secured debt has collateral,
secured creditors rely less on the new investments than unsecured creditors when firms are
at default, thus equityholders are less likely to forgo the investment opportunity. Alterna-
tively, Mayers and Smith (1987) suggest to include a bond covenant that requires the issuer
to purchase protective coverage. The protection pays off the loss or makes up the cash flow
shortfall, reducing the expected downside loss of the project. This results in greater incentive
for equityholders to invest in the positive NPV project.
Issuing guaranteed bonds potentially combines the benefits of secured bond issuance and
protective coverage. When the parent defaults, the bond guarantors hold the responsibility to
make promised payments – This makes a guaranteed bond like a “secured” bond. Guarantees
from affiliated firms also act as if a standby insurance to the bond issuer. Thus, we expect
that firms issue guaranteed bonds to address the debt over hang problem. This gives rise to
the second hypothesis.
H2. Firms with more pronounced debt overhang problem are more likely to use guarantees
on bonds, all else being equal.
8
Despite that there is no or little explicit fee for the the guarantee provided by affiliated
firms, the use of guaranteed bonds to overcome financial constraints is not completely free of
costs, such as that the internal arrangement of guaranteed bonds may restrict guarantors to
issue new bonds. Especially in the parent-subsidiary context of guarantee, the incentive of a
parent firm may be misaligned with that of subsidiaries, regardless of the cost of guarantee
issuance to subsidiaries. As a result, the allocation of internal resources in the form of a
guarantee may not follow the investment opportunities. Instead, the parent company could
use the guarantee for an empire-building purpose5.
When there are financial constraints for conventional bond issuance and the implicit cost
of guarantee is not the concern of the parent company due to the agency conflict, guarantee is
a preferred way to raise capital even when the benefit from the new investment opportunity
is negative. This reasoning results in a link between corporate agency conflicts and incentive
to issue guaranteed bonds. This leads to our third hypothesis.
H3. Firms with greater agency problem are more likely to issue guaranteed bonds, all else
being equal.
Finally we propose a hypothesis related to yield spreads of guaranteed bonds. For firms
facing financial constraints from default risk, as the use of internal guarantees reduces the
default risk and thus mitigates constraints, yield spreads of guaranteed bonds are naturally
lower than those of non-guaranteed bonds, all else being equal.
H4a. Guaranteed bonds have a lower yield spread than non-guaranteed bonds when issuers
face financial constraints, all else being equal.
The debt overhang is an internal constraints to the investment due to the conflict be-
5For example, Bolton and Scharfstein (1998) point out that allocating capital to divisions with oppor-tunities aligns with parents’ empire-building preference. Scharfstein and Stein (2000) argue that a two-tieragency problem, stemming from misaligned incentives at parents and at divisions, is necessary for “corporatesocialism” in internal capital allocation. Ozbas and Scharfstein (2010) find that the ownership stakes of topmanagement have a positive relation with the extent of Q-sensitivity differences, suggesting that agencyproblem leads to the inefficient capital market.
9
tween bondholders and equityholders. Guarantees alleviate the debt overhang problem by
increasing the equityholders value and therefore increase the chance of investing on positive
NPV projects. The higher cost from debt overhang, the higher benefit from guarantee and
the lower yield spread is required by rational bond investors.
H4b. Guaranteed bonds have a lower yield spread than non-guaranteed bonds when issuers
have more debt overhang, all else being equal.
However, under the agency conflict scenario, the purpose of issuing guarantee bonds to
overcome the financial constraints is mainly for empire building. A rational bond investor
may require higher yield due to the risk from the misalignment of the growth opportunities
and guarantee bond issuance.
H4c. Guaranteed bonds have a higher yield spread than non-guaranteed bonds when is-
suers have greater agency problem, all else being equal.
Taken together, the combined effect of guarantees on debt value can be positive or neg-
ative which remains as an empirical question.
4 Data
4.1 Sample
This study utilizes the Mergent FISD database which provides issues and issuers information
for bonds issued by both public and private firms. We select U.S. corporate bonds including
U.S. corporate debenture, corporate midterm notes (MTNs), asset-backed securities and
other corporate bonds issued by U.S. firms. Mergent FISD contains information on whether
corporate bonds were issued with any type of credit enhancements: (i) guarantees, (ii) letters
of credit (LOC) and (iii) bond insurance.
Our sample ranges from 1993 to 2012. Among a total 123,034 corporate bonds, 11,226
corporate bonds were issued with credit enhancements. Specifically, there were 11,551 guar-
10
anteed bond issues, 441 issues with bond insurance, and 4 issues backed by bank LOC. We
identify the guarantors of the issues with guarantees via two ways. First, Mergent FISD
directly lists most guarantors as “Subsidiaries”. Second, the database lists the parent of the
issuers. If a parent’s identification number matches a guarantor’s identification number, the
bond was guaranteed by the parent firm of the issuer. If guaranteed bonds have no infor-
mation on guarantors, we manually search issuers’ SEC filings. The guarantors’ information
is disclosed in the 424B, S-4, 8-k, 10-Q or 10-K. This study investigates the public issuers
only. We restrict our sample to the issuers that are listed at the time of bond issuance by
matching the CUSIP of the issuers in FISD with that in the Center for Research in Security
Prices (CRSP) database.
Consistent with prior studies, e.g., Custdio, Ferreira, and Laureano (2013) and Becker
and Josephson (2016), we exclude financial firms (SIC codes 6000-6999) and regulated utility
firms (SIC codes 4900-4999) because they have significantly different capital structures and
are subject to different regulations. We further exclude bonds issued with bond insurance or
letters of credit (LOCs) to focus on the use of guarantee. There are 8,797 corporate bonds
issued by public firms, of which 825 are guaranteed bonds.
To facilitate the analysis, we remove bonds when issuers’ total assets, firm ratings and
bond ratings are not available. We measure firm ratings using the most recent S&P long
term issuer credit ratings right before bond issuance (Frating(AAA=26,D=1)) in Compustat,
also in line with prior studies such as Norden and Kampen (2013), Alp (2013), and Baghai,
Servaes and Tamayo (2014). We obtain bond ratings at issuance from Mergent FISD. As
there are ratings from multiple rating agencies, we use the S&P rating if it is available for a
specific bond. In case the S&P rating is missing in Mergent FISD, we alternatively use the
Moody’s rating. If both S&P and Moody’s ratings are missing, we use the Fitch’s rating.
The highest rating number is 26 (equivalent to S&P’s AAA) and the lowest rating number
is 1. Our treatments result in a final sample consisting of 7,201 corporate bonds, of which
731 bonds with guarantees (see Figure 2).
Since all guaranteed bonds are guaranteed by either the subsidiaries or the parent firms,
11
to run a fair comparison, we require non-guaranteed bonds in our sample to hold similar
corporate structures. We use Capital IQ to search relevant information manually. Capital
IQ lists the parent firms and the subsidiaries in its corporate tree section. In the final
sample, 5,949 bonds were issued by firms which have parent firms or subsidiaries, of which
647 bonds were packed with guarantees. This is the subsample used in the regressions of
the determinants of guarantee use. Figure 2 provides a detailed description of the number
of bonds with guarantee issued by publicly listed companies in the sample.
We obtain accounting data from Compustat, stock return data from CRSP, and bond
issuance data from Mergent FISD. From FISD, we obtain the bond issuance information
such as time to maturity, initial bond yield spread, bond ratings, the indicators for callable
bonds, putable bonds, and secured bonds, and so on. Then we merge sample bonds with
the Compustat data by the issuer ID. We obtain firm variables from the Compustat data
including firm rating, total assets, operating income, tangible assets, sales, age, dividend,
debt, cash flow and free cash flow. The accounting variables are at the fiscal year end before
the debt issuance.
As Compustat provides the financial data from the consolidated statements, the financial
variables are measured at the group level except the issuer’s firm rating from S&P. When
S&P assesses the credit rating of a firm within a parent-subsidiary structure, S&P considers
the firm’s stand-alone credit profile and the support or intervention from other firms within
the group (see Standard & Poor’s, 2013). We consider having no financial variables available
at the parent firms level as a limit of our data when we run the regressions on the parent
firms.6 In order to examine the validation of our test, we use the minority interest method to
approximately estimate the financial variables in the parent firms only and run a robustness
check.
6We also checked FactSet, one database available to academics that includes information for both parentcompanies and subsidiaries. Unfortunately, FactSet has very little financial data on subsidiaries available.We find that data are available only for those subsidiaries that used to public and only for the period whenthey were public.
12
4.2 Summary Statistics
In Table 1, we present the distribution of guaranteed bonds by both public and private firms
in Mergent FISD. It shows that the fraction of guaranteed bonds in Mergent FISD is about
14% (9%) in terms of the aggregate par value of bonds (the number of bonds). Focusing on
the public firms, the percentage of guaranteed bonds issued by public firms is 9% (8%) in
terms of the aggregate par value (number) of bonds. The fraction of aggregate par value of
bonds issued by public firms ranges between 1.19% in 1994 and 24% in 2009.
Figure 3 presents the percentage of guaranteed bonds in terms of aggregate issuance
amount over time. Shown in Panel A, the percentage of guaranteed bonds issued by all firms
increases over time and peaks in 2009. Panel B shows that the percentage of guaranteed
bonds issued by public firms varies and peaks in 2009 as well. This finding is consistent with
that in Table 1.
In Table 2, we provide the summary statistics of guaranteed bonds and non-guaranteed
bonds as well as their issuers’ characteristics. In both panels A (for non-guaranteed bonds)
and B (for guaranteed bonds) of the table, the first three columns report the distributions
(mean, median and standard deviation) of bond issuer and issue attributes, under the heading
“All”. The average firm’s credit rating (16.13, corresponding to S&P’s BB+, relative to 26
for an AAA rating) of guaranteed bonds is lower than that of non-guaranteed bonds (17.80,
corresponding to S&P’s BBB). Given the fact that the threshold point between investment
grade bonds and speculative grade bonds is BBB- by S&P (the numeric rating of 17.00),
the mean firm rating for guaranteed bonds is right below the threshold and the mean firm
rating for non-guaranteed bonds is right above. Not tabulated, we find the correlation
between rating numbers and a dummy variable of whether a guaranteed is used to be -0.15,
suggesting that, without considering issuer and bond characteristics, the average rating of
guaranteed bonds is unconditionally lower than that of non-guaranteed bonds.
Besides issuer rating, it is also shown in the table that the guaranteed bond issuers have
slightly lower Tobin’s Q (1.97) than non-guaranteed bond issuers (2.07). Guaranteed bond
issuers also make less profit, borrow more debt, and hold fewer assets than non-guaranteed
13
bond issuers. Taken together, the comparisons of issuer characteristics reveal that guaranteed
bond issuers unconditionally have a poorer growth prospect and worse business condition
than non-guaranteed bond issuers.
The comparisons of bond characteristics are also reported in Table 2. The average yield
spread of guaranteed bonds (313.62 basis points) is much larger than that of non-guaranteed
bonds (215.83 basis points). Interestingly, guaranteed bonds typically have larger par value
and shorter time to maturity than non-guaranteed bonds.
Next, we take a close look of the distribution of guaranteed and non-guaranteed bonds
by dividing them into eight sub-groups based on the issuers’ ratings: AAA, AA, A, BBB,
BB, B, CCC and others. We compute the percentage of the aggregate par value in each
issuer’s rating for guaranteed bonds and non-guaranteed bonds respectively. This is plotted
in Figure 4 – the majority of guaranteed bonds were issued by firms with the ratings of BBB
or BB while most of the non-guaranteed bonds were issued by firms with the ratings of A or
BBB.
We also report, in Table 2, the result of univariate comparisons for the variables between
guaranteed bonds and non-guaranteed bonds in the above four firm rating groups. The
comparison of all variables between guaranteed bonds (issuers) and non-guaranteed bond
(issuers) in each rating group is consistent with the overall comparison reported in the first
three columns. Nevertheless, the magnitude of the difference between the guaranteed bonds
and the non-guaranteed bonds is dynamic in each firm rating group. The mean Tobin’s Q
of guaranteed bond issuers is 2.09 and that of non-guaranteed bond issuers is 2.49 in the
AAA-A group, while it is 1.78 for both guaranteed bond issuers and non-guaranteed bond
issuers in the B-CC group. In the AAA-A group, the mean yield spread of guaranteed bond
issuers is 162.52 basis points (bps) and that of non-guaranteed bonds issuers is 113.19 bps ,
while in the B-CC group, the mean yield spread is 589.50 bps for guaranteed bond issuers
and 479.39 bps for non-guaranteed bond issuers.
14
4.3 Regression Variables
Now, we discuss all the variables to be used in hypothesis tests conducted in Section 5. To
be specific, in order to examine the effect of financial constraints on corporate guarantee
use (the first hypothesis), we include the following variables in panel regressions. The main
dependent variable is GT, an indicator variable equal to one if it is issued with a guarantee
and zero otherwise. The main independent variables include financial constraint measures,
firm characteristics and bond characteristics. Financial constraint measures are: the KZ
index (KZ ), the WW index (WW ), the SA index (SA), Tangible (Tangible) and issuer
credit rating (Frating). We follow Lamont, Polk, and Sa-Requejo (2001) to construct the
size (Size), profit (Profit) and leverage (Leverage) to capture any variation in firms’ perfor-
mance and creditworthiness. Bond characteristic variables include time to maturity (Term),
bond issuance amount (Par), the dummy variable for secured bonds (Secure), the dummy
variable for callable bonds (Call), and the dummy variable for putable bonds (Put). Finally,
we control for the fixed industry and the fixed year effect. Industries are classified based on
the first two digits of firms’ Standardized Industry (SIC) Codes.
The regression results are reported in Table 7. In Column 1, we include the guarantee
dummy variable (GT ) only. R-Squared of the regression is 0.15. The standardized beta
of GT is significantly negative, consistent with our earlier finding that, unconditionally,
guaranteed bond issuers have a poorer rating than non-guaranteed bond issuers.
Next, we control for the influence of issuers’ ratings to see the impact of GT on bond
ratings. In Column 2, we include two additional variables related to issuer ratings: Frat-
ing(AAA=26,D=1) and InvGrade. The result shows the standardized beta of the guarantee
dummy turns to be positive, significant at the 1% level. The finding states that, conditional
on issuer ratings, the use of guarantees improve bond ratings. It also is worth noting that
the R2 of the regression reported in Column 2 is 0.939, suggesting that bond ratings are
primarily driven by issuer ratings.
Further we include a set of firm characteristic variables in the analysis reported in Column
3 and include both firm and bond characteristic variables in Column 4. This is to isolate the
GT effect from the potential effects of firm and bond characteristics. In both columns, the
standardized betas of GT are positive and significant at the 5% level, while the increases
in R2 from that of Column 2 is virtually non-existent, further confirming that the primary
role of issuer ratings in bond rating determinations. Despite so, our analysis reveals that
the guaranteed use has a robust and significant role in determining bond ratings – after we
control for firm and bond characteristics, the use of guarantee on average increases bond
rating by 0.11 of a rating notch.
26
5.4 Effect of Guarantee Use on Yield Spreads
We further examine if the guarantee use affects initial yield spreads of individual bonds. We
adopt the following regression:
Yield Spread = α0 + α1GT + α2Controls + ε (7)
where a bond’s yield spread at issuance comes from Mergent FISD. It is the difference
between the yield of the benchmark treasury issue and the bond’s offering yield expressed
in basis points.
The regression results are reported in Table 8. Similar to Table 7, the first column solely
involves the guarantee dummy variable (GT ). The standardized beta on GT is significantly
positive. That is, unconditionally, guaranteed bonds have a higher yield spreads than non-
guaranteed bonds, a finding consistent with the rating analysis.
Interestingly, after we add two variables related to the firm rating: Frating and InvGrade
in Column 2, the standardized beta of GT is no longer significant. We continue to obtain
an insignificant standardized beta of GT after including both firms and bond characteristic
variables, which is reported in Column 3. The result shows that, conditional on issuer ratings
and issuer and bond characteristics, the guarantee use no longer has impact on bond yield
spreads, a result different from the rating analysis reported in Table 7.
To understand on the results reported in Columns 2 and 3, we look into the specific
roles played by financial constraints, debt overhang, and managerial agency problem in
the impact of guarantee use on bond yield spreads. We respectively interact the dummy
variable GT with the dummy variable LPPE (i.e., low tangible assets) for more financial
constraints, the dummy variable HDOH (i.e., high DOH) for more pronounced debt overhang
and the dummy variable LQ*HFCF (i.e., Low Q*high FCF) for greater agency problem. We
separately include one of the three interaction terms in the regressions while excluding GT
from the regression.
In Column 4, we augment regression setup in Column 3 by additionally including GT*LPPE.
We find that the standardized beta of GT*LPPE is negative and it is only marginally sig-
27
nificant (at the 10% level). Thus, there is some weak support to the Hypothesis 4a. Next,
in Column 5, we alternatively include GT*HDOH and find that the standardized beta of
GT*HDOH is negative and significant at the 5% level. The use of guarantees lowers bond
yield spreads and increases the bond value after we have controlled for other factors. The
evidence support to the Hypothesis 4b. In Column 6, we include GT*LQ*HFCF and the
standardized beta of GT*LQ*HFCF is significantly positive. The result shows that the
guarantee use in firms with greater agency problem increases the yield spread and thus de-
creases the bond value. The evidence support to the Hypothesis 4c. Finally, in Column 7,
we include the three interaction terms together in one regression. The result in the column
is similar to those reported in earlier columns.
Putting all together, the analysis in Sections 5.3 and 5.4 shows that on average guarantee
improves bond ratings while such use has little impact on initial yield spreads. However,
guarantees used by bond issuers facing greater financial constraints or with more pronounced
debt overhang indeed reduce yield spreads, while guarantees used by bond issuers with more
severe managerial agency problems increase yield spreads. These two inverse effects cancel
out in a sample where all bond issues are pooled together.
6 Conclusions
This paper examines U.S. firms’ issuance of guaranteed bonds. We focus on a unique feature
of guarantee on corporate bonds – the guarantors of these bonds are typically affiliated firms.
The key advantage of using internal guarantee for credit enhancement is its relatively trivial
explicit issuance cost. A simple tradeoff motivate firms to issue guaranteed bonds. On
one hand, the use of guarantees potentially reduces corporate financial constraints and debt
overhang and increases firms’ ability in investing in favorable growth opportunities. Thus,
firms with greater financial constraints and stronger debt overhang problems are more likely
to issue guaranteed bonds. On the other hand, as the explicit cost of guarantee issuance is
low, firms with greater agency conflicts between the parent companies and subsidiaries are
28
also more likely to issue such bonds for the purpose of empire building.
Empirical findings support our predictions. Guaranteed bonds are predominantly issued
by low creditworthiness firms featured with low rating and less tangible assets. We also find
that firms with more pronounced debt overhang problem tend to issue guaranteed bonds
to alleviate the problems, and that firms with poorer investment opportunities but greater
agency conflicts are more inclined to use guaranteed bonds. Moreover, we find that on
average guarantee improves bond rating but has little effect on the initial bond yield spread.
Further analysis suggests that the overall decreasing yield spread effect from guarantee by
firms with more pronounced debt overhang is offset by the overall increasing yield spread
effect from guarantee by firms with more severe agency problem.
29
Appendix A: Main Variables Used in the Analysis
Variable Definition
GT Dummy variable equal to one if the bond is issued with a guarantee and zero otherwise.
Financial Constraints MeasuresFrating(AAA=26,D=1) The most recent S&P long term issuer rating before a bond issuance.Tangible The ratio of the property, plant and equipment to total assets.WW The WW index of Whited and Wu (2006). Calculation method is provided at Section 4.3.SA The SA index of Hadlock and Pierce (2010). Calculation method is provided at Section 4.3.KZ The KZ index of Kaplan and Zingales (1997). Calculation method is provided at Section 4.3.LPPE All firms are sorted into three groups based on the issuers’ property, plant and equipment (PPE).
It is a dummy variable that equals to one if a firm is in the lowest PPE group and zero otherwise.
Debt Overhang MeasuresDOH The measure of a firm’s debt overhang. It is calculated using the approach by Hennessy (2004)
and Hennessy, Levy, and Whited (2007).HDOH All firms are sorted into three groups based on the debt overhang measure. It is a dummy
variable that equals to one if a firm is in the highest overhang group and zero otherwise.
Agency Problem MeasureLQ*HFCF The measure of a firm’s agency problem. All firms are sorted into three equal numbered
groups based on the issuers’ Q and their free cash flow respectively. It is a dummy variable thatequals to one if the issuer is simultaneously in the bottom Q tercile group and top free cash flowtercile group and zero otherwise.
Firm CharacteristicsSize Logarithm of total book value of assets.Profit Ratio of the operating income before depreciation to total assets.Dividend Dummy variable for a firm equal to one if the firm paid dividend and zero otherwise.Leverage Ratio of total debt to total assets.Q Ratio of market value to book value computed as the total assets minus total book.
value of equity plus market capitalization and then divided by total assets.FCF Free cash flow is computed as the EBITDA minus the sum of XINT, TXT, DVC, and DVP and
then divided by total assets.InvGrade Dummy variable equal to one if a firm has a investment grade rating and zero otherwise.
Bond CharacteristicsYield Spread The yield difference between a bond and the corresponding treasury bond with matching maturity
at the time of issuance.Term Logarithm of time to maturity in years.Par Logarithm of par value in billion dollars.Call Dummy variable equal to one if a bond has a Call provision and zero otherwise.Put Dummy variable equal to one if a bond has a Put provision and zero otherwise.MktYld The market yield difference between Moody’s corporate bonds and corresponding Treasury bonds.
30
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32
Table 1: Statistics for Guaranteed Bonds
This table reports the total number and the aggregate par value of both newly issued corporate bonds (All)and newly issued guaranteed corporate bonds (GT) included in the Fixed Income Securities Database (FISD)from 1993 to 2012. Par value is in billion dollars. The statistics are reported separately for public firms andall firms (including both public and private firms).
Public Firms All Firms
Number of Issues Par Value Number of Issues Par Value
This table reports the cross-sectional mean, median, and standard deviation of the main variables used in the analysis for non-guaranteedbonds (in Panel A) and guaranteed bonds (in Panel B) respectively. The main variables include the ratio of the operating income beforedepreciation to total assets (Profit), the ratio of total debt to total assets (Leverage), total assets in billion dollars (Size), the most recentS&P long term issuer rating before issuance (Frating(AAA=26,D=1)), firm Tobin’s Q (Q), yield spread at issuance (Spread, in basis points),the bonds’s time to maturity in years (Time to Maturity), and par value in million dollars (Par Value). The definitions of the variables areprovided in Appendix A. We then sort sample bonds into four rating groups (AAA-A, BBB, BB, B-CC) and report the mean and medianof the variables in each group. AAA-A group include all bonds with the ratings from AAA to A. BBB (BB) groups include bonds with theratings of BBB (BB). B-CC group includes bonds with the ratings from B to CC. The sample period is from 1993 to 2012.
Panel A: Non-Guaranteed Bonds
All AAA-A BBB BB B-CC
Mean Median Std dev Mean Median Mean Median Mean Median Mean Median
Table 3: The Effect of Financial Constraints, Debt Overhang and Agency Problem onCorporate Guarantee Uses
This table shows the results of logistic regressions using the sample bonds issued by public firms withsubsidiaries. The dependent variable is GT, an indicator variable equal to one if it is issued with guaran-tee and zero otherwise. The main independent variables include five financial constraint measures (WW,SA, KZ, Tangible and Frating(AAA=26,D=1)), debt overhang measure (DOH), agency problem measure(LQ*HFCF). The control variables are Size, Profit, Free Cash Flow (FCF), Dividend, MktYld, Term, Par,Call, and Put. All variables are defined in Section 4. All specifications include industry fixed effect and yearfixed effect. Standardized betas are reported and p-value are presented in parentheses. ***, **, and * meansignificant at the 1%, 5%, and 10% level, respectively.
Fixed industry Y Y Y Y Y Y YFixed year Y Y Y Y Y Y Y# of Obs. 5814 5949 5154 5767 5767 5767 5767Likelihood Ratio 348.83 351.28 336.0839 404.57 534.03 465.92 470.12Pseudo R2 0.058 0.057 0.059 0.067 0.081 0.087 0.090
35
Table 4: Time Variation of Guarantee Use
This table shows the result of logistic regression on the time variation of guarantee use. The dependentvariable is GT, an indicator variable equal to one if it is issued with guarantee and zero otherwise. Themain independent variables include five financial constraint measures (WW, SA, KZ, Tangible and Frat-ing(AAA=26,D=1)), debt overhang measure (DOH ), agency problem measure (LQ*HFCF ). The controlvariables are Size, Profit, Free Cash Flow (FCF), Dividend, MktYld, Term, Par, Call, and Put. All variablesare defined in Section 4. The year dummy are reported. All specifications include industry fixed effect.Standardized betas are reported and p-value are presented in parentheses. ***, **, and * mean significantat the 1%, 5%, and 10% level, respectively.
Table 5: Multinomial Logistic Regressions for Guarantee Use
The choice of guaranteed bonds and non-guaranteed bonds is modeled as the outcome of a variable GTthat takes the value of zero when the firm issues non-guaranteed bonds only in a year, one when the firmissues both guaranteed and non-guaranteed bonds in a year, two when the firm issues guaranteed bonds onlyin a year, and is estimated as a multinomial logistic regression. All data are in the fiscal year before thedebt issuance. The baseline group is non-guaranteed bonds only. The main independent variables includefinancial constraint measures Tangible and Frating(AAA=26,D=1), debt overhang measure (DOH), agencyproblem measure (LQ*HFCF). The control variables are Size, Profit, Free Cash Flow (FCF), Dividend,MktYld, Term, Par, Call, and Put. All variables are defined in Section 4. All specifications include industryfixed effect and year fixed effect. p-value are presented in parentheses. ***, **, and * mean significant atthe 1%, 5%, and 10% level, respectively.
Fixed industry Y YFixed year Y Y# of Obs. 3239Pseudo R2 0.172
37
Table 6: Analysis of Determinants of Guaranteed Bond Issuance Using Estimated ParentFirm Level Variables
This table shows the results of logistic regressions using the estimated parent firm level variables. Parentfirm level variables Tangible, DOH, LQ*HFCF, Size, Profit, FCF are measured at the parent firm level usingthe estimation from the minority interest method. Frating(AAA=26,D=1) is at the parent firm level basedon the rating agency’s rating methodology. The dependent variable is GT, an indicator variable equal toone if it is issued with guarantee and zero otherwise. The main independent variables include the financialconstraint measures (Tangible and Frating(AAA=26,D=1)), debt overhang measure (DOH ), agency prob-lem measure (LQ*HFCF ). The control variables are Size, Profit, Free Cash Flow (FCF), Dividend, MktYld,Term, Par, Call, and Put. All variables are defined in Section 4. All specifications include industry fixedeffect and year fixed effect. Standardized betas are reported and p-value are presented in parentheses. ***,**, and * mean significant at the 1%, 5%, and 10% level, respectively.
Fixed industry Y Y Y Y Y YFixed year Y Y Y Y Y Y# of Obs. 1304 1304 1304 1304 1304 1304Likelihood Ratio 200.68 221.26 213.67 218.88 222.41 222.54Pseudo R2 0.136 0.149 0.151 0.155 0.157 0.157
38
Table 7: Effect of Guarantees on Bond Rating
This table reports the results of the impact of guarantees on bond ratings. The dependent variable isthe bond rating at issuance. The independent variables include GT,Frating(AAA=26,D=1),InvGrade, Size,Profit, Leverage, Tangible, Par, Term, Secure, Call and Put. All variables are defined in Section 4. Allspecifications include industry fixed effect and year fixed effect. All data are in the fiscal year before thedebt issuance. Standardized betas are reported and p-value are presented in parentheses. ***, **, and *mean significant at the 1%, 5%, and 10% level, respectively.
This table reports the results of the impact of guarantees on yield spread at issuance. The dependent vari-able is the yield spread. The independent variables include GT, Frating(AAA=26,D=1),InvGrade, Size,Profit, Leverage, Par, Term, Secure, Call, Put, GT*LPPE, GT*HDOH and GT*LQ*HFCF. GT*LPPE isthe interaction term between GT and the dummy variable LPPE for more financial constraints. GT*HDOHis the interaction term between GT and the dummy variable HDOH for more pronounced debt overhang.GT*LQ*HFCF is the interaction term between GT and the variable LQ*HFCF for greater agency problem.HDOH and LPPE are defined in Appendix B and other variables are defined in Section 4. All specificationsinclude industry fixed effect and year fixed effect. All data are in the fiscal year before the debt issuance.Standardized betas are reported and p-value are presented in parentheses. ***, **, and * mean significantat the 1%, 5%, and 10% level, respectively.
Figure 1: Guarantors of Guaranteed Corporate Bonds
This figure shows the number of guaranteed corporate bonds in our sample and the number of guaranteedbonds with different types of guarantors. The two main types of guarantors are external and internalguarantors. Further, the internal guarantors are either parent firms or subsidiaries.
The number of Guaranteed (GT) Bonds: 731
GT Bonds with internal guarantors: 647
GT bonds with external guarantors: 84
GT bonds using subsidiaries as guarantors: 621 GT bonds using parents as guarantors: 26
41
Figure 2: Percentage of Guaranteed Corporate Bonds in All Corporate Bond Issues
This figure shows the the percentage of guaranteed corporate bonds issued in terms of the amount issued.Issuers are either public firms or private firms. Panel A presents the percentage for public and private firmstogether. Panel B presents the percentage for public firms. The sample period is from 1993 to 2012.
1995 2000 2005 20100
20%
40%Panel B: Public Firm Sample
1995 2000 2005 20100
20%
40%Panel A: All Firm Sample
42
Figure 3: Distribution of Corporate Bond Issuers
This figure plots the distributions of corporate bond issues across different rating groups. Panel A is for theissuers of guaranteed bonds (credit enhanced bonds) and Panel B is for the issuers of non-guaranteed bonds.The AAA group includes issuers whose firm rating is AAA. The AA group includes issuers whose firm ratingsare AA+, AA, and AA-. The A group includes issuers whose firm ratings are A+, A, and A-. The BBBgroup includes issuers whose firm ratings are BBB+, BBB, and BBB-. The BB group includes bond issuerswhose firm ratings are BB+, BB, and BB-. The B group includes bond issuers whose firm ratings are B+,B, and B-. The CCC group includes bond issuers whose firm ratings are CCC+, CCC, and CCC-. TheCC group includes bond issuers whose firm ratings are CC, C, and D. The sample period is from 1993 to 2012.