The Total Costs of Corporate Borrowing in the Loan Market:
Don’t Ignore the Fees
Tobias Berg†
Anthony Saunders‡
Sascha Steffen*
January 31, 2013
Abstract
Fees are an important part of the total cost of corporate borrowing. More than 80% of
US syndicated loans contain at least one fee type and payments from fees can easily
exceed interest payments. We find that the scope of relationship benefits extend beyond
spreads, in particular, relationship loans are associated with lower upfront fees and
lower letter of credit fees and these relationship benefits are similar in magnitude to
those observed for spreads. We also find evidence consistent with a liquidity insurance
view of lines of credit where relationship banking facilitates the smoothing of payments
between no-liquidity-shock states and liquidity-shock states. Importantly, we propose a
new measure for the total cost of corporate borrowing that accounts for fees and the
fact that most loans are not immediately drawn down at origination. This measure
produces higher costs of borrowing than has hitherto been recognized in the academic
literature to date.
We thank Viral Acharya and Michael Roberts for valuable comments and suggestions.
†
Humboldt University Berlin and New York University. Email: [email protected] Tel: +49 177 314 2164.
Stern School of Business, New York University. Email: [email protected] Tel: +1 212 998 0711.
*
European School of Management and Technology (ESMT). Email: [email protected] Tel: +49 30 181 1544.
‡
1
In this paper, we analyze the total costs of borrowing for US public firms in private debt markets.
Prior research focuses almost entirely on the All-In-Spread-Drawn (AISD) paid by the borrower
for each dollar borrowed without analyzing the type and size of fees included in the AISD and
whether the AISD ignores other fees charged to the borrower to complete deals, which would
add to the total cost of borrowing. This is surprising as the theoretical literature highlights the
importance of fees relative to spreads (Boot et al. (1987), Thakor and Udell (1987), and Morgan
(1994)). A similar concern about the importance of fees was also mentioned by Roberts (2012).
The total cost of borrowing is challenging to estimate empirically because it comprises various
fees which are customized in each contract, for example, some are shared among all syndicate
lenders and some are privately negotiated between the borrower and the lead arranger and kept
by the latter, such as the upfront fee. Moreover, only a small percentage of loans are immediately
paid out. Sufi (2009) reports that 82% of public firms’ borrowings in the US are credit lines and
even 32% of otherwise all equity financed firms also have credit lines. The design and utilization
of loans and credit lines govern to what extent spread and fees eventually apply and thus the total
cost of corporate borrowing.1
As an example of the importance and scale of fees, on June 18th, 2009 Eddie Bauer
Holdings, a clothing store chain and debtor-in-possession at that time, negotiated a USD 100mn
revolving credit facility with a maturity of seven months.2 With an annual spread over LIBOR of
400 bps and an upfront fee of 275 bps, the income from the upfront fee over the maturity of the
loan exceeded the cumulative spread income over the seven-month life of the loan. Furthermore,
the contract contains a letter of credit fee of 425 bps for drawings under the letter of credit sub1
Fees are also an important income component for banks. In the first quarter of 2012, based on regulatory filings
from the largest five bank holding companies in the US (JP Morgan Chase, Bank of America, Citigroup, Wells
Fargo and US Bankcorp) 42% of total revenues were non-interest revenues.
2
The credit agreement is available online at http://www.sec.gov/Archives/edgar/data/1345968/0001193125091334.
Information on spreads and fees can be found in Article 1 and Article 3.
2
limit and a commitment fee of 100 bps payable on undrawn amounts. The total cost of the
revolving credit facility – the upfront fee, the spread, the commitment fee and the letter of credit
fee – significantly exceeds the AISD, which in this case contains only the spread,3 and the All-inSpread-Undrawn (AISU), which in this case only contains the commitment fee.4 This example
indicates that aggregates such as the AISD and AISU might not be sufficient to describe the total
cost of corporate borrowing. To preview our results, we find that ignoring fees significantly
underestimates the costs of syndicated loans to borrowing firms.
Given the limited research available on fees in the syndicated loan market we start by
providing two stylized facts. First, fees are important; in our sample of US term loans and
revolvers from 1986 to 2011 more than 80% of the loans have at least one type of fee. In
particular, almost 50% of the loans carry a commitment fee, one third contain a letter of credit
fee, almost 25% a facility fee and some syndicated loans even specify a “collateral monitoring
fee” (see Figure 1). The mean values for these fees over the 1986-2011 period range from 16
bps (facility fee) to 177 bps (letter of credit fee) and are sizable compared to the average AISD of
190 bps. Indeed, for lines of credit, where fees are most prevalent, a borrower may pay for
setting up the line of credit (upfront fee), for not using the line of credit (commitment fee), for
using the line of credit (spread), for going above or below a certain threshold (utilization fee), for
extending the line of credit (extension fee) and for cancelling the line of credit (cancellation fee).
[Figure 1]
3
The AISD contains the spread and the facility fee. Since no facility fee is specified in this contract, the AISD
reduces to the spread for this contract.
4
The AISU contains the commitment fee and the facility fee. Since no facility fee is specified in this contract, the
AISU reduces to the commitment fee for this contract.
3
Second, we find that parameters used in the prior literature, such as the AISD and the
AISU, are only aggregates of certain spread and fee components and ignore certain features of
the overall borrowing costs. Figure 2 is a graphical illustration of the key spread and fee
components that comprise the total cost of corporate borrowing in the syndicated loan market. In
general, AISD comprises the spread and the facility fee, while AISU comprises the facility fee
and the commitment fee. For a typical term loan a borrower pays a one-time upfront fee and an
annual spread on the total borrowed amount. Thus, the AISD (spread plus facility fee) includes
the spread, but ignores the upfront fee.5 A typical revolver loan comprises i) an upfront fee, ii)
either a commitment fee (payable on undrawn amounts) or a facility fee (a fee payable both on
undrawn and drawn loan amounts), iii) a spread on drawn amounts, iv) a letter of credit fee if the
revolver loan contains a limit for letters of credit. Thus the AISD (spread plus facility fee)
ignores both upfront fees and fees payable under drawn letters of credit. The AISU (commitment
fee plus facility fee) ignores the upfront fee.
[Figure 2]
There is a broad literature on the effect of relationships on loan spreads both for small as
well as large publicly traded firms.6 However, little or nothing is known about possible
relationship benefits for fees. It is a testable hypothesis that these benefits also extend to
discretionary fees charged by lenders. Our results corroborate this hypothesis. More specifically,
we find that loan lending relationships reduce upfront fees (-16 bps) and letter of credit fees (-6
bps). These relationship effects are similar to the magnitude we observe for the AISD (-11 bps).
5
In very few cases (<10% of all syndicated loans) borrowers also pay a commitment fee or a facility fee on term
loans, e.g. for forward term loans where the exact date of drawing is not predetermined. In these cases, the facility
fee is also included in the AISD.
6
These studies include Petersen and Rajan (1994), Berger and Udell (1995), Cole (1998), Degryse and Van
Cayseele (2000) and Bharath et al. (2009).
4
In other words, we ignore a sizable proportion of relationship benefits when we ignore fees.
Moreover, the channels through which these relationship benefits accrue differ markedly from
the channels observed for the AISD. For example, we find that the relationship effects for term
loan upfront fees are higher for low liquidity borrowers as measured by their current ratio. This
is consistent with the observation that lead arrangers of a syndication are exposed to the risk of
failure in attracting sufficient participants to lay off part of the syndication risk. Since borrowers
with low current ratios are more likely to default in the short term, the lead arranger is exposed to
a higher syndication risk.
We then focus more narrowly on the role of fees in providing liquidity to borrowers
through corporate lines of credit. Under the liquidity insurance hypothesis (see, for example,
Thakor and Udell (1987)), banks act as liquidity insurers to corporate borrowers. Risk-averse
borrowers aim to smooth their costs over good states (no liquidity needs) and bad states
(liquidity shock with high liquidity needs). However, private information about the likelihood of
liquidity shocks prevents borrowers from being able to fully insure against such shocks. Banks
will offer lines of credit with relatively large spreads and fees on drawn amounts and relatively
low fees on undrawn amounts to facilitate self-selection of good and bad types in equilibrium.
Relationship banking, by overcoming problems of asymmetric information, allows good types
with a low risk of liquidity shocks to better smooth their costs.7
To operationalize this hypothesis, we introduce the variable “Excess AISD” for lines of
credit, which is defined as the difference between costs on drawn amounts (AISD = spread plus
facility fee) and costs on undrawn amounts (AISU = commitment fee plus facility fee). The
7
The same argument applies to the moral hazard dimension of lines of credit. Lines of credit which provide a high
level of smoothing can cause illiquidity seeking by firms (Acharya et al. (2012)). If relationship banking helps to
alleviate moral hazard concerns it should be associated with the use of lines of credit with a higher smoothing than
for non-relationship lending.
5
insurance view of lines of credit predicts that the Excess AISD will be lower for relationship
borrowers. As will be shown in what follows, this is exactly the result we find in our sample, i.e.
relationship lending is associated with a significantly lower excess AISD and this excess AISD
decreases in proxies for borrower opacity. We do find a relationship smoothing for letters of
credit, but significantly lower in magnitude than for credit lines.
In the final part of the paper, we go beyond the traditionally used measures of AISD and
AISU and develop a new measure for the total cost of corporate borrowing. This new measure
accounts for two stylized facts mentioned above: First, it incorporates various fees that have to
be paid in addition to the loan spread. Second, it explicitly accounts for the fact that only a
percentage of borrowers’ credit lines is actually drawn down and some other fraction is
frequently used for letters of credit. We find that the difference between the AISD measure and
our new measure is particularly important during recessions, which points to the crucial
importance of fees during an economic downturn.
Our paper is related to four strands of the literature: First, we provide further evidence on
the importance of banking relationships. The theoretical literature on relationship benefits is
largely silent about the components of the total cost of borrowing, i.e. spreads or certain fee
components, through which relationship benefits should arise. The empirical literature has taken
an agnostic stance and focuses almost exclusively on the AISD (examples include Ivashina
(2009), Bharath et al. (2011), Santos and Winton (2008, 2009), Schenone (2011), Saunders and
Steffen (2011)).8 We show that relationships matter for fees as well.
Second, we add to the literature on long-term bank relationship smoothing of spreads.
The empirical literature on this topic has provided evidence of loan rate smoothing over time
8
Notable empirical exception are the papers by Gatti et al. (2008) and Bord and Santos (2011). Gatti et al. (2008)
look at upfront fees in project finance transactions and Bord and Santos (2011) analyze the impact of bank liquidity
on the magnitude of credit line fees in the syndicated loan market.
6
(Berger and Udell (1992) and Berlin and Mester (1998, 1999)). These approaches observe
spreads over time to identify smoothing over “good” and “bad” states of the economy. Looking
at lines of credit allows us to identify smoothing by looking at loan contracts at a single point in
time rather than rate setting at different points in time, which requires some identification of the
time series uncertainties of “creditworthiness” states.9
Third, our paper adds to the growing literature on lines of credit, which can serve as precommitted debt capacity (Shockley and Thakor (1997), Holmstrom and Tirole (1998)), thereby
having a role of liquidity insurance to corporate borrowers. Recent literature has also stressed the
importance of asymmetric information and moral hazard in the use of lines of credit (Sufi (2009),
Acharya et al. (2012)). The crucial role of screening and monitoring for lines of credit is at the
heart of the importance of relationship lending. We add to this literature by documenting the
importance of relationships for the pricing structure of lines of credit.
Fourth, we develop a more complete measure of the costs of borrowing that produces a
more extensive measure of borrowing costs than either the AISD or AISU.
The rest of the paper is organized as follows: Section I develops the hypotheses, Section
II describes our data set, Section III presents the empirical results. In Section IV we develop a
new measure for the total cost of corporate borrowing and provide empirical tests and
comparisons with the AISD. Section V concludes.
9
As an example, a line of credit contract to borrower A on December 3rd, 2011 might specify fees of 30 bps if
undrawn and spreads and fees of 100 bps if drawn, while a line of credit to a similar borrower B, negotiated on the
same date (i.e. December 3rd, 2011), might specify fees of 10 bps on undrawn amounts and spreads and fees of 120
bps on drawn amounts. Rather than analyzing a time series of loan contracts for both borrowers so as to identify
relationship smoothing we can do this by directly analyzing these two contracts at the same time of origination.
Specifically, we can directly see from the example above that there is more smoothing for borrower A than for
borrower B because the Excess AISD for borrower A (100 bps – 30 bps = 70 bps) is significantly lower than for
borrower B (120 bps – 10 bps = 110 bps).
7
I Hypotheses
As argued above it seems a priori rational that if relationships reduce spreads the benefit
would also extend to fees. Consequently our Hypothesis 1 is the following:
Hypothesis 1 (H1: Relationship hypothesis): Relationship clients pay lower fees than nonrelationship clients.
With respect to liquidity insurance, Figure 3 shows two alternative pricing structures for a
line of credit. The pricing structure in the left-hand part is smooth, i.e. there is only a small
difference between AISD and AISU in a no-liquidity-shock state and a liquidity-shock state. As
we discussed earlier AISD equals spread plus the facility fee and AISU equals the commitment
fee plus the facility fee, so that the difference between AISD and AISU equals the spread minus
the commitment fee. The AISU represents the costs on undrawn amounts, i.e. the costs in a noliquidity-shock state whereas the AISD represents the costs on drawn amounts, i.e. the costs in a
liquidity-shock state when the line of credit is drawn down. In contrast, the pricing structure
depicted in the right-hand part of Figure 3 shows a stronger difference, with loan payments in the
liquidity-shock state (AISD) far exceeding payments in the no-liquidity-shock state (AISU).
Rationally, risk-averse borrowers would prefer the pricing structure shown in the left-hand part
of Figure 3 to the pricing structure shown in the right-hand part of Figure 3, i.e. they would
prefer a high level of smoothing (Thakor and Udell (1987)).
[Figure 3]
8
In the context of our hypothesis, borrowers should prefer a low Excess AISD (the
difference between spreads and fees on drawn amounts (AISD) and the fees on undrawn amounts
(AISU)). If, however, borrowers have private information about the likelihood of a liquidity
shock, which is not available to bank lenders, then lenders will offer two contracts to facilitate
self-selection in light of adverse selection problems (see also Rothschild and Stiglitz (1976)).
Without bank–borrower relationships, borrowers might have to choose a pricing structure from
the right-hand side of Figure 3, i.e. a low level of smoothing, to signal their type. Relationship
banking, by limiting the problems of asymmetric information among borrowers and lenders,
allows borrowers to obtain revolving loans of the type depicted on the left-hand side of Figure 3,
i.e. contracts that more fully insure against borrower liquidity shocks. Thus, in Hypothesis 2 we
test the following:
Hypothesis 2 (H2: Liquidity insurance hypothesis): The difference between fees and spreads paid
on drawn amounts (AISD) and fees paid on undrawn amounts of lines of credit (AISU) should be
lower for relationship borrowers.
II Data and Definitions
II.A. Data Sources and Sample Selection
To investigate the effect of relationships on fees and measures of the total costs of
borrowing, we construct a dataset using various data sources. We collect all syndicated loans
issued by US non-financial firms during the 1986 to 2011 period from the LPC DealScan
database. We obtain all spreads and fees as well as other relevant information including maturity,
loan size, facility type, collateral and covenants.
9
Using the DealScan-Compustat Linking Database (Chava and Roberts (2008)) and
extending it manually to 2011, we collect quarterly financial statement information from the
merged CRSP/Compustat database for each borrower. The sample selection process is explained
in detail in Appendix B. Starting with the universe of all non-financial borrowers, we include
only LIBOR-based loans so as to have a comparable base rate (79,646 facilities remaining),
loans to public firms where we have Compustat data available (38,574 facilities remaining) and
an ultimate parent (38,278 facilities remaining). We drop first-time borrowers as they have no
existing relationships by definition (29,372 facilities remaining). Finally, we keep only term
loans and revolving loans10 in the sample and require that the key loan contract terms are not
missing. We carefully control for mergers and acquisitions among banks using the National
Information Center (NIC) database and information provided by the Federal Deposit Insurance
Corporation (FDIC). The final dataset includes 24,719 loans from 4,215 borrowers of which
7,760 (31%) are term loans and 16,959 (69%) are revolving loans. Appendix B reports the
availability of spread and fee components of our sample loans.
Following Bharath et al. (2011), we construct a binary measure of relationship
(Rel(Dummy)) that is equal to 1 if the lead arranger of the current facility has provided a
syndicated loan to the same borrower during the prior five years.11 Using the matched
CRSP/Compustat database, we obtain several firm characteristics that measure borrower risk.
Specifically, we obtain total assets, a borrowers’ coverage ratio, leverage, profitability,
tangibility, current ratio, market-to-book ratio, one-digit SIC code and borrower rating. These
variables are described in detail in Appendix A.
10
We define term loans as all loans with type “Term Loan”, “Term Loan A”-“Term Loan H” or “Delay Draw Term
Loan” as indicated in the facility table in DealScan. We define revolving loans as all loans with type “Revolver/Line
< 1 Yr.”, “Revolver/Line >= 1 Yr.”, “364-Day Facility”, “Limited Line” or “Revolver/Term Loan” as indicated in
the facility table in DealScan, see Appendix A for details.
11
If there are several lead arrangers Rel(Dummy) is equal to 1 if any of the lead arrangers has provided a syndicated
loan to the same borrower over the previous five years.
10
II.B. Fee Types and Definitions
Below we describe the various fee and spread components in more detail and describe
how they relate to the different loan types. We focus on fee types which are present in at least
10% of the loans in our sample.12
(a) Spread over LIBOR:
The spread over LIBOR is the interest margin above the interbank loan rate charged to
borrowers on the drawn portion of the loan.
(b) Upfront Fee:
The fee paid by the borrower to lender(s) at the closing date. The fee will vary from
transaction to transaction and will frequently vary within the same transaction based on
the level of commitment offered by the lender (see Taylor and Sansone (2007)).
(c) Commitment Fee:
The commitment fee is paid by borrowers on unused loan commitments.13 Commitment
fees are most frequently used in revolving credit facilities and are found in 68% of all
revolvers. For term loans, such fees are only used where the exact date of drawing is not
predetermined (6% of all term loans).
(d) Facility Fee:14
As described by Taylor and Sansone (2007) a facility fee is “a fee paid on the entire
committed amount, regardless of usage. It is often charged on revolving credits to
investment grade borrowers instead of a commitment fee because these facilities typically
12
An example of a fee type that is available for less than 10% of the loans is the “collateral monitoring fee”, which
is reported for 0.2% of all loans. Given the small number of observations it would be both uninteresting and
impossible to draw robust conclusions about relationship benefits for such a fee type.
13
If a term loan has not been drawn down, the commitment fee is usually referred to as a “ticking fee” (Taylor and
Sansone (2007)).
14
The facility fee is labeled “annual fee” in DealScan. We use the wording “facility fee” as this is usually used in
the credit agreements.
11
have a competitive bid option (CBO).15 The lenders that do not lend under the CBO are
still paid for their commitment.”16 Commitment fees and facility fees are usually
mutually exclusive. In particular, revolvers contain one of these types of fees, but not
both. We find that 97.4% of our revolving credit facilities have either a facility fee or a
commitment fee.17 That is, 65.7% of the facilities include a facility fee (but not a
commitment fee) and 31.7% a commitment fee (but not a facility fee).
(e) Letter of Credit Fee:
A letter of credit fee is paid for the issuance of a letter of credit. Letters of credit are
written obligations of an issuing bank to pay a sum of money to a beneficiary on behalf
of their customer in the event that the customer does not pay the beneficiary and therefore
fulfills the same function as a bank credit guarantee.
DealScan aggregates the spread over LIBOR and the fees into the AISD and the AISU
using the following formulas:18
(1)
AISD = Spread + Facility fee
(2)
AISU = Facility fee + Commitment fee
The AISD is estimated to be a measure of the cost of lending for loans that are actually
drawn. The AISU is estimated to be a measure of the cost of lending on undrawn lines of credit.
15
A CBO allows the borrower to solicit the best bid from its syndicated group for a given borrowing (Taylor and
Sansone (2007). Therefore, the syndicated loan shares by the participants are backup shares in case no sufficient
bids are obtained in any of these auctions. If, for example, two lenders each have a USD 50mn share of a USD
100mn revolver, each lender is still allowed to bid for a higher amount when the borrower requests liquidity from
this line of credit. For example, in the extreme case, lender A might provide the whole USD 100mn financing if
lender A bids for the total amount and lender B bids nothing. The facility fee is therefore used to ensure that the
lenders that do not lend under the CBO are still paid for their commitment.
16
Revolver loans usually include various sub-limits which allow some flexibility for the borrower such as
competitive bids, letters of credit, swingline or foreign currency. The draw-downs under the sub-limits cannot
exceed the aggregate loan commitment made by the syndicate.
17
Approximately three percent have both types of fees included.
18
In particular, DealScan does not include the upfront fee in the AISD.
12
Conceptually, the AISU can be interpreted as an insurance premium paid by a potential borrower
while the portion of the AISD which exceeds the AISU is a deductible that has to be paid in case
of an insurance event, i.e. a borrower needs liquidity and actually draws down a loan.
III Determinants of Loan Spreads and Fees
III.A The Anatomy of Fees: Stylized Facts
We start by describing some stylized facts about the anatomy of fees in the syndicated
loan market. We discuss the frequency of fees, the magnitude of fees, the time-series behavior as
well as cross-sectional differences with respect to non-price terms and borrower characteristics.
[Table I]
Panel A of Table I shows the spread and fee terms for our sample loans segregated into
term loans and revolver loans. Among all fee types, the commitment fee is used most frequently
(12,075 out of 24,719 loans = 49%) followed by the letter of credit fee (8,188/24,719 = 33%),
the facility fee (6,044/24,719 = 24%) and the upfront fee (5,481/24,719 = 22%). As term loans
are fully funded at origination and only rarely originated to be funded at some pre-determined
future date, only a small number of term loans exist where DealScan records AISU, facility or
commitment fees. For revolver loans, fees are much more prevalent, with the commitment fee
being reported in 68% (=11,577/16,959) of the loans, the letter of credit fee in 48%
(=8,188/16,959), the facility fee in 34% (=5,816/16,959) and upfront fees in 20%
(=3,371/16,959) of all revolver loans. The average size of the different fee types vary
significantly, ranging from 16 bps (facility fee) to 177 bps (letter of credit fee). The upfront fee
13
shows the strongest variation with the standard deviation exceeding the mean value (67 bps
versus 59 bps).
Panel B of Table I reports non-price features of our loan sample. Revolver loans are, on
average, larger than term loans, have shorter maturities and are less likely to be secured.
Numerically, they also have larger syndicates (based on the total number of participants).
Moreover, borrower characteristics reported in Panel C of Table I show that revolving loans have
larger interest coverage and lower leverage than term loans. They are also more likely to be
made to investment grade borrowers.
As can be seen from Table II, both spreads and fees show a significant time-series
variation. All spread and fee types are larger during recessions with the most marked increase
observed during the recent financial crisis from 2007 to 2009. Further, upfront fees have the
highest time-series standard deviation while commitment fees have the lowest time-series
standard deviation.
[Table II]
Finally, spreads and fees also differ substantially cross-sectionally. Table III provides a
univariate analysis of our sample of syndicated term and revolver loans. We document that fee
types and spreads show a markedly different behavior in their time series and in the crosssection. While spreads, letter of credit fees, facility fees and commitment fees are lower for
larger firms, large borrowers pay, on average, higher upfront fees. This higher upfront fee is
consistent with lead arrangers seeking compensation for being exposed to the cost and risk that
they have to absorb the loan on their balance sheet if the syndication process is unsuccessful, i.e.
does not attract sufficient participations in the loan. For example, a larger loan exposes the lead
14
arranger(s) to significant concentration risk and enhanced capital requirements. Loans with
longer maturities have lower letter of credit fees. However, long maturity loans have higher
commitment fees and upfront fees. While relationship borrowers pay 43 bps lower spreads on
average than non-relationship borrowers, the difference between relationship borrowers and nonrelationship borrowers is smaller for letter of credit fees (27 bps) and upfront fees (20 bps) and
significantly smaller for facility fees (3 bps) and commitment fees (3 bps).
Letter of credit fees are the most cyclical, with fees during NBER-determined recessions
being 38 bps above non-recession period fees. Upfront fees follow with a 28 bps difference and
we observe a 23 bps difference for spreads and no significant difference for facility fees. We also
find that non-investment grade borrowers not only pay higher spreads and letter of credit fees
than investment grade borrowers but also significantly higher facility fees, commitment fees and
upfront fees. Interestingly, borrower liquidity, as measured by the current ratio, is associated
with significantly lower upfront fees (10 bps) while the difference in spreads is insignificant, a
result which is consistent with the notion of upfront fees acting as a partial compensation for
credit risk, concentration risk and capital requirement exposure during the syndication process.
This heterogeneity among different fee types discussed above, while being only univariate in
nature, indicates that aggregates such as the AISD and the AISU might not be sufficient to
describe the pricing and fees which drive the time-series and cross-sectional behavior of the total
cost of syndicated loan borrowing.
[Table III]
15
III.B. Test of Hypotheses
In this section we test the two hypotheses formulated in Section I:
Hypothesis 1:
In the first set of tests, we analyze cross-sectional determinants of loan spreads and fees
using OLS regressions focusing on the effects of bank–borrower relationships on fees
(Hypothesis 1). Previous papers have studied the effects of relationships on the AISD. By
contrast, we decompose borrower costs into its separate components, i.e. spread, facility fees,
commitment fees, letter of credit fees and upfront fees.
[Table IV]
We start by reporting results for the aggregates of AISD and AISU (columns (1) and (2)
in Table IV). Consistent with recent studies (Bharath et al. (2011)) we find that relationships
significantly reduce AISD. Specifically, after controlling for loan characteristics and borrower
risk, relationship loans are associated with an 11 bps lower AISD, the same value as reported in
Bharath et al. (2011). However, the AISD is the sum of the loan spread and the facility fee. We
report the relationship effect for these two parts separately in columns (3) and (4) of Table IV.
Interestingly, the relationship benefit for loan spreads is 11 bps after controlling for loan
characteristics and borrower risk, while the effect for the facility fee is not only small but
relationship clients pay a marginally higher facility fee (1 bp) than non-relationship clients after
controlling for loan characteristics and borrower risk.
Further, we find that relationship lending is not associated with a lower AISU. As above,
we decompose the AISU into its two fee components: the facility fee and the commitment fee.
Interestingly, having a prior relationship actually increases the facility fee paid by borrowers to
16
lenders and does not have a significant effect on commitment fees. One possible interpretation of
the result is that the facility fee and commitment fee is a compensation for the time and effort of
the relationship lender for providing a loan commitment that is unlikely to be drawn except in
liquidity shock circumstances. The relationship premium resembles an insurance premium
against a future liquidity shock to the borrower.
However, two fees, the upfront fee and the letter of credit fee, which are overlooked in
the calculation of AISD and AISU on DealScan, are both favorably impacted by relationships in
a multivariate setting. Having a relationship actually reduces a borrower’s upfront fees by 16 bps
and its letter of credit fees by 6 bps, both significant at the 1 % level. A lower letter of credit fee
suggests lower ongoing monitoring costs while lower upfront fees (which is a one-time payment
by the borrower to the lender) suggests lower costs in organizing and structuring the syndicate.19
These savings are economically significant: A 16 bps decrease in upfront fees, for example,
translates into one-time savings of USD 0.6mn for the average loan size of USD 355mn; a 6 bps
decrease in letter of credit fees translates into yearly savings of USD 0.25mn for a letter of credit
equal to the average amount of revolving loans (USD 393mn).
Larger loans have lower spreads, lower facility fees and also lower commitment and
letter of credit fees but loan size is not statistically significantly related to upfront fees. Similar to
previous papers, we find that longer maturity loans carry lower spreads. Facility fees and letter of
credit fees are also lower for longer maturity loans; however, commitment fees are significantly
higher. This is intuitive given that banks make a longer-term commitment during which credit
and liquidity shocks could adversely impact a borrower. Secured loans have higher spreads as
19
Upfront fees can also be seen as a component of a two-part tariff. Oi (1971) shows that a discriminating two-part
tariff maximizes monopoly profits by extracting all consumer surpluses. A monopolist would effectively set the cost
of borrowing equal to the marginal costs and extract the whole consumer surplus with an upfront fee. The
relationship benefit for upfront fees can thus be interpreted as an indication against the argument of banks fully
exploiting any potential monopoly power vis-à-vis relationship borrowers.
17
well as higher facility, commitment, letter of credit and upfront fees. These results are consistent
with the interpretation that riskier borrowers have to pledge collateral.
Table V provides results separately for term loans and revolvers. Importantly,
relationship effects are much stronger for term loans than for revolvers. Term loans are on
average smaller and extended to smaller firms (see descriptive statistics in Table I) and it is a
well-established fact that relationship benefits are larger for smaller and more opaque firms
(Bharath et al. (2011)). Another notable difference between term loans and revolvers is the effect
of the loan amount on fees. A larger loan amount increases term loan upfront fees but decreases
revolver upfront fees. A possible explanation is that term loans are fully funded from the first
day onwards, which increases syndication risk and concentration risk for the lead arranger(s).
Results for commitment fees, facility fees and letter of credit fees are only provided for revolvers
as these fee types are rarely observed for term loans. Consequently, the results are very similar to
the results from Table IV for the overall sample, i.e. relationship effects are significant for letter
of credit fees but small to non-existent for commitment fees and facility fees.
[Table V]
Finally, we analyze the channels through which a relationship benefit to a borrower
arises. We have established in Table IV and Table V that the aggregate relationship effect is
economically significant for spreads, upfront fees and letter of credit fees while the benefit is
significantly lower for commitment fees and facility fees. Disaggregating these effects can shed
light on the underlying economics driving bank–borrower relationship benefits. In theory,
relationship benefits should be greater when problems of information asymmetry and bank
monitoring and information collection costs are most pronounced. We therefore introduce
18
interaction terms of the form X·Rel(Dummy) into our regression where X is a measure such as
loan size, leverage ratio or maturity. Table VI reports the results. Relationship effects on term
loan spreads are driven by many channels, among them maturity (larger relationship benefits for
longer maturities), size (larger relationship benefits for smaller syndicates) and the coverage ratio
(larger relationship benefits for borrowers with higher coverage ratios). In contrast, relationship
benefits for upfront fees only arise from two channels: the liquidity of the borrower (as measured
by the current ratio) and the number of lead arrangers. In particular, relationship benefits for
upfront fees are larger for low-liquidity borrowers. Upfront fees compensate the lead arranger(s)
for the credit, capital requirement and concentration risks arising during the syndication process.
The more lead arrangers there are, the more those risks are shared.
[Table VI]
Hypothesis 2:
Our second hypothesis is the liquidity insurance hypothesis, i.e. the difference between
fees and spreads paid on drawn amounts (AISD) and fees paid on undrawn amounts of lines of
credit (AISU) should be lower for relationship borrowers. Revolving lines of credit offer
protection against liquidity shocks. If borrowers are faced with unexpected liquidity needs they
offer liquidity at predetermined spread and fee terms. Similar to other insurance contracts, banks
face a trade-off. While risk-averse borrowers will have an innate desire to smooth liquidity costs
over good and bad states, offering such “smoothing” contracts will attract borrowers with a high
risk of a liquidity shock. In a world without relationships, good borrowers with a low risk of a
liquidity shock will tend to signal their quality by self-selecting into contracts with low fees on
undrawn amounts and high spreads and fees on drawn amounts. However, by forming a
19
relationship with a bank to decrease asymmetric information vis-à-vis their credit and liquidity
exposure types, relationship banking enables contracts that smooth fees and spreads over time.
As discussed in Section I our key variable of interest is Excess AISD, defined as:20
Excess AISD = AISD – AISU.
Excess AISD is the extra amount (in bps) a borrower has to pay in a liquidity-shock state
(drawing on the revolver) versus a non-liquidity-shock state (not drawing on the revolver).
Revolving lines of credit that smooth costs for relationship borrowers over different states of the
world will offer a lower Excess AISD compared to signaling devices associated with asymmetric
information in the absence of a relationship. Our key hypothesis is that relationship loans will be
associated with a lower Excess AISD, especially for borrowers where opacity and asymmetric
information is likely to be largest. Consequently, we compare the Excess AISD for relationship
customers to the Excess AISD for non-relationship customers and analyze how relationship
effects vary with proxies for borrower opacity.
Figure 4 shows the univariate results. Panel A shows the Excess AISD for relationship
and non-relationship loans by quartiles of the borrowers’ assets. The pattern shown demonstrates
that, first, the Excess AISD is larger for smaller, more opaque borrowers. Second, the relationship
effect on the Excess AISD is larger for smaller borrowers. This is exactly in line with the
predictions of the liquidity insurance hypothesis. Alternative measures of borrower opacity
confirm these results, e.g. relationship effects for the Excess AISD are larger for non-investment
grade firms and non-rated firms than for investment grade firms (Panel B of Figure 4) and they
are larger for firms followed by fewer analysts (Panel C of Figure 4).
[Figure 4]
20
Our results also carry over to defining Excess AISD as a relative measure, i.e. Excess AISD = AISD / AISU.
20
In a multivariate set-up, we regress the Excess AISD for our sample of revolvers on a
relationship dummy and controls for non-price terms and other borrower characteristics. The
results are shown in Table VII. Column (1) provides the results using the relationship dummy as
an independent variable, columns (2) to (4) use interaction terms between the relationship
dummy and proxies for borrower opaqueness. As alternative measures of opaqueness we use size
measured by the logarithm of total assets, a dummy if a company is not rated and the number of
analysts following the borrowing firm. We find that relationship loans are associated with a 5 bps
lower Excess AISD. Furthermore, relationships facilitate a reduction in the Excess AISD in
particular for opaque borrowers where the problems of information asymmetry are likely to be
largest. If a borrower is half as big as another borrower (measured by total assets) then the
relationship effect on the Excess AISD is 3 bps larger.21 For non-rated firms the relationship
effect on the Excess AISD is 9.1 bps larger than for rated firms and it is 0.7 bps lower for each
additional analyst that covers the respective borrower.22
[Table VII]
As a further robustness test we look at a sample of letters of credit. Standard letters of
credit are simple contingent credit guarantees by the lenders that do not provide liquidity to the
borrower. Consequently, smoothing arguments based on liquidity insurance should not apply to
letters of credit. To operationalize this we introduce a dependent variable “Excess LCF” which is
defined as the difference between the costs on drawn letters of credit (the letter of credit fee) and
21
The coefficient in column (2) of Table 8 is 4.257, therefore if the total assets of borrower A are 50% lower than
the total asset of borrower B, the relationship effect for borrower A is 3.0 bps higher (ln(0.5)*4.257 bps = 3.0 bps).
22
These results are robust to instrumenting the relationship dummy using the distance between the lender and the
borrowers’ headquarter. Results are available on request.
21
costs on undrawn letters of credit (the commitment fee). We construct a matched sample of
revolving loans and letters of credit for our empirical test, i.e. we look at borrowers that have
received a revolving line of credit and a letter of credit limit on the same day with the same
maturity. Specifically, we regress Excess LCF on a relationship dummy, interaction terms of the
relationship dummy with measures of borrower opaqueness and control variables. The results are
reported in Table VIII. For each regression we also report the results from the borrower, date and
maturity matched sample of revolving credit lines. Columns (1), (3), (5) and (7) report the results
for the Excess LCF, columns (2), (4), (6) and (8) report the results for the Excess AISD. We do
find significantly smaller smoothing for letters of credit, with the relationship effect on letters of
credit being significantly weaker than that on revolving lines of credit.
[Table VIII]
IV. Measuring the Total Cost of Borrowing
Our previous results show that fees are an important component of the cost of bank debt.
What can a borrower expect to pay for each dollar borrowed? The answer is not trivial as it
depends on the one hand on spreads and fees, and, on the other hand, on the utilization of the
credit limit as agreed in the loan contract which determines the applicability of certain types of
fees. In this section, we derive new measures of the total cost of borrowing (TCB) and compare
them with the widely used AISD-measure for both term loans and revolvers. While omitting fees
ceteris paribus leads to an underestimation of the true costs of borrowing, implicitly assuming
that loans are fully drawn down will overstate them. We define the annual TCB on a loan as:
TCB for term loans:
TCB = UpfrontFee / Loan Maturity in Years + Annual Facility Fee + Annual Spread
22
TCB for revolvers without letter of credit:
TCB = UpfrontFee / Loan Maturity in Years + Annual Facility Fee +
(1- PDrawn) x Annual Commitment Fee + PDrawn x Annual Spread
TCB for revolvers with a letter of credit sublimit:23
TCB = UpfrontFee / Loan Maturity in Years + Annual Facility Fee +
(1- PDrawn) x Annual Commitment Fee + PDrawn x
[ (1-LC-Limit) x Annual Spread + LC-Limit x Annual Letter of Credit Fee ],
where PDrawn is the probability that the credit facility is going to be drawn down and LC-Limit
denotes the percentage of the loan that can be used as a letter of credit by the borrower. In our
empirical examples below, we set PDrawn to be 57% based on Mian and Santos (2012) who show
that, on average, only 57% of a revolving facility is actually drawn down.24 The USD-amount of
the LC-Limit is available in DealScan and we determine the percentage LC-Limit by dividing it
by the total facility amount.25
The interpretation of the TCB-measure for term loans is straightforward: Using only
AISD, which comprises the spread and the facility fee, will always understate the true costs of
borrowing for term loans since it ignores the annualized upfront fee, i.e. the upfront fee divided
by loan maturity. For revolvers, TCB is a weighted average of AISU and AISD with adjustments
23
It is straightforward to see that this formula also applies to term loans and to revolvers without letters of credit by
setting the LC-Limit equal to zero and, for term loans, PDrawn equal to one.
24
PDrawn can be measured for each borrower individually subject to data availability. For example, one could use the
historical draw down behavior of each borrower from the previous loans (as shown in the annual reports) and use
this as a proxy for the next loans.
25
In approximately 10% of the facilities which have a letter of credit fee we do not find an LC-Limit in DealScan. In
these cases we use the average LC-Limit. Dropping these observations leads to qualitatively and quantitatively very
similar results. We also substitute missing values for the upfront fee by their predicted values based on the
regressions (2) and (6) in Table V. Again, we obtain very similar results when restricting the sample to loans with
non-missing values for the upfront fee. Results are available on request.
23
for the annualized upfront fee and the annual letter of credit fee.26 Therefore, TCB can be higher
or lower than the AISD depending on the magnitude of these effects.
We provide descriptive statistics for the new measure TCB along with AISD for a
comparison from our sample of loans in Table IX.
[Table IX]
Panel A of Table IX reports the descriptive statistics. As expected, the mean TCB for
term loans is 294 bps and therefore about 22 bps larger than the AISD. This implies, on average,
USD 0.6 million higher costs per annum than suggested by the AISD based on the average term
loan facility amount of USD 274 mn. The mean TCB for revolvers is 115 bps and about 38 bps
lower compared to the mean AISD for revolvers. Panel B of Table IX reports univariate results
comparing the AISD and TCB along various dimensions such as borrower size, relationship
status or stage of the economic cycle. The results suggest that there are important differences
between the AISD and TCB. For term loans, the relationship between maturity and AISD is
positive and significant whereas the relationship between maturity and TCB is negative and
insignificant. This is driven by the fact that the upfront fee, as a one-time payment, has a much
larger per annum effect for short-maturity loans than for long-maturity loans.
A similar effect can be observed for revolvers. For revolvers, the size effect is
significantly smaller for the TCB compared to the AISD. This explanation is straightforward:
While the spread for revolvers is negatively related to size, both upfront fees, commitment fees
and letter of credit fees are positively related to size (see Table V) and all three fees are not
26
The TCB for revolvers without letter of credit sublimit can be rewritten as TCB = UpfrontFee/Maturity + (1PDrawn) x AISU + PDrawn x AISD.
24
included in the AISD. Finally, the TCB is more sensitive to changes in the economic cycle and
increases substantially if the economy is in a recession. For term loans, the difference between
the TCB in a recession period and the TCB in a non-recession period is 50 bps, while this
difference is only 29 bps for the AISD. Upfront fees increase significantly during recessions and,
equally important, maturities of loans shorten during recessions. For revolvers, the difference
between TCB in a recession period and the TCB in a non-recession period is similar in absolute
terms (23 bps). However, relative to the mean AISD of 153 bps and the mean TCB of 115 bps
the effect is larger for the TCB (23/115 = 20%) than for the AISD (23/153 = 15%). These
univariate effects are confirmed in a multivariate analysis (cf. Panel C of Table IX). The
relationship effect is similar in magnitude, although slightly more pronounced, for the TCB than
for the AISD. Table IX also implies that AISD and TCB differ in their level and relation to
certain non-price terms and borrower characteristics. Figure 5 plots the yearly cross-sectional
correlation between AISD and TCB. While the correlation between AISD and TCB is high
during non-recession periods, we observe a significant decline in the correlation during recession
periods. These results suggest that loan cost differentiation between borrowers occurs to a
significant extent through fees that are not included in the AISD, and this effect is in particular
important during recessions.
V Conclusion
The total cost of borrowing in the syndicated loan market comprises spreads and fees.
Commonly used aggregates such as the All-In-Spread-Drawn (AISD) aggregate spreads and fees
into a single aggregate number that ignores important fees charged by lenders such as upfront
and letter of credit fees. While abundant research is available on the cross-sectional and time-
25
series behavior of aggregates such as the AISD, to our knowledge, almost no research has
investigated the determinants of syndicated loan fees. This is an important topic because these
fees are not only important parts of the total costs of corporate borrowing but also play an
important role in driving the overall profitability of banks.
First, we find that ignoring fees significantly underestimates the benefits to borrowers
from lending relationships. Relationship lending is associated with lower upfront fees and letter
of credit fees, although with little benefit in terms of commitment fees and facility fees.
Moreover, the magnitude of these relationship effects is similar to those previously demonstrated
for the aggregate AISD, which only incorporates the spread and the facility fee.
Second, we find that the channels through which relationship effects operate are different
from the channels observed for AISD in the previous literature. For example, relationship
benefits in terms of upfront fee payments are particularly large for lower liquidity firms. This
observation is consistent with the interpretation of upfront fees as compensation for the risk lead
arrangers face during the syndication process.
Third, we find evidence consistent with the liquidity insurance hypothesis. The liquidity
insurance hypothesis implies that relationship lending, by reducing asymmetric information
problems among lenders and borrowers, allows borrowers to obtain a lower cost coverage
against unexpected liquidity shocks. That is, relationship lending allows borrowers to smooth
their liquidity costs over time and over economic cycles by reducing the difference between the
costs of drawn and undrawn lines of credit. We find evidence consistent with this hypothesis,
specifically that relationship loans are associated with a significantly lower difference between
costs on drawn and undrawn lines of credit. We also find that this effect is most pronounced for
relatively opaque borrowers. These results suggest that relationship lending not only helps to
26
overcome asymmetric information about the creditworthiness of a borrower but also asymmetric
information about the liquidity risk of a borrower.
Finally, we develop an alternative measure to the widely used AISD, the total cost of
borrowing (TCB), which includes all major fees typically charged in syndicated loan contracts.
We demonstrate the particular features of this new measure. For example, the increase in the
TCB during recessions is much larger than the increase in the AISD, largely because fees
increase significantly during recessions and maturities of loans shorten, which in turn increases
the impact of the upfront fee on the total cost of borrowing. Furthermore, the cross-sectional
correlation between AISD and TCB also decreases significantly during periods of recession.
Overall, these results suggest that analyzing fees in the syndicated loan market can
provide important insights beyond the results obtained by analyzing partial aggregates such as
the commonly used AISD. Fees are important determinants of the total cost of borrowing in the
syndicated loan market and should not be ignored.
27
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30
Figure 1
Spread and fee components of US syndicated loans
This figure depicts fee types and the proportion of syndicated loans where the respective fee type is
available in DealScan. The column Percentage of contracts denotes the percentage of contracts where the
respective fee is available in DealScan. The column Mean (in bps) denotes the mean of the respective fee
type in basis points. Any fee is the percentage of syndicated loans where any fee is available on DealScan.
The sample is based on term loans and revolvers in the US syndicated loan market from 1986 to 2011.
For a detailed description of the sample and the availability of fees see Appendix B.
31
Figure 2
Spread and fee type patterns for term loans and revolver
This figure illustrates the spread and fee type patterns used in US syndicated loans. “x” denotes that the
fee type as indicated in the respective column header exists, while (x) denotes that the fee type as
indicated in the respective column exists for some of the loans for the respective loan type. N denotes the
number of facilities in our sample. The sample is based on term loans and revolvers in the US syndicated
loan market from 1986 to 2011. For a detailed description of the sample see Appendix B.
Loan types by fee pattern
N
Spread
Term loan
7,052
x
Revolver 1
3,952
x
Revolver 2
4,554
x
Revolver incl. letter of credit 1
1,430
x
Revolver incl. letter of credit 2
6,589
x
Other term loans/revolver
1,142
x
Total
24,719
Facility
fee
Commitment
fee
Upfront
fee
Letter of
credit fee
(x)
x
(x)
x
x
(x)
(x)
x
x
(x)
x
(x)
(x)
(x)
AISU (dotted line)
AISD (solid line)
32
(x)
Figure 3
Lines of credit as insurance against liquidity risk
This figure provides an illustration of the hypothesis based on the liquidity insurance view of the role of credit lines. The left-hand picture depicts a line of credit
with a high level of smoothing and the right-hand picture depicts a line of credit with a low level of smoothing. AISU denotes the All-In-Spread-Undrawn. AISD
denotes the All-In-Spread-Drawn. Excess AISD denotes the difference between the AISD and AISU.
33
Figure 4: Excess AISD by proxies for asymmetric information
This figure depicts the Excess AISD for relationship loans (grey bars), non-relationship loans (red bars) and the difference between both (green bars). Excess AISD
is defined as the difference between the AISD and the AISU. Panel A (upper left-hand picture) depicts results based on quartiles by total assets of the borrower.
Panel B (upper right-hand picture) depicts results based on S&P ratings of the borrower. Panel C (lower picture) depicts the results based on quartiles by the
number of analysts following the borrowing company.
34
Figure 5: Correlation between All-in-spread-drawn (AISD) and Total Cost of Borrowing (TCB)
This figure depicts the correlation between the Total Cost of Borrowing (TCB) and the All-In-Spread-Drawn (AISD). The black line shows the yearly correlation
for revolvers, the grey line shows the yearly correlation for term loans. Shaded areas depict years with NBER recessions.
35
Table I
Summary statistics for key price terms, non-price terms and borrower characteristics
This table provides summary statistics for key price terms, non-price terms and borrower characteristics. Column “(I) All loans” reports summary statistics for the total sample,
column “(II) Term loans” reports summary statistics for term loans, column “(III) Revolver” reports summary statistics for revolvers. Panel A reports price terms, Panel B reports
non-price terms and Panel C reports borrower characteristics. For variable definitions see Appendix A.
(I)
Variable
Unit
N
Mean
Basis points
24,719
Std.Dev.
All loans
P25
Median
87.50
175.00
P75
Panel A: Price terms
AISD
190.42
128.74
275.00
AISU
Basis points
17,262
31.03
19.50
15.00
25.00
50.00
Spread
Basis points
24,719
186.36
130.65
75.00
175.00
275.00
Facility fee
Basis points
6,044
16.18
12.80
8.00
12.50
20.00
Commitment fee
Basis points
12,075
37.56
17.85
25.00
37.50
50.00
Letter of credit fee
Basis points
8,188
176.83
97.86
100.00
162.50
250.00
Upfront fee
Basis points
5,481
58.70
66.69
15.00
37.50
75.00
Panel B: Non-price terms
Facility amount
USD mn
24,719
355.34
532.95
59.18
163.11
400.46
Maturity
Months
24,719
49.44
23.60
36.00
59.00
60.00
Secured
0/1
24,719
0.53
0.50
0.00
1.00
1.00
Sole lender (0/1)
0/1
24,719
0.15
0.35
0.00
0.00
0.00
Syndicate size
Number
24,719
9.07
9.62
3.00
6.00
12.00
Lead size
Number
24,719
1.47
1.07
1.00
1.00
2.00
Total assets
USD mn
23,079
4,269.67
8,825.31
299.13
956.99
3,348.82
Coverage
Percent
22,316
13.67
31.81
2.64
5.09
10.52
Leverage
Number
23,057
0.33
0.24
0.16
0.29
0.45
Profitability
Number
22,914
0.17
0.13
0.08
0.13
0.22
Tangibility
Number
22,993
0.35
0.24
0.15
0.30
0.52
Current ratio
Number
22,018
1.76
1.06
1.07
1.52
2.17
Market-to-book
Number
19,972
1.67
0.89
1.12
1.39
1.89
Investment grade
0/1
10,961
0.49
0.50
0.00
0.00
1.00
Not rated
0/1
24,719
0.56
0.50
0.00
1.00
1.00
Panel C: Borrower characteristics
36
(II) Term loans
Variable
Unit
N
Mean
Std.Dev.
AISD
Basis points
7,760
271.54
AISU
Basis points
303
55.88
Spread
Basis points
7,760
Facility fee
Basis points
Commitment fee
Basis points
Letter of credit fee
Basis points
0
Na
Na
Na
Upfront fee
Basis points
2,110
77.69
83.19
25.00
Facility amount
USD mn
7,760
273.90
446.05
45.45
Maturity
Months
7,760
62.05
22.69
49.00
Secured
0/1
7,760
0.69
0.46
Sole lender (0/1)
0/1
7,760
0.16
Syndicate size
Number
7,760
8.46
Lead size
Number
7,760
1.54
Total assets
USD mn
6,845
Coverage
Percent
Leverage
Profitability
(III) Revolver
P25
Median
P75
N
Mean
Std.Dev.
P25
Median
P75
135.40
175.00
250.00
325.00
16,959
153.31
106.68
62.50
137.50
225.00
27.93
37.50
50.00
75.00
16,959
30.59
19.03
15.00
25.00
50.00
270.59
135.58
175.00
250.00
325.00
16,959
147.82
108.34
50.00
125.00
225.00
228
27.18
19.24
12.50
25.00
37.50
5,816
15.75
12.28
8.00
12.50
20.00
498
52.30
26.44
37.50
50.00
75.00
11,577
36.93
17.10
25.00
37.50
50.00
Na
Na
8,188
176.83
97.86
100.00
162.50
250.00
50.00
100.00
3,371
46.82
50.34
12.50
25.00
62.50
126.47
302.54
16,959
392.61
564.41
68.18
182.31
455.58
60.00
81.00
16,959
43.67
21.68
25.00
48.00
60.00
0.00
1.00
1.00
16,959
0.45
0.50
0.00
0.00
1.00
0.37
0.00
0.00
0.00
16,959
0.14
0.35
0.00
0.00
0.00
11.16
2.00
5.00
10.00
16,959
9.35
8.82
3.00
7.00
13.00
1.12
1.00
1.00
2.00
16,959
1.44
1.05
1.00
1.00
2.00
2,850.10
6,357.76
249.89
765.76
2,150.56
16,234
4,868.23
9,616.58
324.90
1,075.91
4,047.83
6,627
10.79
28.46
2.00
3.75
7.54
15,689
14.89
33.05
3.04
5.72
11.80
Number
6,841
0.40
0.27
0.20
0.37
0.55
16,216
0.30
0.22
0.14
0.27
0.40
Number
6,787
0.16
0.13
0.08
0.13
0.22
16,127
0.17
0.13
0.08
0.13
0.22
Tangibility
Number
6,811
0.34
0.23
0.14
0.29
0.50
16,182
0.36
0.24
0.16
0.30
0.53
Current ratio
Number
6,583
1.74
1.07
1.05
1.51
2.12
15,435
1.77
1.05
1.08
1.53
2.19
Market-to-book
Number
5,551
1.60
0.82
1.11
1.36
1.80
14,421
1.70
0.91
1.13
1.40
1.92
Investment grade
0/1
3,053
0.21
0.41
0.00
0.00
0.00
7,908
0.60
0.49
0.00
1.00
1.00
Not rated
0/1
7,760
0.61
0.49
0.00
1.00
1.00
16,959
0.53
0.50
0.00
1.00
1.00
Panel A: Price terms
Panel B: Non-price terms
Panel C: Borrower characteristics
37
Table II
Price terms by year
This table provides mean values of the price terms (AISD, AISU, spread, facility fee, commitment fee, letter of credit fee and upfront
fee) from 1986 to 2011. For variable definitions see Appendix A. The row “Total mean” provides the unweighted mean over all
syndicated loans. The row “Stdev” provides the standard deviation of the yearly time series of mean values. The column Year is
formatted in italic and marked with the word Recession if at least one month of the year falls within an NBER-defined recession.
basis points
Commitment fee
basis points
Letter of
credit fee
basis points
basis points
37.50
119.33
153.32
159.61
141.29
155.31
157.53
146.24
136.16
139.56
151.93
141.31
166.90
201.38
187.15
176.19
200.30
212.20
199.54
178.29
176.30
192.35
237.59
385.73
314.38
232.81
Na
31.05
22.21
19.30
17.71
26.58
21.18
18.41
17.46
13.88
14.57
14.07
14.83
18.23
14.02
16.53
16.90
17.34
16.14
14.82
12.19
10.10
15.11
41.09
32.84
19.63
12.50
35.20
39.87
37.94
36.37
36.37
36.38
34.13
33.04
33.71
34.04
32.03
35.09
41.15
39.58
41.70
41.59
43.11
38.76
34.17
32.22
34.82
37.31
63.30
49.29
35.67
Na
115.00
156.56
132.67
139.51
159.43
168.99
150.35
146.85
137.30
152.22
138.66
165.29
200.98
210.66
205.35
209.06
218.15
175.77
145.76
135.88
142.89
199.90
330.52
276.11
197.18
Na
58.56
90.19
88.64
65.79
67.00
62.46
51.08
52.90
52.67
49.38
36.59
39.99
47.41
44.15
50.39
57.05
52.46
33.53
28.15
27.35
119.09
125.89
160.70
105.68
104.69
31.03
186.36
16.18
37.56
176.83
58.70
27.40%
34.59%
43.59%
21.77%
27.51%
57.45%
Year
AISD
AISU
Spread
Facility fee
Unit
basis points
basis points
basis points
1986
1987
1988
1989
1990(Recession)
1991(Recession)
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001(Recession)
2002
2003
2004
2005
2006
2007(Recession)
2008(Recession)
2009(Recession)
2010
2011
37.50
124.88
157.49
163.06
144.52
160.45
162.22
150.59
141.53
143.92
155.86
145.10
170.41
205.86
191.15
183.12
206.50
217.27
203.76
182.01
178.73
194.17
239.30
388.88
317.55
235.93
12.50
36.90
38.17
38.14
35.57
37.48
36.37
32.13
29.25
27.64
27.69
26.08
28.57
34.00
29.45
29.35
30.01
33.00
30.67
27.85
26.27
27.37
34.29
61.42
46.76
32.10
Total mean
Stdev
(in% of total
mean)
190.42
33.86%
38
Upfront fee
Table III
Stylized facts about spreads and fees
This table provides a univariate analysis of spreads and fees. AISD denotes All-In-Spread-Drawn, AISU denotes All-In-SpreadUndrawn. For a variable definition see Appendix A. We report t-values based on Welch–Satterthwaite adjusted standard errors in
parentheses. ***, **, * denote significance at the 1, 5 and 10 % level, respectively.
Variable
Size
Total assets < median
Total assets > median
Difference
Maturity
Maturity < median
Maturity > median
Difference
Relationships
Rel(Dummy) = 0
Rel(Dummy) = 1
Difference
Cyclicality
No NBER recession
NBER recession
Difference
Credit risk
Investmentgrade
Non-Investmentgrade
Difference
Liquidity
Current ratio < median
Current ratio > median
Difference
(1)
(2)
(3)
(4)
(5)
(6)
(7)
AISD
AISU
Spread
Facility fee
Commitment
fee
Upfront fee
Letter of
credit fee
217.56
148.18
36.80
24.65
214.94
142.32
24.69
13.87
37.74
35.85
54.39
59.33
187.37
154.80
-69.38***
(-44.08)
-12.15***
(-42.80)
-72.62***
(-45.59)
-10.82***
(-22.79)
-1.88***
(-5.15)
4.94***
(2.66)
-32.57***
(-14.30)
181.65
199.26
30.84
31.30
176.52
196.27
16.82
15.19
37.27
37.94
50.76
66.34
190.29
161.41
17.60***
(10.77)
0.46
(1.53)
19.75***
(11.91)
-1.63***
(-5.06)
0.67**
(-2.05)
15.58***
(8.74)
-28.88
(-13.48)
222.41
180.98
35.87
29.73
219.51
176.58
18.85
15.75
39.44
36.93
73.03
53.06
197.53
170.37
-41.43***
(-20.75)
-6.14***
(-17.29)
-42.93***
(-21.25)
-3.11***
(-5.98)
-2.52***
(-6.79)
-19.97***
(-9.21)
-27.16***
(-10.83)
188.31
211.66
30.76
33.65
184.29
207.15
16.15
16.47
37.17
41.43
56.16
84.02
173.30
211.35
23.35***
(7.27)
2.89***
(4.94)
22.86***
(7.02)
0.31
(0.52)
4.25***
(6.49)
27.86***
(6.45)
38.06***
(9.39)
86.57
241.41
15.24
42.68
78.07
239.09
11.99
31.07
25.09
43.46
40.50
64.43
99.91
209.09
154.84***
(76.24)
27.44***
(72.76)
161.02***
(79.02)
19.08***
(20.56)
18.37***
(28.94)
23.93***
(8.67)
109.18***
(33.90)
184.31
183.66
-0.65
(-0.39)
29.46
31.64
2.18***
(7.04)
179.71
179.83
0.12
(0.07)
14.76
18.02
3.25***
(9.31)
38.52
36.00
-2.51***
(-7.21)
61.86
51.75
-10.11***
(-5.40)
179.66
171.11
-8.56***
(-3.76)
39
Table IV
Effect of lending relationships on spreads and fees
This table provides results of a linear regression of price terms on a relationship dummy and control variables. The price terms are the
AISD, the AISU, the spread, the facility fee, the commitment fee and the upfront fee as indicated in the second row. For variable
definitions see Appendix A. Fixed effects for year, loan purpose, loan type, one-digit SIC code and borrower credit rating are not
shown. We report t-values based on standard errors clustered at the borrowing firm in parentheses. ***, **, * denote significance at
the 1, 5 and 10 % level, respectively.
Variable
REL(Dummy)
Log(Facility Amount)
Log(Maturity)
Secured (0/1)
Sole Lender (0/1)
Syndicate size
Lead size
Log(Total assets)
Log(1+Coverage)
Leverage
Profitability
Tangibility
Current ratio
Market-to-book
Year fixed effects
Loan purpose fixed effects
Loan type fixed effects
One-digit SIC code fixed effects
Borrower credit rating fixed effects
Observations
R-squared
Adj. R-squared
(1)
(2)
(3)
(4)
(5)
(6)
(7)
AISD
AISU
Spread
Facility fee
Commitment
fee
Upfront fee
Letter of
credit fee
-10.626***
(-5.42)
-10.272***
(-9.84)
-12.137***
(-5.06)
52.495***
(25.06)
-4.282
(-1.52)
-0.356***
(-3.75)
3.236***
(3.99)
-6.177***
(-5.23)
-16.681***
(-12.49)
20.374***
(3.05)
-25.913**
(-2.29)
-7.631
(-1.48)
-3.972***
(-4.02)
-5.066***
(-4.34)
-0.244
(-0.72)
-2.039***
(-9.27)
-0.086
(-0.19)
9.384***
(23.15)
-2.952***
(-6.21)
-0.013
(-0.53)
0.538***
(3.93)
0.157
(0.76)
-2.086***
(-9.76)
5.553***
(4.82)
-1.270
(-0.73)
-1.086
(-1.24)
-0.158
(-0.83)
-0.521***
(-2.64)
-10.949***
(-5.60)
-10.517***
(-10.01)
-11.478***
(-4.79)
54.523***
(25.95)
-3.883
(-1.38)
-0.375***
(-3.94)
3.270***
(4.29)
-6.554***
(-5.52)
-16.771***
(-12.51)
19.785***
(2.93)
-22.923**
(-2.04)
-7.372
(-1.43)
-3.852***
(-3.86)
-4.899***
(-4.21)
1.012**
(2.01)
-0.731***
(-2.90)
-2.724***
(-4.14)
5.578***
(6.65)
-2.125***
(-2.76)
0.022
(1.02)
0.157
(1.13)
-0.424*
(-1.80)
-1.327***
(-3.82)
3.469*
(1.73)
-1.801
(-0.84)
-2.652**
(-2.37)
0.041
(0.13)
-0.603**
(-2.04)
-0.644
(-1.59)
-2.346***
(-8.36)
1.201**
(2.30)
8.387***
(19.42)
-3.780***
(-6.72)
-0.007
(-0.17)
0.707***
(3.16)
0.622**
(2.20)
-2.140***
(-8.87)
5.524***
(4.40)
-1.800
(-0.91)
-0.050
(-0.05)
-0.107
(-0.51)
-0.329
(-1.37)
-15.990***
(-5.92)
-1.031
(-0.85)
-1.432
(-0.59)
21.197***
(8.15)
7.817**
(2.19)
-0.118
(-1.33)
1.593**
(2.36)
2.873**
(2.24)
-4.967***
(-2.82)
-7.630
(-0.97)
-23.119*
(-1.69)
-3.113
(-0.56)
-3.018***
(-2.70)
3.239**
(2.57)
-6.294***
(-2.86)
-17.527***
(-11.04)
-10.555***
(-3.31)
58.153***
(25.00)
-22.569***
(-6.53)
-0.090
(-0.59)
6.463***
(5.26)
2.452*
(1.70)
-9.320***
(-7.37)
37.985***
(5.32)
-17.589*
(-1.73)
-1.446
(-0.26)
-2.416**
(-2.38)
-4.814***
(-3.94)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
18,433
0.61
0.61
13,451
0.57
0.57
18,433
0.62
0.62
5,134
0.51
0.50
8,987
0.40
0.40
3,987
0.34
0.33
6,361
0.57
0.57
40
Table V
Effects of lending relationships on spreads and fees by loan type
This table provides results of a linear regression of price terms on a relationship dummy and control variables split by loan type.
Columns (1) and (2) report results for term loans and columns (3) to (7) report results for revolver loans. The price terms are the
spread and the upfront fee for term loans and the spread, facility fee, commitment fee, upfront fee and letter of credit fee for revolvers
as indicated in the third row. For variable definitions see Appendix A. Fixed effects for year, loan purpose, loan type, one-digit SIC
code and borrower credit rating are not shown. We report t-values based on standard errors clustered at the borrowing firm in
parentheses. ***, **, * denote significance at the 1, 5 and 10 % level, respectively.
Term loans
Variables
REL(Dummy)
Log(Facility Amount)
Log(Maturity)
Secured (0/1)
Sole Lender (0/1)
Syndicate size
Lead size
Log(Total assets)
Log(1+Coverage)
Leverage
Profitability
Tangibility
Current ratio
Market-to-book
Year fixed effects
Loan purpose fixed effects
Loan type fixed effects
One-digit SIC code fixed effects
Borrower credit rating fixed effects
Observations
R-squared
Adj. R-squared
Revolver
(1)
(2)
(3)
(4)
Facility fee
(5)
Commitment
fee
(6)
Upfront
fee
(7)
Letter of
credit fee
Spread
Upfront fee
Spread
-18.879***
(-4.80)
-3.656*
(-1.82)
-4.356
(-1.03)
48.111***
(11.91)
-8.171
(-1.49)
-0.799***
(-4.73)
0.914
(0.71)
-9.709***
(-4.13)
-24.308***
(-7.81)
-6.162
(-0.52)
-53.883*
(-1.95)
6.995
(0.70)
-6.421***
(-3.31)
-6.155**
(-2.35)
-24.514***
(-5.15)
4.054*
(1.88)
-10.318**
(-2.53)
23.950***
(4.16)
7.600
(1.21)
-0.244**
(-2.54)
1.240
(1.11)
-1.768
(-0.69)
-5.047
(-1.39)
-22.776*
(-1.65)
-52.390*
(-1.94)
-5.583
(-0.52)
-6.405***
(-3.22)
3.292
(1.26)
-5.326***
(-3.20)
-13.586***
(-11.58)
-12.691***
(-5.42)
58.335***
(28.42)
-1.308
(-0.53)
0.069
(0.73)
4.314***
(5.95)
-5.903***
(-5.32)
-13.223***
(-12.13)
33.522***
(5.50)
-9.963
(-1.19)
-14.940***
(-3.28)
-2.592***
(-2.93)
-5.322***
(-5.39)
1.115**
(2.41)
-0.713***
(-2.83)
-2.898***
(-4.24)
5.870***
(6.96)
-2.297***
(-3.08)
0.005
(0.23)
0.157
(1.20)
-0.378
(-1.63)
-1.275***
(-3.84)
3.331*
(1.66)
-1.424
(-0.68)
-2.621**
(-2.48)
0.085
(0.29)
-0.599**
(-2.06)
-0.331
(-0.89)
-2.361***
(-8.26)
0.751
(1.46)
7.907***
(19.14)
-3.682***
(-6.59)
-0.011
(-0.24)
0.689***
(3.15)
0.673**
(2.38)
-1.876***
(-8.37)
6.308***
(5.32)
-2.812
(-1.54)
-0.466
(-0.44)
-0.237
(-1.20)
-0.546**
(-2.45)
-8.727***
(-4.09)
-6.551***
(-4.82)
8.542***
(3.22)
21.394***
(10.31)
5.676*
(1.90)
0.273**
(2.28)
1.922***
(2.63)
5.188***
(4.45)
-5.253***
(-3.98)
-2.040
(-0.31)
-10.941
(-0.98)
-0.543
(-0.12)
-1.489
(-1.49)
2.725***
(2.59)
-6.294***
(-2.86)
-17.527***
(-11.04)
-10.555***
(-3.31)
58.153***
(25.00)
-22.569***
(-6.53)
-0.090
(-0.59)
6.463***
(5.26)
2.452*
(1.70)
-9.320***
(-7.37)
37.985***
(5.32)
-17.589*
(-1.73)
-1.446
(-0.26)
-2.416**
(-2.38)
-4.814***
(-3.94)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
5,176
0.40
0.39
1,420
0.39
0.36
13,257
0.65
0.65
4,964
0.52
0.51
8,639
0.40
0.39
2,567
0.36
0.34
6,361
0.57
0.57
41
Table VI
Channels of the relationship effect
This table provides results of a linear regression of price terms on interaction terms between a relationship dummy and control
variables from previous regressions (non-price terms, borrower characteristics). The control variables itself are included in the set of
independent variables but coefficients are not shown for reasons of brevity. Columns (1) and (2) report results for term loans and
columns (3) to (7) report results for revolver. The price terms are the spread and the upfront fee for term loans and the spread, facility
fee, commitment fee, upfront fee and letter of credit fee for revolvers as indicated in the third row. For variable definitions see
Appendix A. Fixed effects for year, loan purpose, loan type, one-digit SIC code and borrower credit rating are not shown. We report tvalues based on standard errors clustered at the borrowing firm in parentheses. ***, **, * denote significance at the 1, 5 and 10 %
level, respectively.
Revolver
Term loans
(1)
(2)
(3)
(4)
Spread
Upfront fee
Spread
Facility fee
(5)
Commitment
fee
-6.941*
(-1.78)
-18.097**
(-2.42)
-11.457
(-1.31)
1.204
(0.11)
1.998***
(3.78)
-15.069**
(-2.31)
1.246
(0.33)
-13.109***
(-2.61)
-6.767
(-0.32)
30.936
(0.78)
34.389*
(1.84)
5.829
(1.53)
-3.252
(-0.66)
96.277**
(2.37)
0.515
(0.10)
-3.052
(-0.32)
-17.840
(-1.59)
2.942
(0.21)
0.810
(1.37)
-20.042***
(-2.97)
-2.330
(-0.47)
-9.722
(-1.36)
32.300
(1.14)
5.551
(0.11)
25.937
(1.13)
8.331*
(1.85)
5.162
(0.86)
9.309
(0.17)
3.796
(1.58)
-9.508***
(-3.31)
-15.112***
(-3.87)
2.031
(0.42)
0.139
(0.49)
-6.657**
(-2.17)
0.493
(0.28)
-2.860
(-1.42)
20.757*
(1.79)
-16.719
(-1.05)
1.735
(0.21)
3.103*
(1.89)
1.359
(0.70)
17.132
(1.04)
0.364
(0.59)
0.757
(1.27)
4.798***
(2.60)
1.264
(0.77)
-0.045
(-0.77)
0.748
(1.13)
0.394
(0.85)
-1.484
(-1.64)
-7.320
(-1.59)
0.670
(0.11)
-0.493
(-0.19)
-0.538
(-0.70)
0.332
(0.52)
-2.424
(-0.50)
-0.691
(-1.37)
-1.380*
(-1.84)
0.210
(0.25)
0.907
(0.92)
0.070
(0.85)
-1.637**
(-2.09)
-0.004
(-0.01)
-0.178
(-0.42)
2.724
(1.31)
4.377
(1.35)
-1.976
(-1.07)
-0.018
(-0.05)
-0.357
(-0.86)
9.189**
(2.24)
Controls for non-price terms
and borrower characteristics
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Year fixed effects
Loan purpose fixed effects
Loan type fixed effects
One-digit SIC code fixed effects
Borrower credit rating fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
5,176
0.41
0.40
1,402
0.41
0.37
13,257
0.66
0.65
4,964
0.52
0.51
8,639
0.40
0.40
2,567
0.37
0.34
6,361
0.58
0.57
Variables
REL(Dummy) x Log(Facility Amount)
REL(Dummy) x Log(Maturity)
REL(Dummy) x Secured (0/1)
REL(Dummy) x Sole Lender (0/1)
REL(Dummy) x Syndicate size
REL(Dummy) x Lead size
REL(Dummy) x Log(Total assets)
REL(Dummy) x Log(1+Coverage)
REL(Dummy) x Leverage
REL(Dummy) x Profitability
REL(Dummy) x Tangibility
REL(Dummy) x Current ratio
REL(Dummy) x Market-to-book
REL(Dummy)
Observations
R-squared
Adj. R-squared
42
(6)
Upfront
fee
(7)
Letter of
credit fee
8.281**
4.838
(2.33)
(1.48)
-10.119*** -21.448***
(-2.90)
(-4.34)
-11.270**
-8.204*
(-2.48)
(-1.79)
7.393
3.718
(1.13)
(0.54)
-0.274
0.220
(-0.87)
(0.50)
-1.516
-2.783
(-0.41)
(-0.77)
-4.198*
-3.140
(-1.65)
(-1.31)
0.500
-4.796*
(0.19)
(-1.86)
26.734**
16.953
(2.01)
(1.28)
-0.662
-17.078
(-0.03)
(-0.78)
-4.042
7.253
(-0.40)
(0.68)
-0.040
4.227**
(-0.02)
(2.05)
2.124
-2.511
(0.92)
(-0.98)
15.532
79.032***
(0.72)
(3.27)
Table VII
Liquidity insurance hypothesis
This table provides results for a regression of the excess AISD on a relationship dummy and interaction terms with the relationship
dummy. The excess AISD (“Excess AISD”) is defined as the AISD less the AISU and it represents the difference between spreads and
fees paid on drawn amounts and fees paid on undrawn amounts. A zero Excess AISD means that a borrower is fully insured against
liquidity shocks, i.e. payments are independent of the state of nature (high/low liquidity needs). A high Excess AISD means that a
borrower is not or is only partially insured against liquidity shocks, i.e. payments are much higher in the bad state (high liquidity
needs) compared to the good state (low liquidity needs). Column (1) provides results based on the relationship dummy and control
variables. Columns (2) to (4) report results for introducing interaction terms between the relationship dummy and proxies for
asymmetric information. For variable definitions see Appendix A. Control variables (price terms and borrower characteristics), fixed
effects for year, loan purpose, loan type, one-digit SIC code and borrower credit rating are not shown. We report t-values based on
standard errors clustered at the borrowing firm in parentheses. ***, **, * denote significance at the 1, 5 and 10 % level, respectively.
(1)
Variables
REL(Dummy)
(2)
Excess AISD
-4.728***
(-3.18)
REL(Dummy) x Log(Total Assets)
Excess AISD
-30.068***
(-5.64)
4.257***
(5.19)
REL(Dummy) x Not rated
(3)
(4)
Excess AISD
Excess AISD
1.142
(0.52)
-8.306***
(-4.33)
-9.119***
(-3.11)
REL(Dummy) x No. of analysts
0.749***
(3.94)
Log (Total Assets)
-8.648***
(-7.45)
Not rated
-20.294**
(-2.34)
No. of analysts
-0.955***
(-4.85)
Controls for price terms
Controls for borrower characteristics
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Year fixed effects
Loan purpose fixed effects
Loan type fixed effects
One-digit SIC code fixed effects
Borrower credit rating fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
13,257
0.61
0.61
13,257
0.61
0.61
13,257
0.61
0.61
13,257
0.61
0.61
Observations
R-squared
Adj. R-squared
43
Table VIII
Robustness test using a matched sample of letter of credit sub-limits
This table provides results for a regression of the excess AISD and the excess letter of credit fee on a relationship dummy and interaction terms with the relationship dummy. The
excess AISD (“Excess AISD”) is defined as the AISD less the AISU and it represents the difference between spreads and fees paid on drawn amounts and fees paid on undrawn
amounts. The excess letter of credit fee (“Excess LCF”) is defined as the difference between the letter of credit fee and the commitment fee and it represents the difference between
fees paid on drawn amounts on letters of credit and fees paid on undrawn amounts of letters of credit. Columns (1), (3), (5), and (7) provide results for the excess letter of credit
fee, columns (2), (4), (6), and (8) provide results for a matched sample of credit lines from the same borrower originated on the same date with the same maturity. Columns (5) and
(6) include data from 1993 which is the first year where rating data is available on Compustat. For variable definitions see Appendix A. Control variables (price terms and
borrower characteristics), fixed effects for year, loan purpose, loan type, one-digit SIC code and borrower credit rating are not shown. We report t-values based on standard errors
clustered at the borrowing firm in parentheses. ***, **, * denote significance at the 1, 5 and 10 % level, respectively.
Variables
REL(Dummy)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Letter of credit
Credit line
Letter of credit
Credit line
Letter of credit
Credit line
Letter of credit
Credit line
Excess LCF
Excess AISD
Excess LCF
Excess LCF
Excess AISD
Excess LCF
Excess AISD
-5.151***
(-2.60)
-7.636***
-3.86
-6.443
(-0.73)
0.214
(0.16)
-1.171
(-0.38)
-1.246
(-0.38)
-3.593
(-1.44)
-8.716
(-3.43)
-4.944
(-1.27)
-10.075**
(-2.43)
-0.378
(-1.12)
0.305
(0.91)
-0.218
(-0.63)
-0.756**
(-2.19)
REL(Dummy) x Log(Total Assets)
Excess AISD
-26.040***
(-3.05)
3.041**
(2.26)
REL(Dummy) x Not rated
REL(Dummy) x No. of analysts
Log (Total Assets)
0.736
(0.46)
-4.293**
(-2.54)
Not rated
-18.167**
(-2.24)
-14.816
(-1.48)
No. of analysts
Controls for price terms
Controls for borrower characteristics
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Year fixed effects
Loan purpose fixed effects
Loan type fixed effects
One-digit SIC code fixed effects
Borrower credit rating fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
6,361
0.53
0.52
6,361
0.56
0.55
6,361
0.53
0.52
6,361
0.56
0.55
6,004
0.54
0.53
6,004
0.57
0.56
6,361
0.53
0.52
6,361
0.56
0.55
Observations
R-squared
Adj. R-squared
Difference between REL(Dummy) terms
or REL(Dummy) interaction terms
Prob > F
-2.485*
0.093
2.827***
-5.131*
0.683***
0.009
0.084
0.003
44
Table IX
A Measure for the Total Cost of Borrowing
This table provides results for both the AISD and the Total Cost of Borrowing (TCB). The TCB includes upfront fees, fees on
undrawn amounts and letter of credit fees in addition to the components of AISD. Columns (1) and (2) provide results for AISD and
TCB for term loans and columns (3) and (4) for revolver loans. Panel A reports descriptive statistics, Panel B reports univariate
results and Panel C reports multivariate results. For variable definitions see Appendix A. Control variables (price terms and borrower
characteristics), fixed effects for year, loan purpose, loan type, one-digit SIC code and borrower credit rating are not shown. We report
t-values based on standard errors clustered at the borrowing firm in parentheses. ***, **, * denote significance at the 1, 5 and 10 %
level, respectively.
Term Loans
Revolver
(1)
(2)
(3)
(4)
AISD
TCB
AISD
TCB
N
7,760
7,760
16,959
16,959
Mean
271.54
293.54
153.31
115.42
Std.Dev
135.40
143.71
106.68
77.09
P25
175.00
200.81
62.50
54.28
Median
250.00
275.59
137.50
103.17
P75
325.00
354.46
225.00
162.85
275.40
248.05
296.50
271.28
188.48
110.78
137.70
88.22
-27.35***
(-8.70)
-25.22***
(-7.50)
-77.70***
(-50.56)
-49.48***
(-43.60)
264.53
278.82
296.03
290.95
157.55
148.30
123.82
105.53
14.29***
(4.67)
-5.08
(-1.56)
-9.25***
(-5.67)
-18.28**
(-15.75)
291.99
264.18
318.00
284.74
182.55
145.48
136.67
109.74
-27.81***
(-7.67)
-33.26***
(-8.69)
-37.07***
(-18.30)
-26.93***
(-18.73)
268.99
298.27
289.16
339.49
151.17
174.32
113.31
136.17
29.28***
(4.70)
50.33***
(7.57)
23.15***
(7.08)
22.86***
(9.17)
189.05
283.04
220.83
300.63
72.62
209.49
60.93
154.43
93.99***
(16.42)
79.80***
(12.70)
136.87
(65.24)
93.50***
(59.14)
275.12
250.14
-24.98***
(-7.74)
300.22
268.94
-31.28***
(-9.09)
145.08
155.81
10.73***
(6.32)
111.25
114.95
3.70**
(2.99)
Panel A: Descriptive statistics
Panel B: Univariate tests
Size
Total assets < median
Total assets > median
Difference
Maturity
Maturity < median
Maturity > median
Difference
Relationships
Rel(Dummy) = 0
Rel(Dummy) = 1
Difference
Cyclicality
No NBER recession
NBER recession
Difference
Credit risk
Investmentgrade
Non-Investmentgrade
Difference
Liquidity
Current ratio < median
Current ratio > median
Difference
45
Panel C: Multivariate results
Term loans
REL(Dummy)
Log(Facility Amount)
Log(Maturity)
Secured (0/1)
Sole Lender (0/1)
Syndicate size
Lead size
Log(Total assets)
Log(1+Coverage)
Leverage
Profitability
Tangibility
Current ratio
Market-to-book
Year fixed effects
Loan purpose fixed effects
Loan type fixed effects
One-digit SIC code fixed effects
Borrower credit rating fixed
effects
Observations
R-squared
Adj. R-squared
Revolver
(1)
AISD
(2)
TCB
(3)
AISD
(4)
TCB
-18.942***
(-4.81)
-3.510*
(-1.74)
-5.024
(-1.18)
48.306***
(11.95)
-8.723
(-1.59)
-0.790***
(-4.72)
0.888
(0.69)
-9.678***
(-4.13)
-24.337***
(-7.87)
-5.567
(-0.48)
-55.756**
(-2.02)
7.082
(0.71)
-6.410***
(-3.31)
-6.342**
(-2.43)
-25.957***
(-6.40)
-1.480
(-0.72)
-55.838***
(-12.12)
55.164***
(13.26)
-6.540
(-1.14)
-0.823***
(-4.95)
0.976
(0.73)
-10.137***
(-4.20)
-25.173***
(-8.15)
-9.479
(-0.80)
-77.257***
(-2.77)
6.147
(0.60)
-7.834***
(-3.87)
-4.961*
(-1.89)
-4.813***
(-2.89)
-13.446***
(-11.43)
-13.813***
(-5.90)
55.503***
(27.11)
-1.819
(-0.73)
0.090
(0.94)
4.282***
(5.39)
-5.267***
(-4.76)
-13.181***
(-12.16)
33.932***
(5.66)
-13.006
(-1.54)
-15.387***
(-3.40)
-2.765***
(-3.20)
-5.464***
(-5.45)
-5.447***
(-4.68)
-11.704***
(-14.08)
-18.507***
(-11.22)
41.710***
(30.02)
-1.272
(-0.72)
0.232***
(3.48)
3.681***
(5.47)
-0.344
(-0.44)
-10.518***
(-13.61)
20.485***
(4.61)
-12.997**
(-2.13)
-9.944***
(-3.26)
-2.335***
(-3.86)
-2.144***
(-3.05)
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
5,176
0.40
0.39
5,176
0.44
0.43
13,257
0.64
0.64
13,257
0.67
0.67
46
Appendix A
Explanation of variables
Variable
Source
Description
General
Revolver
DealScan
Term Loan
DealScan
Lead arranger
DealScan
REL(Dummy)
DealScan
Loans with type “Revolver/Line < 1 Yr.”, “Revolver/Line >= 1 Yr.”, “364-Day Facility”,
“Limited Line” or “Revolver/Term Loan” as indicated in the facility table in DealScan
Loans with type “Term Loan”, “Term Loan A”-“Term Loan H”,or “Delay Draw Term Loan” as
indicated in the facility table in DealScan
We follow Bharath et al. (2011) and define a lender as a lead arranger if at least one of the
following conditions is met: 1) LeadArrangerCredit = Yes in the LenderShares table of DealScan,
2) LenderRole is equal to “Agent”, “Admin agent”, “Arranger” or “Lead bank” in the
LenderShares table of DealScan, 3) the lender is the sole lender.
Dummy equal to 1 if one of the lead arrangers of the current facility has provided a syndicated
loan to the same borrower in the past five years
Price terms
AISD
AISU
Spread
DealScan
DealScan
DealScan
Facility fee
Commitment fee
Upfront fee
Letter of credit fee
Total cost of borrowing
DealScan
DealScan
DealScan
DealScan
DealScan
Non-price terms
Facility amount
Dealscan
Maturity
Secured (0/1)
DealScan
DealScan
Sole Lender (0/1)
DealScan
Syndicate Size
DealScan
Lead Size
DealScan
Borrower characteristics
Total assets
Coverage
Leverage
Profitability
Tangibility
Current ratio
Market-to-book
Compustat
Compustat
Compustat
Compustat
Compustat
Compustat
Compustat
Investment grade (0/1)
Compustat
Not rated (0/1)
Compustat
All-In-Spread-Drawn, defined as the sum of the spread over LIBOR plus the facility fee
All-In-Spread-Undrawn, defined as the sum of the facility fee and the commitment fee
Spread over LIBOR (non-LIBOR-based loans are excluded from the sample) paid on drawn
amounts on lines of credit
Fee paid on the entire committed amount, regardless of usage
Fee paid on the unused amount of loan commitments
Fee paid upon completion of a syndicated loan
Fee paid on drawn amounts on the letter of credit sub-limit
Total cost of borrowing taking into account the spread, the facility fee, the commitment fee, the
upfront fee and the letter of credit fee (see Section IV for a definition)
Facility amount in USD mn as indicated in the field FacilityAmt in the facility table in DealScan,
adjusted for inflation in year 2005 dollars
Facility maturity in months as indicated in the field Maturity in the facility table in DealScan
Dummy equal to 1 if a facility is secured as indicated by the field Secured in the facility table in
DealScan
Dummy equal to 1 if a facility is provided solely by a single lender as indicated by the
LenderShares table in DealScan
Number of lenders (lead arranger and participants) of a syndicated loan facility as indicated by
the LenderShares table in DealScan
Number of lead arrangers of a syndicated loan facility as indicated by the LenderShares table in
DealScan
Total assets in USD mn, adjusted for inflation in year 2005 dollars
Ratio of EBITDA to interest expenses
Ratio of book value of total debt to the book value of assets
Ratio of EBITDA to sales
Ratio of property, plant and equipment to total assets
Ratio of current assets to current liabilities
Ratio of (book value of assets – book value of equity + market value of equity) to book value of
assets
Dummy equal to 1 if the S&P rating is BBB- or higher. For non-rated borrowers this dummy is
equal to zero
Dummy equal to 1 if no S&P rating for the borrower exists
47
Appendix B
Availability of spreads and various fee types in the DealScan database
This table presents descriptive statistics about the availability of spread and fee data in the DealScan database. The column Sample describes the restrictions on the sample
selection. The column Loan Type denotes the loan type. N denotes the number of facilities. % of Sample denotes the percentage of Term Loans, Revolvers and Other Loans. AISD
(0/1), AISU (0/1), Spread (0/1), Facility fee (0/1), Commitment fee (0/1), Upfront fee (0/1), and Letter of credit fee (0/1) denote the mean of a dummy variable which is equal to 1 if
the AISD, the AISU, the spread (over LIBOR or a similar measure), a facility fee, a commitment fee, a letter of credit fee or an upfront fee is available in DealScan.1 For variable
definitions see Appendix A.
Facility
CommitUpfront
Letter of
AISD
AISU
Spread
fee
ment fee
fee
credit fee
Sample
Loan Type
N
% of Sample
(0/1)
(0/1)
(0/1)
(0/1)
(0/1)
(0/1)
(0/1)
All Facilities
112,743
100%
0.79
0.36
0.71
0.11
0.28
0.17
0.15
Term Loan
Revolver
36,040
64,689
32%
57%
0.86
0.84
0.02
0.60
0.77
0.74
0.02
0.17
0.05
0.45
0.20
0.17
0.00
0.23
Other
12,014
11%
0.34
0.06
0.32
0.04
0.10
0.10
0.11
LIBOR-based loans2
All Facilities
79,646
100%
0.99
0.45
1.00
0.14
0.35
0.17
0.17
Compustat data available
All Facilities
38,574
100%
0.99
0.60
1.00
0.20
0.44
0.23
0.29
Ultimate parent available
All Facilities
38,278
100%
0.99
0.60
1.00
0.20
0.44
0.23
0.29
Only repeated borrowers
All Facilities
29,372
100%
0.99
0.61
1.00
0.22
0.43
0.21
0.29
Basic data items available3
All Facilities
24,719
100%
1.00
0.70
1.00
0.24
0.49
0.22
0.33
Term Loan
Revolver
7,760
16,959
31%
69%
1.00
1.00
0.04
1.00
1.00
1.00
0.03
0.34
0.06
0.68
0.27
0.20
0.00
0.48
US-Sample, 1986-2011, Nonfinancials
1)
2)
3)
Missing data for certain fee types can indicate non-existence of this particular fee type or a selection bias in the reporting of fees in DealScan. We manually investigated a random sample of 50 individual loan
contracts which we obtained from EDGAR: Missing data with respect to commitment fees, facility fees and letter of credit fees in DealScan indicates non-existence of this fee type, i.e. there is no reporting bias of
DealScan for these fee types. DealScan reports upfront fees for only 22% of all syndicated loans in our sample, however, from our random sample of loan contracts we find evidence that at least 80% contain an
upfront fee. We searched the 10-K and 10-Q filings of the companies in our random sample for “Debt issuance costs” in the “Cash flows from financing activities” section of the statement of cash flows. The crosssectional correlation between the upfront fee reported in DealScan and the SEC filings is very high (~0.85), suggesting indeed that the information contained in DealScan is informative.
We include only LIBOR-based loans to allow for a comparison of spreads across different loans. Out of the 33,097 loans discarded in this step, 47% are based on a benchmark other than LIBOR (e.g. Fed Funds
rate or fixed rate loans) and 53% have missing information on the base rate. Based on a closer inspection of these latter loans the missing fields are indeed due to missing information and not to “pure fee” loans
such as pure letters of credit.
Maturity (1,186 missing), Loan amount (0 missing), AISD (273 missing), AISU for Revolver (2,716 missing), SIC-code (154 missing), exclude loan type = "Other" (1,198 facilities).
Numbers in parenthesis sum up to more than the total number of excluded facilities due to multiple missing values on some facilities.
48