The Impact of Changes in Balance Sheet Covenant Protection
on the Design of Private Loan Contracts
Peter Demerjian*
Goizeuta Business School
Emory University
1300 Clifton St NE
Atlanta GA 30322
October 2010
Abstract
I examine the economic implications of the recent decline in use of balance sheet-based financial
covenants in private debt contracts. I find the borrowers that experience a drop in balance sheet
covenant protection to have both higher interest rates (35.3 basis points) and shorter maturities
(7.4 months) for their loans. However, I find no association between the decline in balance sheet
covenant use and the inclusion of either income statement covenants or restrictive covenants. I
also find the costly effects of dropping balance sheet covenants are restricted to cases where the
specific demand for balance sheet covenants is low, but the overall demand for contractual
protection is high.
* 404-727-2329. [email protected]
1
Introduction
Recent years have seen a sharp decline in the use of debt covenants written on balance
sheet values. As documented in Demerjian (2010a), over the period 1996 through 2007, balance
sheet covenant use in private loans fell from 80% to 30%.1 There are a number of explanations
for this change. It may be that the overall demand for protection in debt contracts is decreasing;
that is, borrowers may have improved over this time period and thus lenders require less
protection written into the contract. Or, it could be due to changes in the underlying economics
of borrowers. For example, if borrowers’ value is comprised of fewer fixed assets and more
growth opportunities, the balance sheet may provide less information than it did in the past.
Another explanation is that the quality of information from the balance sheet is declining.
Demerjian (2010a) argues that the conceptual shift to the “balance sheet approach” and the
increased use of fair value accounting has rendered the balance sheet insufficiently reliable for
contracting. Finally, borrowers may desire greater flexibility and opt to avoid covenants in
contracts, even if this means increased strictness of other terms.
Given the significant decrease in balance sheet covenant use, there are likely
consequences to this change. In this study, I assess the economic impact of the decline, focusing
on changes in the design of debt contracts. I distinguish between two broad motivations for the
reduced use of balance sheet covenants: changes in firm-level demand for covenant protection,
and changes in covenant-level demand. Firm-level demand refers to the overall demand for
protection in the debt contract by the creditor. This demand will be increasing in the default risk
of the borrower, and will drive the aggregate amount of protection that the loan provisions
provide. Covenant-level demand refers to the demand for a specific provision, in this study
1
Balance sheet covenants include those written exclusively with balance sheet values: net worth, leverage, or
current ratio.
1
balance sheet covenants. While not mutually exclusive, these two types of demand are distinct:
changes in covenant-level demand can impact the use of a specific covenant even when firmlevel demand is constant (or moving in the opposite direction as covenant-level demand). This
distinction leads to different predictions based on whether the decline in balance sheet covenant
use is due to changes in firm-level or covenant-level demand. If firm-level demand drives the
decline in balance sheet covenants, I do not anticipate any change in other loan provisions; the
reduction in protection due to not having a balance sheet covenant is offset by the lower demand
for protection. In contrast, if the decline is due to a decrease in covenant-level demand, and firmlevel demand has not changed (or has increased), I expect that creditors will require
compensation for the reduction in covenant protection by tightening other loan provisions. I
examine the relation between changes in balance sheet covenant protection and four other
aspects of loan contract design: the interest spread, the maturity, the use of income statement
covenants, and the use of general covenants.
I collect 1,458 private loan observations from 729 borrowers; the sample is designed so
that each borrower has a balance sheet covenant in their earlier loan (the Pre-Drop period) and no
balance sheet covenant in their later loan (the Drop period). I then analyze changes in the loan
contract design between the Pre-Drop and Drop periods. Observations are split based on the
change in default risk, my proxy for changes in firm-level demand. If default risk decreased, I
label the observations “Low Risk”; these are cases where the firm-level demand for protection
declined, and I expect that any loosening of loan provisions (including removing balance sheet
covenants) can be attributed to improvement in the quality of borrowers. If default risk increased,
I term these borrowers “High Risk”; in these cases, firm-level demand for protection has
increased, so the drop in balance sheet covenant use is due to decline in the covenant-level
2
demand for balance sheet covenants. I expect tightening of contract provisions in High Risk
observations, but not in Low Risk.
The empirical results bear out this prediction. Using a difference-in-differences research
design, I find that dropping a balance sheet covenant in a period of increasing firm-level demand
is associated with higher interest spreads and shorter maturities. I find no association between
dropped balance sheet covenants and either income statement covenant inclusion or general
covenant inclusion.
In economic terms, the impact on loan spread appears substantial. For High Risk
borrowers without a balance sheet covenant, interest spreads are 35.3 basis points higher. Based
on the average loan size, this leads to an increase in interest expense of $2.25M, or
approximately 5.4% of income. If balance sheet covenants are becoming less useful for
contracting and hence not used in contracts (i.e. due either to changes in borrower characteristics
or changes in the information provided by the balance sheet), this suggests the decline in their
use is costly. If the decline is due to changing preferences in contracting (i.e. a shift in the
preferred mix of contract provisions), this suggests the average amount that borrowers are
willing to pay to avoid having a balance sheet covenant. For maturity, loans from the High Risk
group have maturities that are 7.4 months, or about 15%, shorter when balance sheet covenants
are dropped. Though the cost is more difficult to quantify, this similarly suggests borrowers are
either forced into more frequent loan renegotiation (with all the attendant risks and costs) or are
willing to renegotiate more frequently to avoid being checked by covenants.
This research sheds light on the overall design of loan contracts by showing how the
different terms interact. I find, consistent with Christensen and Nikolaev (2010), that balance
sheet and income statement covenants are not substitutes but likely serve distinct purposes in
3
debt contracts. I also find that balance sheet covenants and loan maturity are substitutes. This is
consistent with the covenants providing control rights to lenders in technical default, thus
allowing borrowers longer loans when performance is sufficiently good. Finally, consistent with
Bradley and Roberts (2004), I find that balance sheet covenants are priced in loan contracts.
In the next section I present the background and develop hypotheses. Data and research
design are presented in Section 3. Principal empirical results are presented in Section 4, with
supplementary test results in Section 5. I conclude in Section 6.
2
Background and Hypothesis Development
2.1
The Balance Sheet in Debt Contracting
The balance sheet plays an important role in debt contracting; collateral values are
derived from balance sheet values, covenants are written on balance sheet values, and other
measures are calculated at least in part from GAAP-reported balance sheet figures (e.g.
regulatory capital (Beatty et al. 1995)). Holthausen and Watts (2001) discuss how the balance
sheet measures the liquidation value of the borrower. Similarly, Watts (2003) argues that the
balance sheet must provide a “verifiable lower bound” of asset values to be useful for
contracting. Kothari et al. (2010) discuss how certain features of US GAAP, particularly
asymmetric verifiability requirements and conditional conservatism, have evolved to keep
accounting useful for contracting. Several recent studies have examined the specific role of
balance sheet data in debt contracts. Demerjian (2010b) finds that poorly performing firms that
are closer to liquidation are more likely to have net worth covenants. Christensen and Nikolaev
(2010) find that balance sheet covenants (which they term “capital covenants”) are in place to
protect lenders by requiring firms to maintain a minimum level of value.
4
I define balance sheet covenants as those measured exclusively with balance sheet values,
a group that includes net worth, leverage (debt-to-assets or debt-to-equity), and current ratio. I do
not include the debt-to-cash flow (generally measured as the ratio of debt to EBITDA) since its
measurement is partially from the income statement. Demerjian (2010a) notes that the use of
balance sheet covenants has declined sharply in recent years, being used in 80% of private loans
in 1996 to just 30% by 2007. This trend is illustrated in Figure 1.
2.2
Firm-Level and Covenant-Level Demand
The decline in use of balance sheet covenants can be explained by changes in two distinct
but related types of demand. The first, which I term “firm-level demand”, is the demand for
protection by the creditor based on the general risk that the borrower presents in contracting. By
this definition, firm-level demand can be measured as the default risk of the borrower: creditors
of borrowers with high levels of default risk will demand more protection, while low levels of
default risk will be rewarded with a lower demand for protection. Under high firm-level demand,
the lender will require tighter contract provisions (e.g. high interest rates, short maturities,
restrictive provisions); if the default risk of the borrower improves, loan provisions will be
loosened commensurately. Much of the theory on covenant use (as well as other contract
provisions) focuses implicitly on firm-level demand. The Agency Theory of Covenants,
proposed in Bradley and Roberts (2004), follows Smith and Warner (1979) in linking the use of
covenants to moral hazard problems. The Signaling Theory of Covenants, discussed in
Demiroglu and James (2010), examines how borrowers signal their quality to the debt market by
agreeing to have covenants. Each of these theories, and subsequent empirical tests, takes a broad
5
view of the role of covenants in contracts: a lender faces certain information problems with a
borrower (either moral hazard or adverse selection) and uses covenants to address the problems.2
Firm-level demand for covenants is not the only driver of covenant demand. The second,
which I term “covenant-level demand”, is the demand for a specific covenant (rather than other
provisions); in this study, I focus on the covenant-level demand for balance sheet covenants.3
There are a number of reasons why the demand specific to balance sheet covenants may decline.
If the underlying economics of borrowers shift, this may cause balance sheet information to be
less useful in contracting. For example, if a firm starts investing more in R&D and other
unreported intangible assets, the balance sheet will provide relatively less information about the
firm’s true value (Skinner 1993). Or, balance sheet information may become less useful for
contracting; Demerjian (2010a) examines whether fair value accounting has diminished the
contracting value of balance sheet information. There may also be structural changes in the debt
market that leads to changes in demand for balance sheet covenants. For example, Drucker and
Puri (2009) document the association between net worth covenants and loan sales on the
secondary market. Finally, borrowers may prefer other provisions rather than balance sheet
covenants. They may be willing to pay (e.g. have a higher interest rate or shorter maturity loans)
to remove the financial covenant and enjoy greater flexibility in operating and financing
decisions.4
Firm-level and covenant-level demand are not mutually exclusive. In fact, since balance
sheet covenants make up part of the set of protective provisions of the debt contract, declines in
2
For example, Billett et al. (2007) examine how growth opportunities, a proxy for general agency problems, affect
maturity and debt covenant intensity in bond contracting.
3
Covenant-level demand is more aptly referred to as “individual provision-level demand”; this refers to the case
where one provision is preferred over another for some reason other than the overall risk of the borrower. I refer to
this as “covenant-level” in this study due to my focus on balance sheet covenant use.
4
Beatty et al. (2002), examining how changes in GAAP are incorporated into debt contracts, find that borrowers are
willing to pay higher interest spreads to maintain reporting flexibility.
6
firm-level demand can manifest as declines in demand for balance sheet covenants. The critical
distinction is that covenant-level demand can change even when firm-level demand for
protection remains constant. By this definition, changes in covenant level-demand can occur
independent of changes in firm-level demand. That is, covenant-level demand can decrease even
when firm-level demand for protection has not changed or has increased.
This distinction is important, because the driver of the decline in balance sheet covenant
use (firm-level versus covenant-level) affects the consequences. Consider a borrower with
improved operating performance, leading to lower default risk and a decline in firm-level
demand for protection. If removing a balance sheet covenant exactly offsets the decrease in firmlevel demand (i.e. that level of protection that the balance sheet covenant provided is equal to the
decline in protection required by the creditor), the other provisions of the loan contract should
not change.5 If removing a balance sheet covenant either over- or under-compensates the
borrower for decreased risk, other provisions will be changed to balance the aggregate protection
provided by the loan contract with the borrower’s risk. Since the level of protection that a
balance sheet covenant provides varies from borrower to borrower, I do not anticipate a
systematic tightening or loosening of other contract provisions in response to dropping a
covenant due to a decline in firm-level demand.
In contrast, a decline in covenant-specific demand can occur when firm-level demand has
not changed. Consider a borrower whose overall default risk is constant but where the demand
for balance sheet covenants has decreased to the point where a covenant is not used in a new loan
contract. With the covenant excluded, the aggregate protection has declined; however, the
demand for protection has not changed, meaning the remaining provisions are insufficient based
5
More precisely, the aggregate level of protection provided by the other loan provisions (e.g. maturity, interest rate,
collateral requirements, restrictive covenants) will not change. It is possible, due to macroeconomic or other changes
that the efficient mix of other provisions will change, though the aggregate protection will be the same.
7
on the creditor’s demand for protection. As such, another provision or provisions will be
tightened to compensate for the dropped covenant. For example, the creditor may require a
higher interest rate or add restrictive covenants. Hence, a covenant-specific decline in demand
must be accompanied by tightening in other loan provisions, holding firm-level demand constant.
The extent of the tightening will be a function of both how much protection the dropped
covenant had provided as well as any change in firm-level demand.
To summarize, the decline in use of balance sheet covenants can be attributed to two
broad reasons: a decline in firm-level demand or a decline in covenant-level demand. I expect
any systematic effect of declining balance sheet covenant inclusion to be driven by changes in
covenant-level (but not firm-level) demand. That is, I anticipate a systematic tightening of loan
provisions when a balance sheet covenant is dropped due to covenant-level demand, but no
changes when the drop is related to firm-level demand.
2.3
Hypotheses
There are a variety of debt contract provisions that serve to either limit the risk of the
creditor entering a risky lending agreement or compensate the creditor for bearing risk. If the
decline in balance sheet covenant use has affected the protection provided to the creditor in the
debt contract, I expect to see this manifested in the structure of the loan contract. In this section, I
describe four provisions—interest spread, maturity, income statement covenants, and general
covenants—that either limit or compensate for risk, and present hypotheses on how these
provisions may be affected by declining balance sheet covenant protection.
The first provision is interest spread, or the pricing of the loan. Following the standard
risk-return relation, if removing a balance sheet covenant reduces the aggregate protection in the
8
loan contract, the creditor may require more interest as compensation. There is considerable
evidence that inclusion of provisions that reduce risk and agency problems are priced in debt
contracts. Examples include performance pricing (Asquith et al. 2005), collateral (Chan and
Kanatas 1985, Stulz and Johnson 1985), and restrictive covenants (Reisel 2006, Chava et al.
2010). Bradley and Roberts (2004) show that a variety of covenants, including financial
covenants, are priced. This evidence suggests that a decline in covenant protection, holding other
things equal, may result in a higher interest spread.
H1: The decline in balance sheet covenant inclusion is associated with higher
interest spreads on loans.
The second provision that could be affected is loan maturity. Barclay and Smith (1995)
and Childs et al. (2005) find that the maturity structure of debt is linked to agency problems. To
the extent that balance sheet covenants limit agency issues, their exclusion may induce a shorter
debt maturity. More directly, technical default serves as a trigger for renegotiation of private
loans. Dichev and Skinner (2002) find that covenants serve as “trip wires”, allowing the creditor
the option of action (including the shortening of maturity) when a covenant is violated.
Exclusion of covenants may therefore encourage the creditor to offer shorter maturity loans,
since he loses the ability to renegotiate in technical default: a loan with a long maturity and a
financial covenant is de facto a shorter-term loan conditioned on borrower performance. It
follows that the fewer covenants should result in shorter loan maturities:
H2: The decline in balance sheet covenant inclusion is associated with shorter
maturity loans.
Another possible substitute for balance sheet covenants are income statement covenants.
These covenants—including interest coverage, fixed charge coverage, and debt-to-earnings
ratio—function similarly to balance sheet covenants. That is, the borrower must maintain a
9
threshold, and the loan enters technical default if the threshold is not maintained. It is not clear
that covenants written on these different financial statements will readily serve as substitutes:
Christensen and Nikolaev (2010) shows that income statement and balance sheet covenants
provide different information in contracting and are used by different borrowers. This is
consistent with Kothari et al. (2010), who note that the income statement captures short-term
performance while the balance sheet captures the liquidation value of assets. However, some
studies examining covenant use have found a single set of drivers for use of all financial
covenants, suggesting the possibility they are substitutes (Bradley and Roberts 2004). Given the
ambiguity of the existing evidence, I consider income statement covenants as substitutes for
balance sheet covenants:
H3: The decline in balance sheet covenant inclusion is associated with an increase
in income statement covenant inclusion.
Finally, balance sheet covenants and restrictive covenants may be substitutes. Restrictive,
or negative, covenants directly limit actions that can transfer wealth from the borrower to the
creditor. For example, Smith and Warner (1979) show that covenants may restrict dividend
payments (to limit underinvestment) or debt issuance (to limit claim dilution). The moral hazard
problems addressed with restrictive covenants can also be limited with balance sheet covenants.
Following the example above, net worth covenants can limit dividend payments, and leverage
covenants restrict the amount of new debt a borrower can assume. While there is little theory on
the decision to use a restrictive covenant versus a financial covenant—it is likely that financial
covenants allow more flexibility, but with a greater risk of measurement error—it is possible
they serve as substitutes, particularly if balance sheet information is losing its contracting
usefulness (Demerjian 2010a). This leads to the final prediction:
10
H4: The decline in balance sheet covenant inclusion is associated with an increase
in restrictive covenant inclusion.
3
Sample and Research Design
3.1
Sample
Private loan data is drawn from the LPC/Dealscan database. This database provides
detailed data on loans, including interest rates, loan size, and maturity. Additionally, data on a
variety of contract provisions, including covenants, is provided. The loans in this sample are
drawn from 1996 (when Dealscan begins comprehensive coverage of the private debt market) to
2007. Accounting data is drawn from the quarterly Compustat Xpressfeed. Dealscan lacks
common firm descriptors (e.g. cusip or gvkey) so observations are matched to Compustat by
name and hand-checked to verify accuracy. Loans are matched to the accounting quarter most
closely preceding the loan’s initiation date. All flow variables from Compustat (i.e. from the
income statement or statement of cash flows) are annualized using the sum of the current and
prior three quarters. Dealscan data is organized on two levels, facilities and packages. Facilities
are individual loans, while loan packages are groups of facilities from the same lender. All the
facilities in a loan package have the same set of covenants, so my unit of analysis is the
package.6
The sample selection consists of four steps:
1. I first identify borrowers with at least two loan packages over the sample period.
2. Of these multi-deal borrowers, I find those that, at some point in the sample period, have
at least one balance sheet covenant.
6
I use the terms “loan package” and “deal” interchangeably.
11
3. Of those with a balance sheet covenant, I identify those borrowers who have a subsequent
loan package with no balance sheet covenants; that is, I identify borrowers that had
balance sheet covenants “dropped” from one deal to the next.
4. I remove borrowers with multiple drops; that is, borrowers who have a balance sheet
covenant dropped and in a subsequent package have a balance sheet covenant again.7
For the sample, I retain the first package from a borrower where there was no balance
sheet covenant (the Drop deals) and the package with a balance sheet covenant immediately
preceding the Drop (the Pre-Drop deals). Sample selection is summarized in Table 1. The
intersection of the Dealscan population with Compustat data consists of 9,000 deals from 3,087
individual borrowers; the sample selection yields 1,458 deals from 729 individual borrowers.
Table 2 presents the distribution of sample observations by year. By design, each firm has
a pair of observations, one in the Pre-Drop period and one in the Drop period. The mean
(median) amount of time between the Pre-Drop and Drop deal is 2.7 (2.3) years. This is
illustrated in the table, with the Pre-Drop deals more concentrated earlier in the sample period
and Drop deals more likely later.
3.2
Research Design
I start by defining DROP as an indicator with a value of one when a deal does not have a
balance sheet covenant (net worth, leverage, or current ratio) and zero when it does. Based on the
sample selection criteria, each borrower will have two observations in the sample: the earlier will
have a value of zero for Drop, and the later will have a value of one.
7
The observations dropped in this step include 44 borrowers with two drops, five borrowers with three drops, and
one borrower with four drops, for a total of 214 observations. Including these observations does not affect the
inferences from the empirical tests.
12
I then examine the association between Drop and four variables related to debt contract
structure. INTEREST SPREAD is the amount over an index rate of interest (generally LIBOR or
Prime) that the borrower is charged for the loan. Higher interest spreads imply higher risk, so I
expect a positive association between Drop and Interest Spread. MATURITY is the term of the
loan from inception to the stated maturity date, measured in months. Long-term loans are
generally considered riskier than shorter loans, so I predict a negative association between Drop
and Maturity. IS COVENANT is an indicator variable with a value of one if the borrower has at
least one income statement covenant (interest coverage, fixed charge coverage, debt-to-earnings)
and zero otherwise. GENERAL COVENANT is an index of indicator variables related to direct
restrictions on borrower actions. There are five restrictions in the index: asset sales, dividends,
debt issuance, equity issuance, and insurance proceeds sweeps. If either income statement or
general covenants serve to substitute for balance sheet covenants, there will be a positive
association between Drop and both IS Covenant and General Covenant.
As discussed in Section 2.2, the nature of the decline in balance sheet covenant use (firmlevel demand versus covenant-level demand) has important implications for the predictions;
specifically, I expect the hypothesized results to hold only for covenant-level decreases in
demand. As such, I control for the nature of the decline in the research design. Directly
measuring changes in covenant-level demand is difficult. It can be affected by a number of
things, including changes in the underlying economics of borrowers and the move to balance
sheet accounting (Christensen and Nikolaev 2010; Demerjian 2010a). Measuring a change in
firm-level demand is relatively easier. As a proxy for firm-level demand, I use the expected
default risk (EDF), based on Merton (1974), which incorporates leverage and the volatility of
borrower asset value in an options-style model. Exploiting the structure of the sample, I measure
13
the change in EDF from the Pre-Drop to the Drop period on a borrower-specific basis. If the
default risk declines from the Pre-Drop to the Drop period, I attribute the dropped covenant to
lower firm-level demand.8 If default risk increases from the Pre-Drop to the Drop period, I
expect the covenant was dropped due to a covenant-level factor. I define HIGH RISK as an
indicator with a value of one if EDF increases from the Pre-Drop to the Drop period, and a value
of zero otherwise.
Using Drop and High Risk, I employ a difference-in-difference design in the main
empirical tests. These regression-based tests have the structure:
, Γ
! "
Loan Parameters include Interest Spread, Maturity, IS Covenant, and General Covenant. The
coefficient of interest in each regression is : this captures the association of the loan parameter
with dropping the balance sheet covenant when the firm-level demand for protection is high. I
predict a positive coefficient on when the Loan Parameter is Interest Spread, Is Covenant, or
General Covenant, and a negative coefficient when it is Maturity.
The tests include a variety of controls associated with the different loan parameters,
including borrower and loan characteristics. Borrower characteristics include FIRM SIZE (the
natural logarithm of total assets), ROA (EBITDA scaled by average total assets), LEVERAGE
(total long-term debt scaled by total assets), RATED (an indicator if the borrower has an S&P
Senior Debt Rating), ASSET MATURITY (the age of assets), and ASSET TANGIBILITY (the
relative amount of tangible to intangible assets). Loan characteristics include LOAN SIZE (the
natural logarithm of the loan amount), REVOLVER (an indicator if the loan package has a
8
A decline in firm-level demand can coincide with a decline in covenant-level demand. My assumption is that firmlevel changes dominate the effects of covenant-level changes; in other words, I expect that contracts are designed
with aggregate demand for protection having first-order importance, and the specific mix of provisions having
second-order importance.
14
revolving line of credit), INSTITUTIONAL TRANCHE (an indicator if the loan has a Term
Loan B tranche or higher), PERFORMANCE PRICING (an indicator if the loan has a
performance pricing provision), LENDERS (the number of lenders in the loan syndicate), and
COLLATERAL (an indicator if the loan requires collateral). I provide detailed variable
definitions in the Appendix.
Summary statistics on the test and control variables are presented in Table 3, and simple
correlations are shown in Table 4. Table 5 presents differences in test and control variables based
on the period of the observation. The Drop column presents the mean and median level of the
variables for sample observations without balance sheet covenants, while the Pre-Drop column
presents similar statistics for observations preceding the drop. The next two columns present the
difference and the p-value of a test of significance (t-test for means, Wilcoxon signed-rank test
for medians). This descriptive evidence shows that Interest Spread is significantly higher in the
Drop period (mean 27.643, median 42.5), consistent with prediction. However, Maturities after
the drop are longer (mean 5.241, median 12), and both IS Covenants (mean -0.114) and General
Covenants (mean -0.221) are lower in the Drop period, inconsistent with prediction. Though
descriptive, this data indicates it is important to control for the driver of the decline in covenant
protection. The data also shows, though Drop and Pre-Drop observations are matched by
borrower, there are many significant differences in the control variables. This suggests that
features of the borrowers and their loans are changing over time, and must be controlled in the
tests to make clear inferences.
4
Empirical Results
4.1
Univariate Results
15
The analysis begins with univariate difference-in-differences tests on the four loan
parameters. The results are shown in Table 6. The first set of columns, titled “High Risk”,
presents data for the 282 pairs of observations (i.e. 282 Pre-Drop observations and 282 Drop
observations) where EDF increased (High Risk = 1). Within this High Risk group, I further sort
the firms between the Drop and Pre-Drop periods, and measure the mean values of the loan
parameters. The second set of columns presents similar statistics for the 385 “Low Risk”
observation-pairs (High Risk = 0). The first parameter tested, in the top rows, is Interest Spread.
For High Risk borrowers, the average Interest Spread in the Drop period is 237.478, significantly
higher than the Pre-Drop average of 168.229 (difference 69.249, t-statistic 5.73). In contrast, the
average difference in the Low Risk observations (-5.49, t-statistic -0.65) is not significantly
different from zero. The far right hand columns present the difference-in-differences; in this
case, a significant figure of 74.739 basis points (t-statistic 5.06). By contrasting the High Risk
and Low Risk settings, this test captures general trends in Interest Spread; essentially, the Low
Risk observations serve as a benchmark to evaluate the High Risk. The results support H1:
borrowers that have a balance sheet covenant dropped when there is high firm-level demand for
covenant protection have significantly higher interest spreads than when demand is low.
The send parameter tested is Maturity. For the High Risk firms, the difference between
the Drop and Pre-Drop average maturity is close to zero (-0.989, t-statistic -0.61), suggesting that
dropping a balance sheet covenant is associated with less than a one month decline in loan
maturity. In contrast, there is a significant increase of almost ten months in maturity when the
balance sheet covenant is dropped in the Low Risk setting (9.919, t-statistic 7.41).9 The
difference between the two groups is -10.908, suggesting that borrowers with high firm-level risk
9
The results for Interest Spread and Maturity for the Low Risk group are consistent with an average improvement in
borrower quality; even with the removal of balance sheet covenants, loans are significantly longer while interest
spreads are constant.
16
that drop a balance sheet covenants have loans almost one year shorter those who drop in the low
risk setting. This is consistent with H2.
The results in the next section show a significant decline in income statement covenants
for both High and Low Risk firms. The difference-in-differences shows a difference between the
groups of -8%, which is mildly significant (t-statistic -1.72) but with the opposite of predicted
sign. Similarly, General Covenants decline for all firms, though the decline is larger (though not
significantly so) for High Risk firms. In total, the univariate results support H1 and H2, but do
not support H3 and H4.
4.2
Multivariate Tests
In this section I expand the analysis to include control variables associated with Interest
Spread, Maturity, IS Covenants, and General Covenants. In each test, the variable of interest is
the interaction between Drop and High Risk. Each regression includes control variables related
to the dependent variable. The regressions also include control for industry fixed effects, and
standard errors are clustered at the firm level. Results are presented in Table 7.
The first column shows results for Interest Spread. Since Interest Spread is a continuous
variable, I use ordinary least squares regression. Neither the coefficient on Drop nor High Risk is
significantly different from zero. The coefficient on the interaction is positive as predicted and
significant: this suggests that loans dropping a balance sheet covenant in a period of increased
firm-level demand have, on average, interest spreads 35.3 basis points higher than when the drop
is in a period of decreased firm-level demand. This result is consistent with the univariate test,
which showed a difference of 74.7 basis points between groups; the attenuation in the size of the
coefficient can be attributed to the inclusion of control variables. The control variables show that
17
large firms and firms with higher earnings have lower interest spreads, while borrowers with
higher leverage have higher interest spreads.
The second column presents similar results for Maturity. As with Interest Spread, I use
OLS regression.10 In this case, both the Drop and High Risk have positive and significant
coefficients. However, the coefficient on the interaction term is negative and significant,
suggesting that dropping a balance sheet covenant when demand is high results in loans
approximately 7.4 months shorter than it would be with low firm-level demand.
The dependent variable in the third column is a dichotomous variable for use of an
income statement covenant, so I use probit regression. The results, consistent with the univariate
tests, provide little evidence of income statement covenants substituting for a dropped balance
sheet covenant. Specifically, the coefficient on the interaction term is negative but
insignificant.11 The fourth column shows regression results for the General Covenant index.
Since this variable features a count index of restrictive provisions, I use a negative binomial
regression. The results on the interaction are, consistent with the univariate analysis, not
significantly different from zero. In total the results support the findings in Table 6: dropping a
balance sheet covenant in a period of increasing firm-level demand is associated with higher
interest spreads and shorter maturities, but is uncorrelated with use of other types of covenants.
4.3
Economic Impact on Borrowers
10
Maturity is a continuous variable. However, the observed distribution is censored, as maturity cannot be negative:
it is not sensible in this context that a loan would mature before it was issued. To examine whether this censoring
will impact the inferences from using OLS, I do two things. First, I examine the fitted values of maturity following
the OLS regression. I find that only one observation’s predicted value (of 1,248 observations) is negative, suggesting
that imposing a lower bound would make only a small difference. Second, I rerun the regression using the tobit
model. The results and interpretation are substantively identical. Hence, for ease of discussion and interpretation, I
report the OLS regression results in Table 7.
11
As an additional check, I use the Ai and Norton (2003) adjustment to measure the coefficient and z-statistic. The
result (-0.012, z-statistic -0.33) yields similar inferences as those reported in Table 7.
18
The regression results suggest two changes to the debt contract when a balance sheet
covenant is dropped despite high firm-level demand. First, the average interest spread is 35.3
basis points higher. Second, loans are on average 7.4 months shorter. In this section I evaluate
the economic significance of these results for the subsample of affected borrowers.
The 282 loans where a balance sheet covenant was dropped in a period of increased firmlevel demand have an average size of $636M. Hence, the interest spread results imply (holding
other things equal), an increase in interest expense of $2.25M ($636*0.00353). The average
interest expense and net income before discontinued operations and extraordinary items for these
firms are $63.4M and $41.1M; the economic impact of the increased interest spread is 3.5% and
5.4% of these figures respectively. If balance sheet covenants are being removed from contracts
due to their lack of effectiveness (i.e. either due to changes in borrowers that make the balance
sheet less informative for that firm, or changes in accounting standards that make the balance
sheet less informative in general), this amount is the real cost borne by equity holders of the
borrower. If the borrowers are choosing not to have balance sheet covenants, (i.e. to avoid
restrictions on their actions and maintain flexibility, as in Beatty et al. (2002)), this places an
approximate price on this flexibility.
The impact of decreased maturity is more difficult to quantify. The average maturity for
borrowers that dropped a balance sheet covenant with high firm-level demand is 41.8 months.
The regression coefficient of -7.4 suggests loans would have maturities of 49.2 months with a
balance sheet covenant, holding other things equal. Shorter loans require more frequent
renegotiation. The difference in average maturities between the two groups implies that the firms
with the shorter loans must get new loans 3.7% more frequently (on an annual basis) than the
19
group with longer loans.12 As such, these borrowers will incur the associated fixed loan fees
(upfront fees) with similarly greater frequency. The average upfront fee for these firms, based on
data from Dealscan, is 64 basis points. The 3.7% more frequent renegotiation rate implies the
short-maturity borrowers will incur additional upfront fees once every 27 years (1 / 0.037 = 27).
Dividing 64 basis points by 27 years, shorter maturities lead to an annual cost in added upfront
fees of 2.4 basis points, or about $153,000 per year. Given the size of the borrowers and the
loans, this amount is not economically significant.
However, there are other costs to short maturities that likely do impose real costs on the
borrower. Diamond (1991, 1993) and Childs et al. (2005) argue that more frequent renegotiation
of debt exposes the borrower to liquidity risk: for example, the lender may decide not to extend
further credit to the borrower. Beneish and Press (1993) show that borrowers subject to technical
default receive more stringent loan terms in renegotiated loans. In either case, shorter maturities
allow the creditor the option to limit their own risk, hence transferring risk to the borrower.
While the costs are difficult to quantify, there is considerable research to suggest they are
economically meaningful.
5
Additional Tests
5.1
Instrumental Variables Estimation
It is commonly held that loan interest spread and maturity are jointly determined
(Wittenberg-Moerman 2009). Consistent with this, I find a negative relation between Maturity
12
Loans without a balance sheet covenant have a maturity of 41.8 months, while those with the covenant have 49.2
months. This means loans without balance sheet covenants are about 15% shorter (1 – (41.8 / 49.2)), so
renegotiation would take place 15% sooner for loans without covenants. Since the average loan is 4.1 years long,
renegotiation is 3.7% more frequent (15% / 4.1 years) on an annual basis.
20
and Interest Spread in the first two regressions in Table 7. To address the potential simultaneity
in determination of Interest Spread and Maturity, I use instrumental variable regressions.
I start by selecting instruments; these should be associated with the endogenous variable
they are serving as instruments for, but uncorrelated with the error term in the underlying
structural equation. In the Interest Spread regression, I instrument Maturity using eight variables.
I start with two variables used in the main Maturity regression (Asset Maturity and Asset
Tangibility) that are related to the asset structure of the borrower. I add another along similar
lines, CAPITAL EXPENDITURES, which captures the borrower’s rate of replenishing their
fixed assets. I add three indicator variables related to the stated loan purpose:
RESTRUCTURING, WORKING CAPITAL and CORPORATE PURPOSES. The purpose of
the loan may dictate the timing of its maturity (for example, based on the expect duration of
restructuring, or the operating cycle of the firm), but there is no reason to expect the purpose
should affect price terms. Finally, I add two instruments related to the growth opportunities of
the borrower: MARKET-TO-BOOK and R&D INTENSITY. Market-to-book ratio is a general
measure of investment opportunities, while R&D Intensity specifically captures innovations of
the firm. I expect borrowers with high levels of either of these variables will have shorter loans;
the creditor will require a shorter maturity as a means to monitor the status of these harder-tovalue (relative to fixed assets) opportunities. Following Wittenberg-Moerman (2009), I use
EBITDA and Leverage to instrument Interest Spread in the Maturity regressions.
I use two-stage least squares (2SLS) to estimate the Interest Spread and Maturity
regressions separately. Though potentially less efficient than other methods (e.g. three-stage least
squares) that utilize more information by jointly estimating the equations, 2SLS only requires
21
that the instruments be exogenous for the specific equation in which they are used.13 Regression
results are presented in Table 8. The first two columns present the 1st and 2nd stage results for
Interest Spread. The first stage reports coefficients of all exogenous variables (including all
instruments) regressed on the endogenous variable (in this case, Maturity). I run a series of
specification tests on the first stage results. First, since the equation is overidentified (there are
more instruments than endogenous variables), I calculate the Sargan-Basmann χ2 to confirm the
instruments are conditionally exogenous. The statistic has a p-value of 0.3072, so the null
hypothesis that the instruments are exogenous cannot be rejected. I next calculate the DurbinWu-Hausman statistic to determine if Maturity is in fact endogenous with Interest Spread. This
statistic, which has an F-distribution, has a p-value of 0.0918, consistent with the variables being
endogenous. Finally, I examine the strength of the instruments using the Partial R2 and Partial FStatistic of the instruments. The Partial R2 is 3.6%, and the F-Statistic is statistically significant
(p-value 0.0003). However, as noted in Larcker and Rusticus (2010), an F-statistic at this level
suggests that the instruments may be weak.14
The 2nd stage results are shown in the second column. The coefficients on the main
variables are similar to the OLS results: Drop is insignificant, High Risk is negative and weakly
significant, and the interaction is positive and significant. The coefficient is higher in this
regression, 46.220 versus 35.296. The control variables have similar signs and magnitudes as the
OLS coefficients. Notably, the coefficient on Maturity is positive (opposite of OLS) and not
significantly different from zero. This is not surprising for two reasons. First, the test of
endogeneity is only weakly significant, suggesting that 2SLS represents only a small
13
Three-stage least squares requires the instruments to be exogenous in all the equations that are being jointly
estimated (Larcker and Rusticus 2010).
14
Stock et al. (2002), suggests a minimum F-value of 15.09 when using five instruments. With a Partial F-Statistic
of 3.762 and eight instruments, these instruments jointly fall below the indicated threshold.
22
improvement over OLS. Second, as noted above, the instruments for Maturity are potentially
weak. Hence, the results of this 2SLS regression must be interpreted with caution.
The second two columns present results for Maturity. As before, 1st and 2nd stage results
and specification tests are presented. The test of overidentifying conditions again fails to reject
null, indicating the two instruments are exogenous to Maturity. The Durbin-Wu-Hausman Test
rejects the null of no endogeneity. Finally, the instruments appear to be strong: the Partial R2 is
0.169, and the Partial F-Statistic of 68.395 is above the threshold set in Stock et al. (2002). This
suggests the results in the 2nd stage are efficient, and represent a significant improvement over
OLS. In those results, the coefficient on the interaction term is -6.609; this is lower than the OLS
coefficient in absolute terms, but still statistically significant. The signs and magnitudes of other
variables are similar between 2SLS and OLS, including Interest Spread. In total, the 2SLS results
do not contradict the OLS results.
5.2
Endogenous DROP
The previous tests treat Drop as a strictly exogenous variable. This may be true, at least in
part; Demerjian (2010a) examines how changing accounting standards, which are arguably
exogenous to either borrower or loan features, have affected the inclusion of balance sheet
covenants. More likely, though, is that the decision to drop a balance sheet covenant will have
some determinants in common with other loan parameters. In this section, I examine the impact
on Interest Spread and Maturity when Drop is not exogenous.
I start by modeling the determinants of the decision to Drop. While I expect this variable
to share determinants with both Interest Spread and Maturity, I do not model these as being
simultaneously determined; specifically, Drop should impact Interest Spread and Maturity, but
23
Interest Spread and Maturity do not determine Drop. Since Drop is a dichotomous variable, I use
a probit regression with determinants from the Interest Spread and Maturity regressions. I add
three other controls likely related to inclusion of balance sheet covenants. COLLATERAL is an
indicator with a value of one if the loan is secured. Since Net Worth covenants measure the value
of the borrower in the event of liquidation, these may be complementary with collateral
requirements. I also include EDF and CHANGE IN EDF. Balance sheet covenants are generally
used by riskier, poorer performing firms, so measures of financial distress may predict their
inclusion. I also include control variables for year and industry.
Probit regression results for the selection equation are presented in the first column of
Table 9. The regression yields a fitted value for Drop between zero and one. I code fitted values
with a breakpoint of 0.5: observations less than one-half receive a value of zero for PREDICTED
DROP, and fitted values of one-half or more receive a value of one. The model accurately
classifies 73.4% of the observations. I then use Predicted Drop (both on its own and interacted
with High Risk) in the 2SLS regressions. I do not report first stage results and specification tests,
which are substantively similar to those reported in Table 8. The results are consistent when
using Predicted Drop rather than Drop. The coefficient on the interaction in the Interest Spread
regression is positive and significant, suggesting borrowers with high covenant demand who
drop the a balance sheet covenant (based on the prediction model) have an interest spread 51.3
basis points higher. Similarly, the maturity is 5.9 months shorter absent a balance sheet covenant.
5.3
Other Sensitivity Tests
24
I run a variety of additional specifications of the main OLS regressions. Summary results
(coefficients and t-statistics for the Interest Spread and Maturity regressions) are shown in Table
10, with each test described below.
Ranking HIGH RISK
In the main tests, the High Risk is defined as a dichotomous variable, with an increase in
EDF indicating high firm-level demand for covenants and a decrease indicating low. This
approach assumes a constant effect regardless of the size of the change; i.e. creditors will
respond equally to a small increase in default risk as to a larger increase. To allow for variation
in effects for different size changes, I sort observations into quartiles based on the Change in
EDF. I then interact an indicator for each quartile with Drop. I expect to see coefficients
increasing (in absolute terms) across the quartiles.
Summary results for this piece-wise regression are presented in Table 10, Panel A. The
first (most negative) quartile serves as the reference category, so I report coefficients and tstatistics for the second through fourth interaction terms. In the Interest Spread results, the
coefficients increase monotonically, being negative in the 2nd quartile, close to zero in the 3rd,
and positive in the 4th. The difference between the 2nd and 4th quartile coefficients is statistically
significant (based on a Chow Test, reported in the last column). In the Maturity results, the same
monotonic pattern holds, with a near-zero change in the 2nd quartile and significant negative
decreases in the 3rd and 4th. As with Interest Spread, a test of equality of the 2nd and 4th quartile
coefficients shows a significant difference. These results support the main findings using the
dichotomous measurement of High Risk.
25
Specific Covenants
The main tests group all balance sheet covenants together. To assure the results are not
due to one specific covenant, I run the main OLS regressions using only those cases where a
specific covenant was dropped. The first three columns in Table 10, Panel B, show summary
regression results where borrowers dropped a Net Worth (NW), Leverage (LEV) and Current
Ratio (CR) covenant respectively. For Net Worth and Leverage, the coefficients are significant
and in the predicted direction, consistent with the main findings. For Current Ratio, the
magnitude of the coefficients is similar as for other covenants, but only significant in the
Maturity regression. This is likely due to low statistical power, as only about 200 observations
involve the current ratio.
Rating
It common to include the borrower’s Debt Rating as an explanatory variable in
regressions of loan parameters. In the main sample, only 42% of the observations have an S&P
rating. As a robustness check, I rerun the main regressions sorting observations based on rated
status. Summary results, shown in Table 10, Panel B, suggest that the predicted effects are
stronger in the unrated subsample than in the rated subsample; however, a Chow test
(untabulated) indicates no statistical difference between either of the pairs of coefficients.
6
Conclusion
I examine the impact of the sharp decline in use of balance sheet covenants over the
period 1996 to 2007. Focusing on borrowers where a balance sheet covenant was dropped even
though firm-level demand for contractual protection was high, I find the loss of covenant
26
protection is costly. Specifically, the average firm has an interest spread 35.3 basis points higher
and a maturity 7.4 months shorter. I do not find any association between this drop and the use of
income statement covenants or restrictive covenants, suggesting these different provisions serve
distinct needs. The increase in interest spread costs the average sample borrower $2.25M in
additional interest each year, or 5.4% of net income before discontinued operations and
extraordinary items.
There are a number of forces that lead to lower use of balance sheet covenants even when
firm-level demand for covenants is high. These include shifts in the underlying economics of
borrowers, shifts in the contracting usefulness of balance sheet information, and changes in the
preferences of borrowers for reporting and operating flexibility. While the current study focuses
generally on the effects of reduced covenant protection, it does not attempt to distinguish
between these different motivations. To the extent that the implications on contract design differ
based on these drivers, this is potentially a valuable avenue for future research.
27
Appendix
Variable Definitions
Variable Name
Test Variables
Drop
Interest Spread
Maturity
IS Covenant
General Covenant
High Risk
Predicted Drop
Borrower Characteristics
Firm Size
ROA
Leverage
Rated
Asset Maturity
Asset Tangibility
EDF
Change in EDF
Capital Expenditures
Market-to-Book
R&D Intensity
Loan Characteristics
Loan Size
Revolver
Institutional Tranche
Definition
Indicator with a value of one if deal has at least
one balance sheet covenant (Net Worth,
Leverage, or Current Ratio)
All-In Drawn Loan Spread
Loan Maturity Date – Loan Inception Date (in
months)
Indicator with a value of one if the deal has an
income statement covenant (Interest Coverage,
Fixed Charge Coverage, Debt-to-Earnings)
An index with a value of one for restrictions on:
dividend payment, asset sales, debt issuance,
equity issuance, and use of insurance proceeds
An indicator with a value of one if EDF
increased from the Pre-Drop to Drop period
Based on the fitted value from a regression of
Drop on a set of controls; an indicator with a
value of one if the fitted value is greater than or
equal to 0.5, and zero if the fitted value is less
than 0.5
Source
Dealscan
Dealscan
Dealscan
Dealscan
Dealscan
Dealscan / Compustat /
CRSP
Dealscan / Compustat /
CRSP
The natural logarithm of total assets: ln(ATQ)
EBITDA scaled by average total assets:
OIBDPQ / ATQ
Total debt scaled by total asset:
(DLCQ+DLTTQ) / ATQ
An indicator with a value of one if the borrower
has an S&P Senior Unsecured Debt Rating
(SPLTICRM)
The weighted average of receivable age and
fixed asset age: (ACTQ/(ACTQ+PPENTQ)*
(PPENTQ/COGSQ) ) + (PPENTQ / (ACTQ+
PPENTQ)*(PPENTQ/DPY))
Ratio of tangible assets: (PPENTQ + INVTQ) /
ATQ
Expected Default Frequency, based on Merton
(1974), calculated based on Hillegeist et al.
(2004)
The annual change in EDF
Capital expenditures scaled by total assets:
CAPXY / ATQ
The market value of equity over the book value
of equity: CSHOQ*PRCCQ / CEQQ
Ratio of research and development expenditures
to total assets: XRDQ / ATQ
Compustat
ln(loan amount)
An indicator with a value of one if some portion
of the deal is a revolving line of credit
An indicator with a value of one if the loan has
Dealscan
Compustat
Compustat
Compustat
Compustat
Compustat
Compustat / CRSP
Compustat / CRSP
Compustat
Compustat
Compustat
Dealscan
Dealscan
28
Performance Pricing
Lenders
Collateral
Restructuring
Working Capital
Corporate Purposes
a term loan tranche labeled ‘B’ or higher
An indicator with a value of one if the loan
includes a performance pricing provision
The number of syndicate members
An indicator with a value of one if the loan
requires collateral
An indicator with a value of one if the stated
purpose of the loan is restructuring
An indicator with a value of one if the stated
purpose of the loan is working capital
An indicator with a value of one if the stated
purpose of the loan is corporate reasons
Dealscan
Dealscan
Dealscan
Dealscan
Dealscan
Dealscan
Notes: All Compustat variables are from the Xpressfeed quarterly data. All income statement variables are annualized by
summing the current and prior three quarterly observations. Compustat variables are winsorized at the top and bottom 1% of
observations.
29
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32
Table 1
Sample Selection
Starting
- borrowers with < 2 loans
- borrowers with no BS covenant
- borrowers with no dropped BS covenant
- borrowers with multiple drops
Final Sample
Deals
Borrowers
9,000
- 1,028
7,972
-3,542
4,430
-2,758
1,672
-214
1,458
3,087
-1,028
2,059
-474
1,585
-806
779
-50
729
Notes to Table 1: This table presents the sample selection process. I start with the intersection of LPC/Dealscan and Compustat
for 1996 through 2007, a total of 9,000 loan packages (“Deals”) to 3,087 borrowers. The first step removes borrowers with a
single loan over the sample period. The second step removes borrowers that never had a balance sheet covenant (net worth,
leverage, or current ratio) in a deal over the sample period. The third step removes borrowers who never “dropped” a balance
sheet covenant; that is, borrowers who have balance sheet covenants in all their deals. The final step removes observations of
borrowers with multiple drops; that is, borrowers who have a balance sheet covenant dropped at some point during the sample
period, and later have a loan package including a balance sheet covenant. The final sample consists of 729 borrowers and 1,458
loan packages.
33
Table 2
Distribution of Sample Deals
Year
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
Total
Pre-Drop
65
71
57
78
71
101
99
81
63
34
8
1
729
Drop
2
16
29
27
47
60
78
92
142
84
96
56
729
Notes to Table 2: This table tracks the number of sample observations by year. PRE-DROP observations are deals with a balance
sheet covenant (net worth, leverage, or current ratio). DROP observations are deals with no balance sheet covenant.
34
Table 3
Descriptive Statistics
Test Variables
Drop
Interest Spread
Maturity
IS Covenant
General Covenant
High Risk
Mean
0.500
194.223
42.498
0.769
2.259
0.423
Borrower Characteristics
Mean
Firm Size
ROA
Leverage
Rated
Asset Maturity
Asset Tangibility
6.474
0.137
0.280
0.420
5.891
0.456
Loan Characteristics
Mean
Loan Size
Revolver
Institutional Tranche
Performance Pricing
Lenders
Collateral
5.291
0.942
0.140
0.722
8.441
0.595
Standard
Deviation
0.500
136.223
19.403
0.422
1.872
0.494
Standard
Deviation
1.679
0.103
0.202
0.494
19.376
0.243
Standard
Deviation
1.727
0.234
0.347
0.448
8.990
0.491
1st
quartile
0.000
87.500
30.000
1.000
1.000
0.000
1st
quartile
5.391
0.085
0.126
0.000
1.463
0.263
1st
quartile
4.151
1.000
0.000
0.000
2.000
0.000
Median
0.500
175.000
37.120
1.000
1.000
0.000
Median
6.461
0.133
0.265
0.000
2.615
0.449
Median
5.317
1.000
0.000
1.000
6.000
1.000
3rd
quartile
1.000
265.625
60.000
1.000
5.000
1.000
3rd
quartile
7.535
0.188
0.395
1.000
6.035
0.650
3rd
quartile
6.477
1.000
0.000
1.000
11.000
1.000
Notes to Table 3: This table presents descriptive statistics on test variables, borrower characteristics, and loan characteristics.
DROP is an indicator with a value of one if the observation has no balance sheet covenants (net worth, leverage, or current ratio)
and zero otherwise. INTEREST SPREAD is the interest rate spread above the index (usually LIBOR or Prime) charged to the
borrower. MATURITY is the stated duration of the loan in months. IS COVENANT is an indicator for inclusion of an income
statement covenant (interest coverage, fixed charge coverage, or debt-to-earnings). GENERAL COVENANT is an index of
restrictive contract provisions, including restrictions on dividend payments, debt issuance, equity issuance, asset sales, and use of
insurance proceeds. HIGH RISK is an indicator with a value of one if EDF increases when the balance sheet covenant is dropped,
and zero otherwise. FIRM SIZE is the natural logarithm of total assets. ROA is EBITDA scaled by average total assets.
LEVERAGE is total debt scaled by total assets. RATED is an indicator if the borrower has an S&P Senior Debt Rating. ASSET
MATURITY is the weighted average of receivable age (accounts receivable / cost of goods sold) and fixed asset age (PP&E /
depreciation). ASSET TANGIBILITY is inventory plus PP&E scaled by total assets. LOAN SIZE is the natural logarithm of the
amount of the loan. REVOLVER is an indicator for if the loan package contains a revolving line of credit component.
INSTITUTIONAL TRANCHE is an indicator for if loan has a tranche titled “Term Loan B” or higher. PERFORMANCE
PRICING is an indicator for if the loan has a performance pricing provision. LENDERS is the number of syndicate members.
COLLATERAL is an indicator if the loan requires collateral. Detailed variable definitions are provided in the Appendix. All
borrower characteristics other than Firm Size and Rated are winsorized at the top and bottom 1% of observations.
35
Table 4
Correlation Matrix
-0.07
-0.06
0.11
-0.03
-0.01
0.03
-0.07
-0.02
0.01
-0.01
-0.01
0.08
0.01
0.16
0.67
0.28
0.08
0.79
-0.06
0.01
0.20
0.68
-0.43
-0.14
-0.03
0.07
0.06
0.19
0.05
-0.02
0.19
0.19
-0.18
0.31
0.34
0.24
0.16
-0.08
0.22
-0.01
0.20
0.15
0.24
0.08
0.52
-0.07
0.11
0.13
0.49
-0.20
-0.04
-0.01
0.03
-0.06
0.00
0.03
0.08
0.08
0.22
0.08
0.16
0.05
-0.45
0.25
0.08
0.08
-0.07
0.79
0.21
0.13
0.51
0.06
0.12
-0.07
-0.18
0.04
0.12
0.02
-0.02
-0.06
0.06
-0.08
-0.07
-0.16
-0.02
0.08
0.13
0.29
0.32
0.10
0.36
0.01
0.00
-0.01
0.23
0.11
0.07
-0.02
0.10
-0.11
-0.12
-0.33
0.28
0.37
0.19
-0.01
0.21
0.20
-0.04
0.13
-0.05
0.01
0.37
0.20
-0.02
0.64
0.25
-0.14
0.05
0.01
0.20
0.11
0.12
-0.02
-0.02
0.01
0.09
-0.05
0.06
0.11
0.34
0.81
-0.36
-0.11
0.20
0.13
-0.01
-0.02
0.09
0.26
0.31
-0.09
Collateral
0.11
-0.06
0.03
0.21
0.01
0.01
0.00
0.08
0.03
0.33
0.25
0.11
0.32
0.02
0.03
0.06
-0.06
-0.02
0.00
0.06
-0.08
0.05
0.07
Lenders
0.30
-0.02
-0.09
0.18
0.06
-0.08
-0.03
-0.05
0.07
0.12
0.10
0.37
0.13
0.08
0.05
-0.17
0.05
-0.08
0.00
-0.03
0.64
-0.02
0.28
Perf. Price
0.26
0.26
-0.03
0.08
0.21
0.02
0.05
0.04
0.02
0.28
0.05
0.32
0.28
0.27
0.06
0.02
0.26
0.00
0.04
0.21
0.13
0.14
-0.10
Inst.
Tranche
-0.10
-0.00
0.22
0.08
-0.49
-0.39
0.25
-0.20
-0.06
-0.01
-0.49
-0.12
0.33
-0.29
-0.40
0.62
-0.10
-0.35
0.18
0.20
0.05
-0.04
0.05
Revolver
0.08
-0.41
0.06
-0.11
-0.06
-0.07
Loan Size
0.00
0.10
-0.03
-0.02
0.11
Asset Tang.
Firm Size
-0.06
0.18
0.25
0.25
Asset Mat.
High Risk
-0.14
-0.07
0.26
Rated
Gen Cov
0.14
-0.12
Leverage
IS Cov
0.10
ROA
Maturity
0.08
0.14
-0.14
-0.07
0.00
0.08
-0.10
0.00
0.05
-0.05
-0.05
0.04
-0.07
0.13
-0.12
-0.02
0.03
Int. Spread
Drop
Drop
Int. Spread
Maturity
IS Cov
Gen Cov
High Risk
Firm Size
ROA
Leverage
Rated
Asset Mat.
Asset Tang.
Loan Size
Revolver
Inst. Tranche
Perf. Price
Lenders
Collateral
-0.06
-0.23
0.18
0.07
0.12
0.02
0.52
0.15
0.14
0.41
0.02
0.06
0.63
0.06
0.17
0.20
0.03
0.51
0.06
0.08
0.32
0.08
-0.43
-0.18
0.15
-0.20
-0.00
-0.05
-0.36
-0.01
0.26
-0.09
-0.21
-0.32
Notes to Table 4: This table presents simple correlations. Pearson correlations are in the upper triangle, with Spearman rank correlations in the lower. DROP is an indicator with a
value of one if the observation has no balance sheet covenants (net worth, leverage, or current ratio) and zero otherwise. INTEREST SPREAD is the interest rate spread above the
index (usually LIBOR or Prime) charged to the borrower. MATURITY is the stated duration of the loan in months. IS COVENANT is an indicator for inclusion of an income
statement covenant (interest coverage, fixed charge coverage, or debt-to-earnings). GENERAL COVENANT is an index of restrictive contract provisions, including restrictions on
dividend payments, debt issuance, equity issuance, asset sales, and use of insurance proceeds. HIGH RISK is an indicator with a value of one if EDF increases when the balance
sheet covenant is dropped, and zero otherwise. FIRM SIZE is the natural logarithm of total assets. ROA is EBITDA scaled by average total assets. LEVERAGE is total debt scaled
by total assets. RATED is an indicator if the borrower has an S&P Senior Debt Rating. ASSET MATURITY is the weighted average of receivable age (accounts receivable / cost
of goods sold) and fixed asset age (PP&E / depreciation). ASSET TANGIBILITY is inventory plus PP&E scaled by total assets. LOAN SIZE is natural logarithm of the amount of
the loan. REVOLVER is an indicator for if the loan package contains a revolving line of credit component. INSTITUTIONAL TRANCHE is an indicator for if loan has a tranche
titled “Term Loan B” or higher. PERFORMANCE PRICING is an indicator for if the loan has a performance pricing provision. LENDERS is the number of syndicate members.
COLLATERAL is an indicator if the loan requires collateral. Detailed variable definitions are provided in the Appendix. All borrower characteristics other than Firm Size and
Rated are winsorized at the top and bottom 1% of observations. Statistically significant correlations (<10% level) are in boldface.
36
Table 5
Descriptive Analysis
Test Variables
Interest Spread
Maturity
Income Statement Covenant
General Covenant Index
mean
median
mean
median
mean
median
mean
median
Borrower Characteristics
Firm Size
ROA
Leverage
Rated
Asset Maturity
Asset Tangibility
mean
median
mean
median
mean
median
mean
median
mean
median
mean
median
Loan Characteristics
Loan Size
Revolver
Institutional Tranche
Performance Pricing
Lenders
Collateral
mean
median
mean
median
mean
median
mean
median
mean
median
mean
median
Drop
208.044
192.500
45.119
48.000
0.712
1.000
2.148
1.000
Drop
6.605
6.571
0.127
0.125
0.284
0.262
0.443
0.000
6.239
2.432
0.310
0.233
Drop
5.374
5.416
0.926
1.000
0.184
0.000
0.669
1.000
7.925
6.000
0.608
1.000
Pre-Drop
180.401
150.000
39.877
36.000
0.826
1.000
2.369
1.000
Pre-Drop
6.344
6.306
0.148
0.142
0.275
0.268
0.396
0.000
5.538
2.852
0.323
0.252
Pre-Drop
5.208
5.298
0.957
1.000
0.096
0.000
0.774
1.000
8.957
6.000
0.583
1.000
Difference
27.643
42.500
5.241
12.000
-0.114
0.000
-0.221
0.000
Difference
0.262
0.265
-0.020
-0.017
0.009
-0.006
0.047
0.000
0.701
-0.420
-0.013
-0.019
Difference
0.166
0.118
-0.032
0.000
0.088
0.000
-0.104
0.000
-1.033
0.000
0.025
0.000
p-value
0.000
0.004
<0.0001
<0.0001
<0.0001
<0.0001
0.024
0.005
p-value
0.0030
0.0020
0.0050
0.0005
0.3879
0.9305
0.0713
0.0713
0.5076
0.0923
0.3028
0.1728
p-value
0.0662
0.0934
0.0101
0.0102
<0.0001
<0.0001
<0.0001
<0.0001
0.0282
0.4244
0.3372
0.3370
Notes to Table 5: This table presents differences in test and control variables based on inclusion of balance sheet covenants.
DROP observations are those without a balance sheet covenant. PRE-DROP observations are those from the period immediately
preceding the balance sheet covenant drop. DIFFERENCE is the average difference between the Drop and Pre-Drop periods,
with a p-value of the significance based on a t-test (for means) or Wilcoxon test (for medians). INTEREST SPREAD is the
interest rate spread above the index (usually LIBOR or Prime) charged to the borrower. MATURITY is the stated duration of the
loan in months. IS COVENANT is an indicator for inclusion of an income statement covenant (interest coverage, fixed charge
coverage, or debt-to-earnings). GENERAL COVENANT is an index of restrictive contract provisions, including restrictions on
dividend payments, debt issuance, equity issuance, asset sales, and use of insurance proceeds. HIGH RISK is an indicator with a
value of one if EDF increases when the balance sheet covenant is dropped, and zero otherwise. FIRM SIZE is the natural
logarithm of total assets. ROA is EBITDA scaled by average total assets. LEVERAGE is total debt scaled by total assets.
RATED is an indicator if the borrower has an S&P Senior Debt Rating. ASSET MATURITY is the weighted average of
receivable age (accounts receivable / cost of goods sold) and fixed asset age (PP&E / depreciation). ASSET TANGIBILITY is
inventory plus PP&E scaled by total assets. LOAN SIZE is natural logarithm of the amount of the loan. REVOLVER is an
indicator for if the loan package contains a revolving line of credit component. INSTITUTIONAL TRANCHE is an indicator for
if loan has a tranche titled “Term Loan B” or higher. PERFORMANCE PRICING is an indicator for if the loan has a
performance pricing provision. LENDERS is the number of syndicate members. COLLATERAL is an indicator if the loan
requires collateral. Detailed variable definitions are provided in the Appendix. All borrower characteristics other than Firm Size
and Rated are winsorized at the top and bottom 1% of observations. Statistically significant differences (<10% level) are in
boldface.
37
Table 6
Univariate Difference-in-Differences Analysis
Interest Spread
Obs
Mean
Drop
282
237.478
High Risk
Pre-Drop
Difference
282
168.229
69.249***
t-statistic
5.73
p-value
<0.0001
Drop
385
174.344
Low Risk
Pre-Drop
Difference
385
179.834
-5.49
t-statistic
-0.65
p-value
0.5187
Difference-in-Differences
(High Risk – Low Risk)
predicted sign
+
Diff-in-Diff
74.739***
t-statistic
5.06
p-value
<0.0001
Low Risk
Pre-Drop
Difference
385
38.367
9.919***
t-statistic
7.41
p-value
<0.0001
Difference-in-Differences
(High Risk – Low Risk)
predicted sign
Diff-in-Diff
-10.908***
t-statistic
-5.20
p-value
<0.0001
Low Risk
Pre-Drop
Difference
385
0.821
-0.086***
t-statistic
-2.88
p-value
0.0040
Difference-in-Differences
(High Risk – Low Risk)
predicted sign
+
Diff-in-Diff
-0.080†
t-statistic
-1.72
p-value
0.0846
Low Risk
Pre-Drop
Difference
385
2.132
-0.093
t-statistic
-0.71
p-value
0.4756
Difference-in-Differences
(High Risk – Low Risk)
predicted sign
+
Diff-in-Diff
-0.311
t-statistic
-1.49
p-value
0.1350
Maturity
Obs
Mean
Drop
282
41.809
High Risk
Pre-Drop
Difference
282
42.798
-0.989
t-statistic
-0.61
p-value
0.5404
Drop
385
48.286
IS Covenant
Obs
Mean
Drop
282
0.674
High Risk
Pre-Drop
Difference
282
0.840
-0.166***
t-statistic
-4.67
p-value
<0.0001
Drop
385
0.735
General Covenant
Obs
Mean
Drop
282
2.305
High Risk
Pre-Drop
Difference
282
2.709
-0.404**
t-statistic
-2.49
p-value
0.0127
Drop
385
2.039
Notes to Table 6: This table presents difference-in-difference analysis on four loan parameters. DROP observations are those
without a balance sheet covenant. PRE-DROP observations are those from the period immediately preceding the balance sheet
covenant drop. HIGH RISK are those observations where default risk (EDF) increased from the Pre-Drop to the Drop period.
LOW RISK are those observations where default risk stayed the same or decreased from the Pre-Drop to the Drop period.
INTEREST SPREAD is the interest rate spread above the index (usually LIBOR or Prime) charged to the borrower. MATURITY
is the stated duration of the loan in months. IS COVENANT is an indicator for inclusion of an income statement covenant
(interest coverage, fixed charge coverage, or debt-to-earnings). GENERAL COVENANT is an index of restrictive contract
provisions, including restrictions on dividend payments, debt issuance, equity issuance, asset sales, and use of insurance
proceeds. The table sorts firms into High Risk and Low Risk groups, and measures the difference between the Drop and Pre-Drop
observations within these groups. The difference-in-differences captures the Drop – Pre-Drop difference between the High Risk
and Low Risk groups. ***, **, and * indiciate statistical significance at the 1%, 5% and 10% level of significance. † indicates
statistical significance in the opposite of predicted direction at the 10% level.
38
Table 7
Multivariate Regression Analysis
Dependent Variable =
Drop
High Risk
Drop * High Risk
Maturity
Interest Spread
3.138
(0.40)
-11.633
(-1.37)
35.296***
(2.94)
-0.576***
(-3.11)
Interest Spread
IS Covenant
Firm Size
ROA
Leverage
Rated
0.693
(0.08)
-27.695***
(-7.35)
-319.780***
(-9.87)
150.984***
(8.73)
0.556
(0.07)
Asset Maturity
Asset Tangibility
Loan Size
Revolver
Institutional Tranche
Performance Pricing
Lenders
Maturity
8.390***
(6.90)
3.437***
(2.59)
-7.388***
(-3.91)
-0.021***
(-4.70)
7.374***
(6.11)
-3.906***
(-6.78)
-0.260
(-0.21)
1.210
(1.33)
0.250
(0.08)
4.435***
(8.79)
-11.875***
(-3.32)
-61.738***
(-4.39)
96.222***
(9.96)
-21.427***
(-2.69)
0.645
(1.48)
14.619***
(9.51)
526.265***
(9.91)
1,122
OLS
0.47
45.187***
(5.66)
1,248
OLS
0.28
Collateral
Constant
Observations
Regression Model
Adjusted R2
Concordance
IS Covenant
-0.292**
(-2.21)
-0.155
(-1.01)
-0.028
(-0.13)
General Covenant
-0.086
(-1.45)
0.191***
(3.13)
-0.090
(-1.04)
-0.362***
(-5.43)
1.968***
(3.56)
0.970***
(3.13)
-0.229
(-1.52)
-0.061**
(-2.06)
0.249
(0.99)
0.537***
(4.38)
-0.096
(-1.61)
0.131**
(2.14)
-0.098
(-0.46)
0.574***
(2.88)
1.174***
(9.65)
0.034***
(3.28)
0.034
(0.26)
0.677
(0.83)
1,088
Probit
0.087***
(3.24)
-0.111
(-1.04)
0.477***
(7.88)
0.418***
(6.92)
0.001
(0.47)
0.450***
(8.07)
-0.216
(-0.49)
1,122
Negative Binomial
0.83
Notes to Table 7: This table presents multivariate regression results. There are four regressions for the four different dependent
variables. Reported results include coefficient estimates and t-statistics (for OLS) or z-statistics (for Probit and Negative
Binomial). INTEREST SPREAD is the interest rate spread above the index (usually LIBOR or Prime) charged to the borrower.
MATURITY is the stated duration of the loan in months. IS COVENANT is an indicator for inclusion of an income statement
covenant (interest coverage, fixed charge coverage, or debt-to-earnings). GENERAL COVENANT is an index of restrictive
contract provisions, including restrictions on dividend payments, debt issuance, equity issuance, asset sales, and use of insurance
proceeds. DROP is an indicator with a value of one if the observation has no balance sheet covenants (net worth, leverage, or
current ratio) and zero otherwise. HIGH RISK is an indicator with a value of one if EDF increases when the balance sheet
covenant is dropped, and zero otherwise. FIRM SIZE is the natural logarithm of total assets. ROA is EBITDA scaled by average
total assets. LEVERAGE is total debt scaled by total assets. RATED is an indicator if the borrower has an S&P Senior Debt
39
Rating. ASSET MATURITY is the weighted average of receivable age (accounts receivable / cost of goods sold) and fixed asset
age (PP&E / depreciation). ASSET TANGIBILITY is inventory plus PP&E scaled by total assets. LOAN SIZE is the natural
logarithm of the amount of the loan. REVOLVER is an indicator for if the loan package contains a revolving line of credit
component. INSTITUTIONAL TRANCHE is an indicator for if loan has a tranche titled “Term Loan B” or higher.
PERFORMANCE PRICING is an indicator for if the loan has a performance pricing provision. LENDERS is the number of
syndicate members. COLLATERAL is an indicator if the loan requires collateral. Concordance is the percentage of observations
correctly classified in the probit model. Detailed variable definitions are provided in the Appendix. All borrower characteristics
other than Firm Size and Rated are winsorized at the top and bottom 1% of observations. Each regression includes industry fixed
effects, and standard errors are clustered by borrower. ***, **, and * indicate statistical significance at the 1%, 5%, and 10%
levels respectively.
40
Table 8
Instrumental Variable Regressions
Drop
High Risk
Drop * High Risk
Maturity
Interest Spread
1st Stage
2nd Stage
9.105***
-13.666
(7.84)
(-1.13)
2.464*
-16.694*
(1.67)
(-1.93)
-7.434***
46.220***
(-3.86)
(3.42)
1.193
(1.13)
Maturity
1st Stage
2nd Stage
1.178
8.557***
(0.19)
(7.53)
-11.648
2.678*
(-1.39)
(1.89)
35.688***
-6.609***
(3.01)
(-3.32)
Interest Spread
IS Covenant
Firm Size
ROA
Leverage
Rated
Asset Maturity
Asset Tangibility
Loan Size
Revolver
Institutional Tranche
Performance Pricing
Lenders
Purpose: Restructuring
Purpose: Working Capital
Purpose: Corporate
Market-to-Book
R&D Intensity
Capital Expenditures
Constant
Observations
R2
Sargan-Basmann statistic (χ2, p-value)
Durbin-Wu-Hausman statistic (F, p-value)
Partial R2
Partial F-statistic (F, p-value)
5.405***
-9.732
(3.37)
(0.86)
-2.650***
-24.562***
(-3.50)
(-4.28)
14.841***
-370.985***
(2.47)
(-8.89)
-7.085**
162.320***
(-2.15)
(6.19)
-0.615
0.306
(-0.41)
(0.03)
1.929
(1.57)
3.925
(1.00)
3.830***
-16.117***
(5.64)
(-2.61)
0.829
-80.419***
(0.22)
(-2.81)
13.495***
70.284***
(7.73)
(3.66)
5.317***
-34.726***
(3.56)
(-2.82)
0.003
0.540
(0.04)
(1.10)
9.014***
(4.54)
6.787***
(3.63)
5.496***
(2.77)
-0.270*
(-1.83)
-11.835
(-1.50)
-10.267
(-1.07)
18.552**
496.857***
(2.28)
(7.28)
1,046
1,046
0.33
0.47
8.297, 0.3072
2.851, 0.0918
0.036
3.762, 0.0003
-12.751
(-1.35)
-23.504***
(-5.10)
-347.349***
(-8.74)
159.901***
(6.30)
0.720
(0.09)
7.236
(0.86)
28.900
(1.23)
-15.998***
(-4.07)
95.425***
(7.63)
-0.044***
(-3.75)
7.289***
(4.91)
-4.417***
(-5.73)
0.582
(0.40)
1.155
(0.96)
1.258
(0.35)
3.862***
(5.91)
17.938***
(8.39)
420.689***
47.710***
(7.26)
(5.07)
1,098
1,098
0.46
0.32
0.004, 0.9481
3.824, 0.0510
0.169
68.395, <0.0001
Notes to Table 8: This table presents instrumental variable regressions for Interest Spread and Maturity, using two-stage least
squares. Reported results include coefficient estimates and t-statistics (for 1st stage regressions) or z-statistics (for 2nd stage
regressions). INTEREST SPREAD is the interest rate spread above the index (usually LIBOR or Prime) charged to the borrower.
MATURITY is the stated duration of the loan in months. DROP is an indicator with a value of one if the observation has no
41
balance sheet covenants (net worth, leverage, or current ratio) and zero otherwise. HIGH RISK is an indicator with a value of one
if EDF increases when the balance sheet covenant is dropped, and zero otherwise. IS COVENANT is an indicator for inclusion of
an income statement covenant (interest coverage, fixed charge coverage, or debt-to-earnings). FIRM SIZE is the natural
logarithm of total assets. ROA is EBITDA scaled by average total assets. LEVERAGE is total debt scaled by total assets.
RATED is an indicator if the borrower has an S&P Senior Secured Debt Rating. ASSET MATURITY is the weighted average of
receivable age (accounts receivable / cost of goods sold) and fixed asset age (PP&E / depreciation). ASSET TANGIBILITY is
inventory plus PP&E scaled by total assets. LOAN SIZE is the natural logarithm of the amount of the loan. REVOLVER is an
indicator for if the loan package contains a revolving line of credit component. INSTITUTIONAL TRANCHE is an indicator for
if loan has a tranche titled “Term Loan B” or higher. PERFORMANCE PRICING is an indicator for if the loan has a
performance pricing provision. LENDERS is the number of syndicate members. COLLATERAL is an indicator if the loan
requires collateral. PURPOSE: RESTRUCTURING is an indicator for if the loan’s purpose is restructuring or reorganization.
PURPOSE: WORKING CAPITAL is an indicator for if the loan’s purpose is working capital. PURPOSE: CORPORATE is an
indicator for if the loan’s purpose is related to general corporate operations. MARKET-TO-BOOK is the ratio of the market value
of equity to the book value of equity. R&D INTENSITY is the ratio of research and development expenditures to sales.
CAPITAL EXPENDITURES is capital expenditures scaled by total assets. There are four specification tests for the 1st stage
regressions. The Sargan-Basmann statistic tests for overidentifying restrictions: a significant statistic indicates the instruments
may not be exogenous. The Dubin-Wu-Hausman statistic tests whether the presumed endogenous variable is in fact endogenous:
a significant coefficient indicates endogeneity. The Partial R2 and Partial F-statistic test the joint significance of the set of
instruments. Detailed variable definitions are provided in the Appendix. All borrower characteristics other than Firm Size and
Rated are winsorized at the top and bottom 1% of observations. Each regression includes industry fixed effects, and standard
errors are clustered by borrower. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels respectively.
42
Table 9
Endogenous DROP
1st Stage Selection Equation
Dependent Variable =
Drop
Predicted Drop
High Risk
0.337***
(3.26)
Predicted Drop * High Risk
Maturity
Interest Spread
Income Statement Covenant
Firm Size
ROA
Leverage
Rated
Asset Maturity
Asset Tangibility
Loan Size
Revolver
Institutional Tranche
Performance Pricing
Lenders
Collateral
EDF
Change in EDF
Constant
Observations
Concordance
R2
-0.021
(-0.35)
-1.007*
(-1.87)
0.212
(0.74)
0.080
(0.62)
-0.172*
(-1.91)
-0.274
(-0.91)
0.086
(1.56)
0.200
(0.92)
0.392***
(2.67)
-0.640***
(-5.44)
-0.010
(-1.42)
-0.070
(-0.63)
1.029**
(2.37)
-0.263
(-0.73)
-1.653*
(-1.76)
1,098
0.73
2nd Stage IV Regressions
Dependent Variable =
Interest Spread
Maturity
-12.124
8.681***
(-0.95)
(6.85)
-18.837**
2.243
(-2.22)
(1.48)
51.332***
-5.885***
(3.31)
(-2.63)
1.194
(1.140
-0.047***
(-3.96)
-11.136
7.445***
(-1.01)
(4.98)
-25.168***
-4.656***
(-4.31)
(-5.90)
-366.078***
(-8.83)
164.504***
(6.43)
2.354
0.311
(0.26)
(0.21)
1.321
(1.11)
2.310
(0.63)
-16.261***
3.918***
(-2.69)
(6.01)
-80.897***
(-2.85)
67.703***
17.785***
(3.54)
(8.29)
-32.628**
(-2.53)
0.602
(1.23)
498.507***
(7.26)
1,046
48.848***
(5.21)
1,098
0.48
0.31
Notes to Table 9: This table presents instrumental variable regression results for Interest Spread and Maturity when Drop is
replaced by a predicted value based on various borrower and loan characteristics. Reported results include coefficient estimates
and z-statistics. INTEREST SPREAD is the interest rate spread above the index (usually LIBOR or Prime) charged to the
borrower. MATURITY is the stated duration of the loan in months. DROP is an indicator with a value of one if the observation
has no balance sheet covenants (net worth, leverage, or current ratio) and zero otherwise. HIGH RISK is an indicator with a value
of one if EDF increases when the balance sheet covenant is dropped, and zero otherwise. IS COVENANT is an indicator for
inclusion of an income statement covenant (interest coverage, fixed charge coverage, or debt-to-earnings). FIRM SIZE is the
natural logarithm of total assets. ROA is EBITDA scaled by average total assets. LEVERAGE is total debt scaled by total assets.
RATED is an indicator if the borrower has an S&P Senior Debt Rating. ASSET MATURITY is the weighted average of
43
receivable age (accounts receivable / cost of goods sold) and fixed asset age (PP&E / depreciation). ASSET TANGIBILITY is
inventory plus PP&E scaled by total assets. LOAN SIZE is the natural logarithm of the amount of the loan. REVOLVER is an
indicator for if the loan package contains a revolving line of credit component. INSTITUTIONAL TRANCHE is an indicator for
if loan has a tranche titled “Term Loan B” or higher. PERFORMANCE PRICING is an indicator for if the loan has a
performance pricing provision. LENDERS is the number of syndicate members. COLLATERAL is an indicator if the loan
requires collateral. EDF is the likelihood of default based on the Merton (1974) model. CHANGE IN EDF is the annual change
in EDF. PREDICTED DROP is the based on the 1st stage regression of Drop on borrower and loan variables; predicted values
less than 0.5 receive a value of zero for Predicted Drop, while predicted value greater than or equal to 0.5 receive a value of one.
Concordance is the percentage of observations correctly classified in the probit model. All borrower characteristics other than
Firm Size and Rated are winsorized at the top and bottom 1% of observations. Each regression includes industry fixed effects,
and standard errors are clustered by borrower. ***, **, and * indicate statistical significance at the 1%, 5%, and 10% levels
respectively.
44
Table 10
Sensitivity Tests
Panel A: Piece-Wise Regressions based on Quartile of Change in EDF
Quartile
2
3
Interest Spread
Coefficient
-5.619
-21.562
(N = 1,122)
t-statistic
(-1.74)
(-0.40)
Maturity
Coefficient
0.516
-6.876
(N = 1,248)
t-statistic
(0.23)
(-3.02)
Panel B: Other Sensitivity Tests
Specification:
predicted
sign
Coefficient
Interest
+
t-statistic
Spread
Observations
Coefficient
t-statistic
Maturity
Observations
4
50.730
(2.79)
-7.699
(-3.17)
Chow Test (4 – 2)
F: 20.67
p: <0.0001
F: 10.82
p: 0.0011
1
2
3
4
5
NW
LEV
CR
Rated
Unrated
34.237
(2.54)
836
-5.708
(-2.71)
938
27.272
(1.73)
337
-7.539
(-2.07)
362
29.339
(0.77)
187
-7.188
(-1.82)
201
23.181
(1.23)
492
-6.153
(-2.17)
544
42.041
(2.87)
630
-7.959
(-3.61)
704
Notes to Table 10: This table presents summary results for sensitivity tests. Panel A presents results for piece-wise regressions
based on the quartile of Change in EDF. The coefficient presented is on the interaction of Drop with the quartile of Change in
EDF (with quartile 1 serving as the reference category). Panel B presents results for various sensitivity tests. Specifications 1, 2,
and 3 run the OLS regressions for Interest Spread and Maturity, but use only observations that drop a net worth, leverage, or
current ratio covenant respectively. Specifications 4 and 5 test subsamples that are rated (based on having an S&P Senior Debt
Rating) and unrated respectively. Significant coefficients are in boldface.
45
Figure 1
46