Debt Maturity, Investments, and the Choice of CovenantsDaniel Saavedra*
UCLA Anderson School of Management
daniel.saavedra@anderson.ucla.edu

Abstract
How do debt agreements allocate control rights over future investment decisions? I study thisquestion in the context of prior theory, which suggests that conflicts of interest between borrowers
and lenders increase with debt maturity because it is more likely than an unexpected investment
opportunity will arise before the debt is repaid. Consistent with income statement-based (balance
sheet-based) covenants being more (less) efficient in allocating control rights over future
investment decisions, I find that debt contracts with longer maturities have more (fewer)
performance (capital) covenants. Moreover, using a novel dataset with detailed information about
the design of capital expenditure covenants, I find that debt contracts with longer maturities
mitigate investment inefficiencies by including tailored capital expenditure covenants that (1)allocate control rights over investments contingent on the borrower’s performance (e.g., EBITDA
or revenues), (2) allow the borrower to carryforward unused capital expenditure amounts to future
periods, and/or (3) include dynamic capital expenditure thresholds that are tighter at loan inception
but subsequently loosen up. Finally, I find that my results are stronger when the borrower has ahigher propensity to face unanticipated investment decisions after loan initiation.

October 2018

Keywords: Investments, Loan Maturity, Covenants, Security Design, Bank LoansJEL Classification: G32, G21, C78, L14* I thank David Aboody, Brian Akins, Judson Caskey, Patricia Dechow, Henry Friedman, John
Hughes, William Mann, VG Narayanan, Tatiana Sandino, Brett Trueman, Rodrigo Verdi, Charles
Wang, Joseph Weber and seminar participants at Harvard, UCLA, USC, and the EAA annual
meeting for helpful suggestions. I gratefully acknowledge the financial support of the UCLA
Anderson School of Management. All errors are my own.

1. Introduction
How do debt agreements allocate control rights over future investment decisions? I study
this question in the context of prior theory which suggests that conflicts of interest between
borrowers and lenders increase with debt maturity (Myers 1977; Diamond 1991; Childs, Mauer,
and Ott 2005; Diamond and He 2014). As these models suggest, a key reason for this is that thelonger the time until maturity, the greater the likelihood that unexpected investment opportunities
will arise before the debt is repaid. These opportunities have the potential of generating additional
conflicts of interest, as the payoff functions of the contracting parties with respect to theseinvestments may differ. Given that bank financing is ubiquitous (Sufi 2009) and investment
decisions are important, it is imperative to have a better understanding about how contracting
parties minimize related agency costs. In this study, I investigate whether loan contracts include
different accounting-based and capital expenditure covenants at initiation as investment conflicts
vary with loan maturity. I focus on maturity because the passage of time is a necessary condition
for the arrival of unanticipated investment opportunities.
The optimal contract has to trade off two different costs related to over and underinvestment. If contracting parties included no covenants restricting investment, managers would
have the decision rights and incentives to over-invest in risky projects with a negative net present
value (NPV), thereby expropriating wealth from lenders (Jensen and Meckling 1976). If
contracting parties included covenants that restrict investments, lenders will have the decisionrights if the restriction is binding and potentially not allow positive but risky NPV projects if theseincrease the likelihood of default, leading to under-investment in good projects (Jensen andMeckling 1976). Although there might be scope for renegotiation, managers will still under-invest

1

given that they will have to share the surplus with lenders, thereby reducing their incentives topursue profitable investment opportunities (Holmstrom 1982).
One apparently easy way out to minimize these agency costs is to shorten the maturity of
the loan. Debt that matures before an investment option is to be exercised does not induce
suboptimal investment decisions. This seems to be a good solution, but there are costs of rollingover short maturity debt claims. For instance, Diamond (1991) argues that short-term debt exposes
the firm to a liquidity risk if lenders will not allow refinancing, and the firm is liquidated. This isa risk that became evident during the recent 2008 financial crisis when many borrowers were notable to access the credit markets (Ivashina and Scharfstein 2010). As a result, it is plausible that
contracting parties look at alternative contractual features such as covenants to deal withinvestment conflicts associated with longer maturities.
To develop my predictions of how covenant packages vary with loan maturity, I rely on
the theoretical model introduced by Aghion and Bolton (1992). They suggest that in long-term
debt contracts, the joint surplus of the contracting parties is maximized when control rights overinvestment projects are allocated to the party that has an incentive to take the most efficient action.
Ideally, covenants would allocate control rights to lenders whenever the manager has incentives
to invest in a negative NPV project and leave the decision rights over investments with the manager
when a positive NPV project is available. However, in practice, it is typically not feasible todelineate contractually all future negative or positive NPV projects ex ante, or for a court to enforce
ex post such a vague contractual provision. Consequently, covenants are instead conditioned on
more easily observable accounting variables, such as profitability, that are likely to be imperfectly
correlated with the availability of bad or good future projects (Garleanu and Zwiebel 2009;
Christensen, Nikolaev, and Wittenberg-Moerman 2016). In particular, it is reasonable to assume2

that when the borrower is performing poorly (well), there will be fewer (more) good projects.1 As
a result, I expect that at loan initiation, contracts with longer (shorter) maturities will include more
(fewer) covenants that allocate control rights to lenders when the borrower is performing poorly
but that leave the decision rights with the borrower when it is performing well. This leads me tomake the following predictions regarding accounting-based and capital expenditure covenants.2
First, I focus on accounting-based covenants, which are widely used in debt contracts andaffect the borrower’s ability to make investments if a covenant is binding. I expect that contracts
with longer maturities will include more performance or income statement (as opposed to capitalor balance sheet) covenants because they are timelier in transferring decision rights to lenders
when performance is poor and fewer good projects are available (Christensen and Nikolaev 2012;
Hollander and Verriest 2016; Dyreng, Vashishtha, and Weber 2017), but also more likely to leavedecision rights with the borrower when performance is good, and more positive NPV projects are
obtainable (Saavedra 2017). In contrast, capital covenants serve the purpose of making sure thatthe borrower is sufficiently capitalized (Christensen and Nikolaev 2012) and are less useful inallocating control rights in a state contingent manner (Saavedra 2017).3
Second, I focus on the design of the capital expenditure covenant. This covenant is present
in about 24 percent of contracts and explicitly lays out the conditions under which the borrower
can engage in future capital expenditure investments and offers significant variation in terms of
how it is designed. In my sample, 51 percent of the contracts with a restriction could be considered

1Consistent with this argument, Dyreng, Vashishtha, and Weber (2017) find that the earnings measure used inperformance covenants predicts future cash flows, which in turn are directly related to the outcomes of investments.
2
As I detail in the hypothesis section, if there is scope for renegotiation, the covenant choice here suggested alsoachieves efficient ex-post investment outcomes (Aghion, Dewatripont, and Rey 1994).
3
Consistent with capital covenants being designed to make sure shareholders have sufficient equity at stake, Beatty,
Weber and Yu (2008) and Frankel, Seethamraju, and Zach (2008) find that net worth covenants, a primary capitalcovenant, often include income escalators, which are adjustments to net worth covenant thresholds that reduce theextent to which positive reported income increases covenant slack.

3

as plain vanilla capital expenditure covenants, as they only stipulate the maximum amount that theborrower can invest during each year of the contract. In contrast, 49 percent of the remaining
contracts have a tailored capital expenditure restriction that includes state contingent provisions
that allocate control rights over investments contingent on the borrower’s performance and/or
carryforward provisions that allow the borrower to roll over unused capital expenditure amounts.
The state contingent provision reduces over- and under-investment concerns because, similar to
performance covenants, it conditions the amount of investments on the performance of theborrower (e.g., EBITDA or revenues). The carryforward provision does not allocate control rights
contingent on performance, but it allows the borrower to carry to future periods any amounts not
used in the current year. Thus, it incentivizes managers not to over-invest when borrowers are
performing poorly so that they will not be forced to under-invest if borrowers are performing well.
Given that tailored capital expenditure covenants are more adequate in addressing investment
concerns, I predict that contracts with longer maturities are more likely to include a tailored capital
expenditure covenant as opposed to a plain vanilla capital expenditure covenant.
A challenge with studying the relationship between loan maturity and covenant choice isthat maturity has been shown to be related to specific firm characteristics such as size and growth
opportunities (Barclay and Smith 1995), which in turn could affect covenant choice. To mitigate
these concerns, in addition to controlling for a large set of firm and contract characteristics, I use
a firm-fixed effect specification that addresses concerns related to firm specific, time-invariant
omitted variables.
Notably, I find an opposite relationship with loan maturity for capital- and performancebased covenants: As the contract maturity lengthens, performance-based covenants become morecommon while capital-based covenants become less common. This stark pattern highlights the4differing roles of these two types of covenants and is consistent with performance covenants being
more adequate in allocating control rights contingent on the availability of good projects.
Moreover, exploiting detailed information about how capital expenditure covenants are designed,
I find that loan maturity is positively (negatively) related to the inclusion of a tailored (plain
vanilla) capital expenditure covenant. These findings suggest that when loan maturity is longer,
contracting parties settle ex-ante on performance and tailored capital expenditure covenants that
reduce concerns related to over- and under-investment.
A concern with the firm-fixed effects specification used in the main analysis is that I cannot
rule out that firm-specific, time-varying omitted variables might be driving my results. To mitigate
this concern, I use a within firm-year specification, which allows me to compare the effect of loan
maturity on covenant choice for loans issued by the same firm in the same year. Using a sampleof firms issuing multiple loans in a given year, I find that my results are largely robust to using
this specification. Because the within firm-year estimation is very demanding and eliminates a
substantial amount of variation, I only use it as a sensitivity check.
To further strengthen the argument that contracting parties select covenants with the
purpose of reducing future investment conflicts, I conduct cross-sectional tests based on the
borrower’s propensity to face future unexpected investment decisions. Using a high market-tobook ratio, heavy investment in research and development activities, and high sales growth asproxies for unexpected or uncertain future investment decisions from prior research (e.g., Billet,
King, and Mauer 2007), I find that for these borrowers the association between loan maturity andthe inclusion of performance and tailored capital expenditure covenants becomes even stronger.
This result also mitigates the concern that contracting parties only rely on performance-linked
covenants with the goal of making the effective maturity of long-term contracts shorter when a5company underperforms, giving lenders the option to continue or abandon existing projects(Caskey and Hughes 2012). That said, I cannot fully rule out that this is a complementary
investment related explanation for some of my results.4
I also explore the role of incentive alignment on the choice of covenants. I find that whenfirms have a small fraction of debt in their capital structures (i.e., when the incentives of the
managers and debtholders are more aligned), contracts rely less on performance or tailored capital
expenditure covenants. However, I find that the negative relationship between incentive alignment
and these covenants is attenuated as the likelihood of a change in capital structure (i.e., incentivealignment) increases with maturity. Finally, consistent with the prediction in Garleanu and Zwiebel(2009) that in the presence of agency problems, contracts will be tighter at loan inception andsubsequently loosen up, I find that contracts with longer maturities have dynamic capital
expenditure thresholds that are increasing over time.
My study contributes to the literature by documenting how debt agreements allocate exante control rights over future investment decisions. This is an important topic given that mostfirms in the U.S. have a bank loan and that investments are a key driver of value creation. I provide
evidence that contracting parties select different accounting-based and capital expenditurecovenants at contract initiation as investment conflicts vary with loan maturity. I find that for
longer maturities, debt contracts have more covenants that are directly linked to the current
performance of the borrower and have tailored capital expenditure covenants. As a result, myfindings address the call in Skinner (2011) and Christensen et al. (2016) to understand better thechannels through which specific covenants facilitate contracting.

4

Moreover, the fact that contracting parties put a significant effort in the design of capex covenants (e.g., contracting
parties need to agree on which accounting metric to use when conditioning future capex investment on performanceor what proportion of unused capex amounts can be carried forward) suggests that future investment considerations
are relevant when structuring loan terms.

6This study also adds to prior research that documents that income statement and balance
sheet variables are used for different purposes in debt contracts (Demerjian, 2011; Christensen and
Nikolaev 2012; Saavedra 2017). In addition, to explore a new research question, I provide detailed
evidence that accounting variables are also used in the design of capital expenditure covenants.
Prior research on this restriction (e..g, Nini, Smith, and Sufi 2009) did not explore the extent towhich accounting metrics are used to customize the capital expenditure covenant. I find that moststate contingent provisions in capital expenditure restrictions are conditional on income statement
or performance variables. These findings further shed light on ways in which accounting improves
contracting efficiency (Watts and Zimmerman 1986; Christensen et. al. 2016).
My paper is most closely related to Billet et al. (2007), who provide evidence that an
aggregate measure of covenant protection in public debt contracts is increasing in debt maturity.
My findings are different in that I focus on private debt and the specific choice of covenants (e.g.,
tailored vs. plain vanilla capital expenditure covenant) that minimizes investment inefficiencies.
My study is also related to prior work that shows that creditors exercise control over a firm’s
investment decisions ex post loan initiation, either by the use of capex restrictions (Nini et al. 2009)or through renegotiations of covenants (e.g., Chava and Roberts 2008; Denis and Wang 2014;
Nikolaev 2018). My contribution to this literature is in understanding the use of ex ante statecontingent allocations of control over future investments.
The remainder of the paper is organized as follows: Section 2 discusses the theoreticalmotivation and empirical predictions. Section 3 presents the data and main variables. Section 4
discusses the empirical results. Section 5 presents additional tests including the effect of loan
maturity on covenant strictness, and Section 6 concludes.

7

2. Theoretical motivation and empirical predictions
2.1. Loan maturity and conflicts of interest about future investments
As Jensen and Meckling (1976) and Myers (1977) argue, when the firm has risky debt
outstanding and when managers act to maximize equity value rather than total firm value,
managers have incentives to deviate from the optimal investment path. The loss in firm value
attributable to these suboptimal investment decisions constitutes a significant component of theagency cost of debt. The other component is the cost of contracting mechanisms that the firm uses
to mitigate stockholder–lender conflicts (e.g., covenants).
Stockholder–lender conflicts over the exercise of investment options can be mitigated withshort-term debt. Myers (1977) observes that if debt matures before investment options are
exercised, the manager’s incentive to deviate from a firm value-maximizing investment policy iseliminated. More generally, Childs et al. (2005) argue that short-term debt can mitigate both underand over-investment incentives by making the debt less sensitive to changes in firm value.
Diamond (1991) argues that short-term debt exposes the firm to a liquidity risk if lenders
will not allow refinancing, and the firm is liquidated. Further, Childs et al. (2005) argue that
although short-term debt can mitigate incentives to under- and over-invest in growth options, thisbenefit must be balanced against the greater liquidity risk of refunding short-term debt. An
alternative solution for the firm is to issue debt with longer maturities but to work with the lenders
to adjust the covenant packages to account for the increases in conflicts of interests associated withthose longer maturities. In this study, I investigate whether firms employ this solution.
2.2. Optimal allocation of control rights in long-term debt contracts
Aghion and Bolton (1992) develop a model to analyze incomplete long-term financial
contracts between a borrower (entrepreneur) and lenders (wealthy investors). The borrower raises
8funds from lenders to finance an investment project. Future investment decisions regarding thisproject have to be taken, which due to contractual incompleteness cannot be perfectly determinedin the initial contract. Moreover, the contracting parties have potentially conflicting objectives
about future investments because the borrower cares about both pecuniary and non-pecuniary
returns from the project while the lenders are only concerned about monetary returns. As a result,
it is important for lenders to limit the borrower’s actions by acquiring some control rights. The
authors show that in the case of debt financing, contingent allocation of control maximizes thejoint surplus of the contracting parities. Either the lender or the borrower might be in control
depending on the realization of a publicly verifiable signal such as the borrower’s profitability,
which is imperfectly correlated with the state of nature of the project, which is not contractible exante. When the firm is profitable, it is likely that more good projects are available and, therefore,
optimal that the borrower retains the decision rights. In contrast, when the firm is not profitable(i.e., close to default), fewer good projects will be available and, thus, optimal that lenders obtain
the decision rights. In that case, the lenders can decide to liquidate the firm or renegotiate thecontract under more favorable terms. Aghion and Bolton suggest that covenants in debt contracts
can implement such an optimal governance structure.
2.3. Main predictions
As mentioned earlier, my prediction is that contracts with longer maturities will structure
covenant packages in order to minimize related over- and under-investment problems. Following
the intuition from the Aghion and Bolton (1992) model, the contracting parties should allocate
control rights to lenders when the borrower is close to default, and managers have more incentives
to over-invest but leave the decision rights over investments with the borrower when it isperforming well and should invest in all positive NPV projects. As a result, contracts with longer

9maturities should include more performance (as opposed to capital) covenants because they are
more likely to have a stronger correlation with the availability of good projects. In contrast,
performance covenants are less useful in short-term contracts due to the lower likelihood ofinvestment conflicts that require a state contingent allocation.
For instance, contrast the Interest-coverage ratio (a performance) covenant to the Net-worth(a capital) covenant. The Interest-coverage ratio (i.e., earnings before interest and taxes to interest
expense) covenant has an earnings measure in the numerator, which is likely to have a strong
correlation with the current performance and the availability of good investment projects. In
contrast, the Net-worth (i.e., total assets minus total liabilities) covenant is based on a summary
measure that includes current income, retained earnings (including big bath charges, acquisition
accounting, and cookie jar “reserves”) 5, and dividend and payout decisions. As a result, current
income is more indicative of investment opportunities than is net worth. The current performanceof the firm (i.e., current net income) is only one of many components of net worth, making the
Net-worth covenant less efficient relative to the Interest-coverage ratio covenant in allocating
control rights over future investments.
It is important to note that the here described ex-ante allocation of control rights is also
efficient in terms of monitoring the ex-post renegotiation of the debt contract. As described in themodel developed by Aghion, Dewatripont, and Rey (1994), efficient ex-post investment outcomesare achieved by ex-ante allocating the control rights to the contracting party whose efforts
contribute more to the joint surplus. For instance, assume a long-term loan contract that could
allocate control rights based on either performance or capital covenants. Because capital covenants
are a noisier signal of the availability of good projects relative to performance covenants, there is5

In contrast, prior research has shown that performance covenants remove transitory items that are not indicative of
future performance (e.g., Li 2010).

10

a higher likelihood that a capital covenant is going to allocate control rights to lenders when the
borrower is in a state distant from default and should optimally have the control rights. This would
lead to an under-investment problem because the borrower will not capture the full benefits of anincrease of its investment due having to share the surplus with lenders (Holmstrom 1982). If, incontrast, the contract includes a performance covenant that is more efficient in allocating control
rights to the firm in good states, the manager will have the right incentives to pursue theinvestment.6 Based on these arguments, I state my first hypothesis in alternate form:
H1: Ceteris paribus, contracts with longer maturities are more (less) likely to include
performance (balance) covenants than contracts with shorter maturities.
Next, I predict that contracts with longer maturities are more likely to include a tailoredcapital expenditure covenant as opposed to a plain vanilla capital expenditure covenant. Tailoredcapital expenditure restrictions include provisions that (1) allocate control rights overinvestments contingent on the borrower’s performance and/or (2) allow the borrower tocarryforward unused capital expenditure amounts. The state contingent provision (similar to
performance covenants) reduces over- and under-investment concerns because it explicitly
conditions the amount of investments on the current performance of the borrower (e.g., EBITDA
or revenues). The carryforward provision allows the borrower to carry to future periods any
amounts not used in the current year, therefore, incentivizing managers not to over-invest when
they are performing poorly so that they will not be forced to under-invest if performance
improves. While the plain vanilla capital expenditure covenant mitigates certain over-investment

6

The borrower might still have incentives to renegotiate the contract if a good investment opportunity comes along.
The borrower could be interested in, for instance, increasing the amount of the borrowings or extending the maturityof the loan in order to finance the new investment. Moreover, as opposed to a contract that includes a capital covenant,the borrower will have more bargaining power to negotiate a more favorable amendment to the contract, which gives
it higher incentives to pursue the positive NPV project.

11

concerns by restricting the maximum amount of expenditures in a given year, tailored capital
expenditure covenants are more adequate in addressing investment concerns because they allow
the borrower to invest more (less) when the borrower’s performance is good (bad) and/or not tooverinvest in bad states by carrying forward unused capital expenditure amounts.
I do not expect a high likelihood of tailored capital expenditure covenants in shorter
maturities because they are costly to negotiate at loan inception (e.g., contracting parties have toagree on, for example, the state contingent variable or the percentage of the unused expendituresin a given year that can be carried forward) and less useful due to the lower likelihood ofinvestment conflicts. Based on these arguments, I state my second hypothesis in alternate form:
H2: Ceteris paribus, contracts with longer maturities are more (less) likely to include
tailored (plain vanilla) capital expenditure covenants than contracts with shorter
maturities.
3. Data
3.1. Sample
I start with Dealscan observations that I can link to Compustat using the Roberts
Dealscan–Compustat link (August 2012 vintage, see Chava and Roberts 2008). Following
previous research, I exclude contracts without covenant information from the analysis.7 This
leaves me with 19,855 deal packages issued between 1995 and 2012 that have at least one
financial covenant.8 I also require sufficient data for calculating loan maturity and control
variables. Furthermore, I exclude financial (SIC 6000-6999) and regulated firms (4900-4999)

7

Beatty et al. (2008) and Christensen and Nikolaev (2012) document that Dealscan sometimes underreports thenumber of covenants in deals and that deals with no reported covenants are potentially data errors. Accordingly, I
exclude contracts with no covenant information (rather than set their number to zero).
8
Loan or deal packages are sets of loan facilities from the same lead lender to the same borrower. For example, asingle loan package may include two separate facilities, a revolving line of credit, and a term loan. Because all facilities
in a loan package are subject to the same covenants, my analysis is at the package level.

12

consistent with prior research. This leaves a final sample of 11,046 deal packages of which 2,646
have a capital expenditure covenant. (Due to missing test and control variables, the number ofobservations reported in the tables differ.) Table 1 provides the details.
3.2. Plain vanilla versus tailored capital expenditure covenants
To determine whether capital expenditure covenants are tailored to deal with over- andunder-investment concerns, I manually match each of the 2,646 loan packages in my sample thathave a capital expenditure covenant to the corresponding loan contract from Edgar. Loan contracts
are usually attached to 8-K, 10-Q, or 10K fillings.9 I am able to match successfully 86 percent ofthese contracts leading to a sub-sample of 2,274 loan contracts with detailed information about thedesign of the capital expenditure covenant.10
Next, I read each contract in order to determine how the capital expenditure covenant isdesigned.11 I classify capital expenditure covenants into plain vanilla and tailored capital
expenditure covenants. Plain vanilla capital expenditure covenants are those that stipulate themaximum amount that the borrower can invest during each year of the contract without including
a state contingent and/or carryforward provision (as detailed below). The capital expenditure
restriction contained in the July 15, 1999 credit agreement for Celebrity Inc. illustrates a plain
vanilla capital expenditure covenant:Capital Expenditures. Allow Borrowers, in the aggregate, [not] to make capital
expenditures in any fiscal year in excess of $2,000,000.

9On some occasions, contracts are attached to S-1, S-3, or S-4 fillings.
Among the reasons for not being able to find detailed information about the expenditure covenant for 372 contracts
are: the contract has been redacted, the contract has a supplemental schedule that was not attached, or I could not findthe contract on Edgar.
11
Most contracts define capital expenditures as the sum of all expenditures capitalized for financial statement purposesin accordance with GAAP (whether payable in cash or other property or accrued as liability), including the capitalized
portion of capital leases.
1013Tailored capital expenditure covenants are those that include a state contingent provisionthat conditions the amount of allowable investments on the borrower’s performance and/or acarryforward provision that allows the borrower to rollover unused capital expenditure
amounts.12,13 The capital expenditure restriction contained in the May 5, 2008 credit agreement for
Apac Customer Services Inc. illustrates a state contingent provision:
Capital Expenditures. Contract for, purchase or make any expenditure or commitments for
Capital Expenditures in any fiscal year in an aggregate amount in excess of (a) $6,800,000
for the fiscal year ending on or about December 31, 2008 and (b) for each fiscal year
thereafter an amount not to exceed sixty-five percent (65%) of Borrower’s EBITDA for theprior fiscal year.
In addition, the capital expenditure restriction contained in the November 5, 1999 credit
agreement for SLEEPMASTER L.L.C. illustrates a carryforward provision:
Consolidated Capital Expenditures. The Parent will not, nor will it permit any Subsidiaryto permit Consolidated Capital Expenditures as of the end of any fiscal year of the Parent
to exceed $6,000,000 for all such persons in the aggregate during such fiscal year;
provided, however, that 50% of any amounts not utilized during any fiscal year may be
carried forward to the immediately following fiscal year only.
Table 2 provides descriptive statistics for this hand-collected sub-sample of 2,274 contracts
with detailed information about the design of the capital expenditure covenant. Panel A provides
the distribution by type of capital expenditure restriction. Fifty-one percent of the contracts areclassified as plain vanilla capital expenditure covenants, whereas 49 percent of the remaining
contracts have a tailored capital expenditure restriction. In terms of specific provisions, 11 percent

12

On some rare occasions, contracts classified as having a carryforward provision allow the borrower to spend inexcess of the maximum allowed amount in a given year by reducing permitted capital expenditures in the immediately
following year by the amount of such excess.
13
Sometimes capital expenditure covenants include other provisions that determine how permitted capital
expenditures will change if, for example, a permitted acquisition is consummated or in the event of a loss of PP&E.
Given that the link to mitigating investment inefficiencies is less clear, I do not incorporate those provisions whenclassifying capital expenditure covenants. That said, those provisions are predominantly present in covenantsclassified as tailored capital expenditure covenants.

14

have a state contingent provision and 45 percent a carryforward provision. As a result, about sevenpercent of the contracts contain both provisions.
Panel B provides descriptive statistics for the hand-collected state contingent provisions. I
find that 36 percent of the state contingent provisions are written on EBITDA or cash flow
numbers, 19 percent are written on the borrower’s debt-to-EBITDA ratio, 12 percent on excess
availability in the borrower’s credit line, and another 12 percent on revenues. Even fewer contracts
make investments contingent on the borrower’s liquidity, fixed charge ratio or net income. Last,
the other category contains variables such as the borrower’s credit rating or net worth.
Panel C provides descriptive statistics for the hand-collected carryforward provisions. I
find that the mean carryforward length is about one year, and that on average, 70 percent of theunused amounts in a given year can be carried forward.14
4. Empirical analysis
4.1. Econometric specification
To investigate the link between maturity and the type of covenants used in debt contracts,
I employ the following regression framework:15
𝐶𝑜𝑣𝑒𝑛𝑎𝑛𝑡 𝑇𝑦𝑝𝑒 = 𝛼𝑓 + 𝛼𝑐𝑟 + 𝛼𝑙 + 𝛼𝑦 + 𝛽1 𝐷𝑒𝑎𝑙 𝑀𝑎𝑡𝑢𝑟𝑖𝑡𝑦 + 𝛽2 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠 + 𝜗.

(1)Here, the outcome variable of interest is Covenant Type, which is equal to the number of
performance or income covenants (P-Covenants), the number of capital or balance sheet
covenants (C-Covenants), the ratio of the number of performance covenants to the sum of

14

In some cases, contracts stipulate the dollar amounts that can be carried forward. In those cases, I calculate
percentages relative to first year maximum allowed capital expenditures.
15
Consistent with the suggestion in Angrist and Pischke (2009), throughout the paper I use a linear probability model
as opposed to a non-linear limited dependent variable model. This allows for the easy interpretation of the coefficients
as well as the use of fixed effects in the model.

15performance and capital covenants (Covenant Ratio), a dummy variable for the existence of acapital expenditure covenant without a state contingent or carryforward provision (Plain Vanilla
Capex), or a dummy variable for capital expenditure covenants with a state contingent and/or
carryforward provision (Tailored Capex). 𝛼𝑓 is a firm fixed effect that controls for the borrower’s
type and reduces concerns of borrower-specific time-invariant omitted variables driving theresults. 𝛼𝑐𝑟 is a set of dummy variables for the borrower’s credit rating (e.g., AAA, AA+, etc.).
𝛼𝑙 is a set of controls that account for the purpose of the loan (e.g., LBO, takeover, or working
capital) and the types of facilities that are part of the loan (e.g., revolver, term loan). The
explanatory variable of interest is Deal Maturity, which, consistent with prior research, is equal
to the weighted average loan maturity in a loan deal. 16 I also include a set of controls that aredescribed in more detail below.17 I winsorize all continuous variables at the 1 percent and 99
percent levels to limit the influence of outliers. Finally, I cluster standard errors at the firm level.
4.2. Control variables
I include controls for a number of firm characteristics that might affect covenant choice(e.g., Demerjian 2011; Christensen and Nikolaev 2012). Size is calculated as the natural
logarithm of total assets. Leverage is defined as long-term debt plus debt in current liabilities
divided by book assets. Market-to-Book is the ratio of the market value of equity plus the bookvalue of liabilities to the book value of assets. Profitability is measured as a firm’s pre-tax cash
flow from operations over total assets. Cash Flow Volatility is equal to the volatility of cash flows

16

For example, if the loan deal includes a $5 million two-year revolver and a $10 million five-year term loan, then
Deal Maturity is equal to 4 years (=2 years * 5/15 + 5 years *10/15).
17
To ensure that I only use accounting information that is publicly available at the time of a loan, I employ thefollowing procedure: for those deal packages made in calendar year t, if the deal activation date is four months ormore than the fiscal year ending month in calendar year t, I use the data of that fiscal year. If the deal activation dateis less than four months after the fiscal year ending month, I use the data from the fiscal year ending in calendar year
t−1.

16

scaled by mean non-cash assets over the previous five years. Not Rated is an additional proxy for
default risk. It is a dummy equal to one if the borrower has no S&P long-term credit rating, zerootherwise. Finally, I control for the number of previous deals that the borrower has closed withmembers of the syndicated loan market in the past; firms accessing the syndicated loan market
multiple times usually need less monitoring (Sufi 2007), which might affect the type of covenants
used in the debt contract. # Previous Loans is calculated at the Dealscan level.
I also include controls for a number of loan characteristics that could affect covenantchoice. # Lenders is equal to the number of banks participating in the lending syndicate. #Facilities is equal to the number of different tranches (e.g., credit line, term loan, etc.) included
in a particular loan deal. Deal Amount is the size of the loan deal and is measured in millions of
USD. Last, I control for macroeconomic conditions, which can affect debt contracting. Credit
Spread is the difference between the AAA corporate bond yield and the BAA corporate bondyield. Term Spread is the difference between the 10-year Treasury yield and the 2-year Treasury
yield. All variables used in this study are described in the Appendix.
4.3. Descriptive statistics
Table 3 presents descriptive statistics for the full sample. The average loan deal maturity
is 44 months. However, there is significant variation as loans in the lower quartile of the Deal
Maturity distribution have maturities of 31 months or less, whereas those in the highest quartile
have maturities of 60 months or more. The values for P-Covenants, C-Covenants, and Covenant
Ratio are 1.59, 0.79, and 0.67, respectively. They are similar to the values reported by Christensen
and Nikolaev (2012). The mean of Capex Covenant is 0.24, suggesting that during the sample
period, on average, 24 percent of all contracts include capital expenditure covenants. When I
exclude from the sample contracts without detailed capital expenditure information, I find that17

11 percent of the contracts have a plain vanilla capital expenditure covenant and about 10 percent
a tailored capital expenditure covenant.
To provide a more detailed intuition about how the covenant structure varies withmaturity, Table 4 presents mean covenant values per maturity quartile. Contracts in the bottom
quartile (Quartile 1 Maturity) have an average maturity of about 1.4 years, whereas contracts inthe top quartile (Quartile 4 Maturity) have an average maturity of about six years. The tableshows that the values for P-Covenants (C-Covenants) monotonically increase (decrease) withmaturity. Similarly, the mean values for Tailored Capex (Plain Vanilla Capex) increase(decrease) with maturity. Overall, Table 4 suggests that there is significant heterogeneity in thecomposition of covenant packages across maturity quartiles.
4.4. Empirical results – P-Covenants versus C-Covenants
Figure 1a graphically presents the univariate relationship between accounting-based
covenants and loan maturity from Table 4. It clearly shows an opposite relationship with loan
maturity for capital- and performance-based covenants. As the contract maturity lengthens,
performance-based covenants become more common while capital-based covenants become lesscommon. This stark pattern highlights the differing roles of these two types of covenants.
Table 5 reports the multivariate results for how maturity is related to the inclusion of
accounting-based covenants. The first column presents results when the number of covenants (#Covenants) is the dependent variable. I find no relation between maturity and the number ofcovenants.18 However, columns 2 to 4 suggest that the composition of the covenant package
significantly varies with maturity. For instance, in column 2, I find that the coefficient on Deal

18

This result contrasts a bit with research in the public bond market. Billett, King, and Mauer (2007) find a positive
relation between debt maturity and an aggregate measure of bond-holder covenant protection.

18

Maturity is positive (0.003) and statistically significant (t-stat 3.76), suggesting that maturity is
positively related to the inclusion of P-Covenants. In contrast, in column 3, I find that thecoefficient on Deal Maturity is negative (-0.003) and statistically significant (t-stat -3.99),
suggesting that maturity is negatively related to the inclusion of C-Covenants. Finally, column 4further confirms that contracts with longer maturities have a higher Covenant Ratio, suggestingthat these contracts contain more P-Covenants relative to the sum of P-Covenants and CCovenants. These findings suggest that as maturity increases and it is more likely that a newinvestment opportunity comes along, contracting parties settle on performance covenants that
allocate decision rights in a state contingent manner, thereby reducing concerns of future overand under-investment problems.
In this context, it is worth mentioning that the economic effect of maturity on any specificcovenant is relatively modest. For example, a one standard deviation increase in loan maturity is
associated with an increase in P-Covenants of about 4% relative to the sample mean. This is inpart explained by the use of a firm-fixed effects specification that eliminates a substantial amountof variation. That said, the effect of loan maturity becomes more material if we consider the effecton the whole covenant package (i.e., P-Covenants, C-Covenants, plain vanilla capex, tailored
capex, and dynamic capital expenditure thresholds).
4.5. Empirical results – Plain vanilla versus tailored capital expenditure covenants
Figure 1b graphically presents the univariate relationship between capital expenditurecovenant types and loan maturity from Table 4. It clearly illustrates an opposite relationship withloan maturity for plain vanilla and tailored capital expenditure covenants. As the contract
maturity lengthens, tailored capital expenditure covenants become more common while plain

19vanilla capital expenditure covenants become less common. This stark pattern highlights thediffering roles of these two types of expenditure covenants.
Table 6 reports the multivariate results for how deal maturity is related to the type of
capital expenditure covenant. The first column presents results when Capex Covenant, a dummy
variable for contracts with a capital expenditure covenant of any type, is the dependent variable.
I find that the coefficient on Deal Maturity is negative but not statistically significant, suggestingthat contracts with longer maturities are (weakly) less likely to have a capital expenditurecovenant in general. In columns 2 and 3, I investigate whether maturity is related to the specificdesign or type of capital expenditure covenant. In column 2, I find that maturity is negatively
related to the inclusion of a plain vanilla capital expenditure covenant. The coefficient on Deal
Maturity is negative (-0.001) and statistically significant (t-stat -3.67). In contrast, in column 3,
I find that contracts with longer maturities are more likely to include a tailored capital expenditurecovenant. The coefficient on Deal Maturity is positive (0.001) and statistically significant (t-stat2.60).
These findings suggest, that when loan maturity is longer and it is more likely that a newinvestment opportunity comes along, contracting parties settle on a tailored capital expenditurecovenant that reduce concerns of future over- and under-investment problems.
4.6. Within firm-year specification
A concern with the firm-fixed effects specification just presented is that I cannot rule outthat firm-specific, time-varying omitted variables might be driving my results. To mitigate thisconcern, I exploit the fact that some firms issue multiple loans in a given year. For example,
TRW Automotive issued two loans in 2003, one in February and the other one in July. This
allows me to investigate how loan maturity relates to covenant structure for loans issued by the20same firm and in the same year. For omitted factors to create spurious results in this within firmyear specification, they would have to be correlated with the specific timing of the issuance ofthe loans during that particular year. Thus, the within firm-year specification should be able toseparate covenant structure effects related to maturity from effects that are unrelated to maturity.
To maximize my sample for this test, I conduct it at the Dealscan level without requiringthat data be available on Compustat. I only keep firms that issue two or more loans in a given
year. Moreover, I hand-collect information about the design of the capital expenditure covenant
for the contracts that were not part of my main sample. Unfortunately, however, I can only findcontracts with sufficient information for 73 percent of the sample with capital expenditurecovenants because many loans are issued by private firms. This somewhat reduces the power ofmy test. Finally, I rank deal maturity into quartiles and use it as my explanatory variable. 19
Table 7, Panel A presents the results when Covenant Ratio is the dependent variable.
Column 1 presents results without controls and suggests a positive relation between loan maturity
and Covenant Ratio. Column 2 presents a similar relation when including controls for the numberof lenders, the number of facilities, and deal amount. Column 3, shows that results hold when
also including fixed effects for loan purpose and loan type. This evidence suggests that contracts
with the same borrower written in the same year rely relatively more on performance covenants
when maturity is longer.
Panel B presents the results when Plain Vanilla Capex is the dependent variable. Column
1 presents results without controls and suggests a negative relation between loan maturity andPlain Vanilla Capex. Column 2 presents a similar relation when including controls for thenumber of lenders, the number of facilities, and deal amount. Column 3 shows that results hold

19

Results using Deal Maturity as a continuous measure are somewhat weaker.

21when also including fixed effects for loan purpose and loan type. This evidence suggests that
contracts with the same borrower written in the same year rely relatively less on plain vanilla
capital expenditures when maturity is longer.
Last, Panel C presents the results when Tailored Capex is the dependent variable. Column
1 presents results without controls and suggests a positive relation between loan maturity andTailored Capex. However, in columns 2 and 3, when including additional controls, this relation
becomes insignificant. As a result, there is only weak evidence for a positive relation between
loan maturity and tailored capital expenditures when using the more demanding within firm-year
specification.
5. Additional tests
5.1. Cross-sectional tests based on propensity to face unanticipated investment decisions
To further strengthen the argument that contracting parties select covenants with the
purpose of reducing future investment conflicts, I conduct cross-sectional tests based on the
borrower’s propensity to face unanticipated investment decisions after loan initiation. In particular,
I estimate the following model:
𝐶𝑜𝑣𝑒𝑛𝑎𝑛𝑡 𝑇𝑦𝑝𝑒 = 𝛼𝑖𝑛𝑑 + 𝛼𝑐𝑟 + 𝛼𝑙 + 𝛼𝑦 + 𝛽1 𝐷𝑒𝑎𝑙 𝑀𝑎𝑡𝑢𝑟𝑖𝑡𝑦 + 𝛽2 𝐷𝑒𝑎𝑙 𝑀𝑎𝑡𝑢𝑟𝑖𝑡𝑦 ∗𝑈𝑛𝑎𝑛𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑒𝑑 𝐼𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 + 𝛽3 𝑈𝑛𝑎𝑛𝑡𝑖𝑐𝑖𝑝𝑎𝑡𝑒𝑑 𝐼𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 + 𝛽4 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠 + 𝜗.

(2)Here, the outcome variable of interest is Covenant Type, which is either equal to the ratioof the number of performance covenants to the sum of performance and capital covenants(Covenant Ratio) or a dummy variable for capital expenditure covenants with a state contingent
and/or carryforward provision (Tailored Capex). My prediction is that 𝛽2 > 0, meaning that forloans issued to borrowers with higher propensity to face unexpected investment decisions, theassociation between loan maturity and performance or tailored capital expenditure covenants
22should become stronger. I follow prior research (e.g., Billet, King, and Mauer 2007) and use themarket-to-book ratio, investments in research and development activities, and sales growth asproxies for a higher likelihood of future investment considerations (i.e., Unanticipated
Investment). In particular, I classify borrowers in the following way. First, I expect that firms withhigher market-to-book ratios have higher growth opportunities and, therefore, are more likely toface unanticipated investment decisions after loan initiation. Firms with a market-to-book ratio
above 2.5 are classified as High Market-to-Book, zero otherwise. 20
Second, I expect that when the borrower engages in research and development activities
there is more uncertainty about the profitability and time-horizon of future investments. In thosecases, contracting parties are more likely to disagree about the assessment of future investment
opportunities, and the state contingent allocation of control rights over investment decisions should
be more relevant. Firms with research and development investments above five percent of total
assets are classified as R&D Intensive, zero otherwise. Finally, I also expect that firms with highsales growth are more likely to face unanticipated investment decisions. Firms with sales growth(relative to the prior year’s sales) above 15 percent are classified as High Sales Growth, zerootherwise. Fixed effects and control variables are the same as the ones used in equation (1). The
exception being that in equation (2), I use industry fixed effects instead of firm fixed effects. Thisbecause the use of firm fixed effects renders many of the variables insignificant, essentiallypurging all the cross-sectional variation.
Table 8, Panel A presents the results when using High Market-to-Book, my first proxy forborrowers more likely to face unexpected investment decisions. In column 1, the dependent
variable is Covenant Ratio. I find that the coefficient on the interaction term Deal Maturity x High20

My results are qualitatively similar if I use alternative thresholds for High Market-Book, R&D Intensive, or HighSales Growth (as defined below).

23

Market-to-Book is positive (0.001) and significant (t-stat 2.35), suggesting that when contracts
have longer maturities and the borrower is more likely to face investment decisions, contracts rely
relatively more on performance covenants. In column 2, the dependent variable is Tailored Capex.
I find that the coefficient on the interaction term Deal Maturity x High Market-to-Book is positive(0.001) and significant (t-stat 1.83), suggesting that when contracts have longer maturities and theborrower is more likely to face unexpected investment decisions, contracts rely relatively more on
tailored capex covenants that better deal with investment conflicts. In addition, in Table 8, Panels
B and C, I find similar results when using R&D Intensive and High Sales Growth as the proxies
for uncertain and/or unexpected investment decisions, respectively. The exception being, Panel C,column 2 where the coefficient on Deal Maturity x High Sales Growth is statistically insignificant.
A point worth discussing is that while the coefficient on the interaction term between deal
maturity and unexpected investment decisions is positive, the main effect on unexpected
investment decisions is negative. One interpretation for this result, is that in the case of borrowers
with, for example, growth opportunities, contracting parties see little need for contingent allocation
over future investment decisions when maturity is short. For example, in the case of Panel A
column 2, the coefficients of 0.001 on Deal Maturity x High Market-to-Book and -0.025 on HighMarket-to-Book, suggests that only for maturities in excess of 25 months, high growth firms rely
more on tailored capex covenants than non-high growth firms.
5.2. Incentive alignment and loan maturity
Next, I explore the role of incentive alignment on the choice of covenants. In firms thathave a small fraction of debt in their capital structures, the incentives of the managers anddebtholders are generally aligned and creditors are less concerned about wealth expropriation. On
the other hand, shareholders-managers are likely more reluctant to give stronger control rights to24creditors; this potentially allows the creditors to extract rents if covenants are tightened. In thisinstance, the solution would be to use covenants that ensure incentive alignment by requiring aminimum level of capital to be maintained by the firm through the use of capital covenants. To
test this prediction, I estimate the following model:
𝐶𝑜𝑣𝑒𝑛𝑎𝑛𝑡 𝑇𝑦𝑝𝑒 = 𝛼𝑖𝑛𝑑 + 𝛼𝑐𝑟 + 𝛼𝑙 + 𝛼𝑦 + 𝛽1 𝐻𝑖𝑔ℎ 𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒 𝐴𝑙𝑖𝑔𝑛𝑚𝑒𝑛𝑡 +𝛽2 𝐷𝑒𝑎𝑙 𝑀𝑎𝑡𝑢𝑟𝑖𝑡𝑦 ∗ 𝐻𝑖𝑔ℎ 𝐼𝑛𝑐𝑒𝑛𝑡𝑖𝑣𝑒 𝐴𝑙𝑖𝑔𝑛𝑚𝑒𝑛𝑡 + 𝛽3 𝐷𝑒𝑎𝑙 𝑀𝑎𝑡𝑢𝑟𝑖𝑡𝑦 + 𝛽4 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠 + 𝜗. (3)Here, the outcome variable of interest is Covenant Type, which is either equal to Covenant
Ratio or Tailored Capex as defined before. My prediction is that 𝛽1 < 0, meaning that for loans
issued to borrowers with high incentive alignment, there is less need to contract on performancecovenants or tailored capital expenditure covenants. However, this relationship should be
attenuated as the likelihood of a change in incentive alignment or capital structure increases withmaturity (i.e., 𝛽2 > 0). To deal with a potential deterioration in incentive alignment over time,
contracting parties should increasingly rely on performance covenants or tailored capital
expenditure covenants. I classify borrowers with a leverage ratio in the bottom quartile of thesample as High Incentive Alignment, zero otherwise. Table 9, columns 1 and 2 present the results
when Covenant Ratio and Tailored Capex are the dependent variables, respectively. In both cases,
results are consistent with my predictions.
5.3. Robustness tests
5.3.1. Sample restricted to contracts with a capital expenditure covenant
I start by restricting the sample to only those contracts that have a capital expenditurecovenant. This sample restriction reduces the concern that my previous results might somehow be
driven by the inclusion of contracts that do not have a capital expenditure covenant. Moreover, it

25allows me to conduct tests related to variation in dynamic capital expenditure thresholds in debt
contracts.
Table 10, Panel A presents descriptive statistics for how different covenant values vary bymaturity quartile for this subsample. Similar to Table 4, I find that the values for P-Covenants (CCovenants) monotonically increase (decrease) as contracts have longer maturities. Similarly, themean values for Tailored Capex (Plain Vanilla Capex) increase (decrease) with maturity. For
instance, in quartile 1 (short maturity) 76 percent of the contracts have a Plain Vanilla Capex,
whereas 24 percent of the contracts have a Tailored Capex. This contrasts with the values inquartile 4 (long maturity) where only 19 percent of the contracts have a Plain Vanilla Capex but
81 percent of the contracts have a Tailored Capex. The table also shows that contracts with longer
maturities include more frequently a performance pricing provision.
Panel A also provides evidence about whether the thresholds for maximum allowable
capital expenditures vary over time. Similar to Li, Vasvari, and Wittenberg Moerman (2016), who
document variation in earnings-based covenant thresholds, I find significant variation in
expenditure covenant thresholds. In particular, capital expenditure thresholds can be increasing(Loosening Capex Threshold), constant (Fixed Capex Threshold) or decreasing (Tightening CapexThreshold) over time. The capital expenditure restriction contained in the December 9, 2010 credit
agreement for Morton’s of Chicago Inc. illustrates a capital expenditure covenant with anincreasing threshold (Loosening Capex Threshold) and a carryforward provision:
Maximum Consolidated Capital Expenditures. Holdings shall not, and shall not permit its
Subsidiaries to, make or incur Consolidated Capital Expenditures, in any Fiscal Year
indicated below … in excess of the corresponding amount set forth below opposite such
Fiscal Year; provided, such amount for any Fiscal Year shall be increased by an amountequal to the excess, if any, of such amount for the previous Fiscal Year … over the actual
amount of Consolidated Capital Expenditures for such previous Fiscal Year:26

Fiscal Year
January 2, 2011
January 1, 2012
December 30, 2012
December 29, 2013
December 28, 2014
December 27, 2015

Capital Expenditures$9,000,000.00$14,000,000.00$19,000,000.00$24,000,000.00$29,000,000.00$31,000,000.00

I find that loosening capital expenditure thresholds are more frequent in contracts withlonger maturities although there is also some weaker evidence that this might be true for tightening
capital expenditure thresholds.21 In contrast, I find that constant capital expenditure thresholds are
more prevalent in contracts with shorter maturities. Overall, Panel A suggests that even in thesubsample restricted to contracts with a capital expenditure restriction, there is significant
heterogeneity in the composition of covenant packages across maturity quartiles.
In Panels B and C, I present multivariate regression results. Because the sample is relatively
small and there are fewer observations per firm (relative to the full sample), in Panel B, I start bypresenting results using equation 1 but by excluding firm-fixed effects (and including industry
fixed effects). Consistent with my previous results, I find that contracts with longer maturities are
positively related to Covenant Ratio and Tailored Capex but negatively related to Plain Vanilla
Capex. In addition, columns 4 and 5 suggest that both Capex State Contingent Provision and Capex
Carryforward Provision are more prevalent in contracts with longer maturities. Finally, in column
6, I find that maturity is positively related to Loosening Capex Threshold. This result is consistent
with the prediction in Garleanu and Zwiebel (2009) that in the presence of greater agency concerns(as in the case of longer maturities), contracts will be tighter at loan inception and subsequently
loosen up.

21

For the purpose of the threshold analysis, I exclude contracts with a state contingent provision or when the trend isunclear. In the case of the state contingent provision, the trend depends on the borrower’s future performance or
financial condition.

27

In Panel C, I present results using the same firm-fixed effects specification described inequation 1. The results are similar to Panel B except that the coefficients in columns 1 (Covenant
Ratio), 4 (Capex State Contingent Provision) and 6 (Loosening Capex Threshold) are no longer
statistically significant. Collectively, Table 8 further supports the notion that variation in loan
maturity affects the choice of covenants.
5.3.2. Excluding contracts with shorter maturities
One concern with the analysis is that for short-term contracts (contracts maturing in ayear or less), there is little scope to tailor capital expenditure covenants and make them contingent
on cumulative performance. Short maturity means that there is little or no room to use
performance carryforward provisions. Similarly, for short-term debt, there is little value incontrol allocations contingent on performance because creditors gain unconditional control once
the loan is due. To rule out a potentially mechanical aspect to some of the results, in untabulated
tests, I show that the results are not sensitive to the exclusion of short-term debt.
5.3.3. Covenant strictness
My analysis implicitly assumes that covenants are set with a similar degree of strictness atloan initiation. However, contracting parties could set covenants tighter giving lenders more
control rights or looser giving borrowers more flexibility. To measure the link between loan
maturity and the covenant strictness of accounting-based covenants, I use the measures developed
by Demerjian and Owens (2016).22 Table 11, column 1 presents the results. I find virtually no
relation between maturity and covenant strictness. Moreover, in columns 2 and 3, I use thecovenant strictness of P-Covenants (P-Covenant Strictness) and C-Covenants (C-Covenant

22

I downloaded the covenant strictness estimates from Peter Demerjian’s website (faculty.washington.edu/pdemerj).

28

Strictness), respectively. Again, I find no significant relationship. Overall, this result suggests that
contracting parties primarily rely on the choice of covenants to allocate control rights in contracts
with longer maturities.
6. Conclusion
I study how debt agreements allocate control rights over future investment decisions in thecontext of prior theory, which suggests that conflicts of interest between borrowers and lenders
increase with debt maturity because it is more likely than an investment opportunity will arise
before the debt is repaid. Consistent with income statement-based (balance sheet-based) covenants
being more (less) efficient in allocating control rights over future investment decisions, I find thatdebt contracts with longer maturities have more (fewer) performance (capital) covenants.
Moreover, using a novel dataset with detailed information about the design of capital expenditurecovenants, I find that debt contracts with longer maturities mitigate investment inefficiencies by
including tailored capital expenditure covenants that (1) allocate control rights over investments
contingent on the borrower’s performance (e.g., EBITDA or revenues), (2) allow the borrower tocarryforward unused capital expenditure amounts to future periods, and/or (3) include dynamic
capital expenditure thresholds that are tighter at loan inception but subsequently loosen up.
Additionally, I find that the association between loan maturity and the inclusion of performanceand tailored capital expenditure covenants becomes stronger when the borrower has a higher
propensity to face unexpected investment decisions. Collectively, these results imply that
contracting parties select different accounting-based and capital expenditure covenants at contract
initiation as investment conflicts vary with loan maturity.
This study makes two primary contributions. First, this study contributes to the literatureby documenting how debt agreements allocate control rights over future investment decisions. I

29

provide evidence that contracting parties select different accounting-based and capital expenditurecovenants at contract initiation as investment conflicts vary with loan maturity. I find that for
longer maturities, debt contracts have more covenants that are directly linked to the current
performance of the borrower and have tailored capital expenditure covenants. As a result, myfindings address the call in Skinner (2011) and Christensen, Nikolaev, and Wittenberg-Moerman(2016) to understand better the channels through which covenants facilitate contracting.
Second, this study also adds to prior research that documents that income statement andbalance sheet variables are used for different purposes in debt contracts (Demerjian, 2011;
Christensen and Nikolaev 2012; Saavedra 2017). In addition, to explore a new research question,
I provide detailed evidence that accounting variables are also used in the design of capital
expenditure covenants. Prior research on this restriction did not explore the extent to which
accounting metrics are used to customize the capital expenditure covenant (Nini, Smith, and Sufi2009). I find that most state contingent provisions in capital expenditure restrictions are conditional
on income statement or performance variables. These findings further shed light on ways in which
accounting improves contracting efficiency (Watts and Zimmerman 1986; Christensen et. al.
2016).

30

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Appendix: Variable Definitions
Covenants and Other Terms# Covenants

The total number of covenants in a loan contract.

P-Covenants

Number of performance-based covenants is defined as the sum of(1) the cash interest coverage ratio, (2) the debt service coverage
ratio, (3) the level of EBITDA, (4) the fixed-charge coverage ratio,(5) the interest coverage ratio, (6) the ratio of debt to EBITDA, and(7) the ratio of senior debt to EBITDA.

C-Covenants

Number of capital-based covenants is defined as the sum of (1) thequick ratio, (2) the current ratio, (3) the debt-to-equity ratio, (4) the
loan-to-value ratio, (5) the ratio of debt to tangible net worth ratio,(6) the leverage ratio, (7) the senior leverage ratio, and (8) the net
worth requirement.

Covenant Ratio

The fraction of covenants that are P-Covenants calculated as PCovenants / (P-Covenants + C-Covenants).

Capex Covenant:Dummy variable equal to one if the contract includes a capital
expenditure covenant, zero otherwise.

Plain Vanilla Capex:

Dummy variable equal to one if the capex covenant has no carryforward provision and/or state contingent provision, zero otherwise.

Tailored Capex:

Dummy variable equal to one if the capex covenant has a carryforward provision and/or a state contingent provision, zerootherwise.

State Contingent Capex:

Dummy variable equal to one if the capital expenditures are linked
to the current performance or financial condition of the borrower,
zero otherwise.

Capex Carryfor. Provision: Dummy variable equal to one if the capital expenditures can be
carried forward, zero otherwise.
Loosening Capex Thresh.

Dummy variable equal to one if capital expenditure thresholds are
increasing over time, zero otherwise.

Fixed Capex Thresh.

Dummy variable equal to one if capital expenditure thresholds areconstant over time, zero otherwise.

Tightening Capex Thresh.

Dummy variable equal to one if capital expenditure thresholds are
decreasing over time, zero otherwise.
34

Loan Maturity
Deal Maturity:

The weighted maturity of all facilities in the loan, which is measured
in months.

Controls
Size:

The natural logarithm of total assets.

Leverage:

Measured as long-term debt plus debt in current liabilities divided
by book assets.

Market-to-book:

The book value of total assets minus the book value of equity plus
the market value of equity as the numerator of the ratio and the bookvalue of assets as the denominator.

Profitability:

The firm’s pre-tax cash flow from operations over total assets.

Cash Flow Volatility:

The volatility of pre-tax cash flows scaled by mean non-cash assets
over the previous five years.

Not Rated:

Dummy equal to one if the borrower has no long-term S&P credit
rating, zero otherwise.

#Lenders:

Number of banks participating in the lending syndicate.

#Previous Deals:

Equal to the number of previous loans issued by the borrower.

#Facilities:

The number of different facilities included in the loan deal.

Deal Amount:

The deal amount measured in millions of dollars.

Cross-sectional Variables
High Market-to-Book:

Dummy equal to one if the borrower has a market-to-book ratio
above 2.5, zero otherwise.

R&D Intensive:

Dummy equal to one if the borrower has research and development
investments above five percent of total assets, zero otherwise.

High Sales Growth:

Dummy equal to one if the borrower has sales growth (relative tothe prior year’s sales) above 15 percent, zero otherwise.

High Incentive Alignment:

Dummy equal to one if the borrower has a leverage ratio in thebottom quartile of the sample, zero otherwise.
35

Figure 1
Covenant Types by Maturity Quartiles
Figure 1A: Mean Values for Accounting-based Covenants
P-Covenants

C-Covenants

2.50

2.00

1.50

1.00

0.50

0.00
Quartile 1
Short Maturity

Quartile 2

Quartile 3

Quartile 4Long Maturity

Figure 1B: Mean Values for Capital Expenditure Covenant Types
Plain Vanilla Capex

Tailored Capex

Quartile 2

Quartile 3

0.30
0.25
0.20
0.15
0.10
0.05
0.00
Quartile 1
Short Maturity

Quartile 4Long Maturity

Figure 1. The table presents graphical evidence about how accounting-based and capital expenditure covenant types
vary across deal maturity quartiles. Following previous research, I exclude financial firms (SIC code 6000-6999) andutilities (SIC code 4900-4999). I exclude firm-years with missing values for control variables. All variables aredescribed in the appendix.

36

Table 1: Sample Selection

Loan Packages with non-missing covenants between 1995 and 2012

19,855

Excluding loan packages with missing deal maturity and control variables-7,051

Excluding financial firms (SIC code 6000-6999) and utilities (SIC code 4900-4999)-1,758Full Sample

11,046

Contracts with Capex Covenant

2,646

Contracts with Info about design of Capex Covenant

2,274

Table 1. The table presents the sample selection.

37

Table 2: Descriptive Statistics Design of Capital Expenditure Covenant
Panel A: Distribution by Capital Expenditure Covenant Type

Variable
Plain Vanilla Capex
Tailored Capex
Capex State Contingent Provision
Capex Carryforward Provision

N
2,274
2,274
2,274
2,274

Mean
0.51
0.49
0.11
0.45

Panel B: Variables used in State Contingent Provision

State Contingent Variable
EBITDA/Cash Flows
Debt-to-EBITDA
Excess Availability
Revenues
Liquidity
Fixed Charge Ratio
Net Income
Other

N
250
250
250
250
250
250
250
250

Percentage
36%
19%
12%
12%
4%
4%
3%
9%

Panel C: Features Carryforward Provision

FeatureLength of Carryforward (in years)
Max. % of unused capex that can be carried forward

N
1,017
1,017

Mean
1.07
0.70

Table 2. The table presents descriptive statistics for the hand-collected subsample of 2,274 contracts with detailed
information about the design of the capital expenditure covenant. Panel A presents the distribution by capital
expenditure covenant type. Panel B describes the variables used in the state contingent capital expenditure provision.
Panel C provides details about the structure of the carryforward provision in capital expenditure covenants.

38

Table 3: Descriptive Statistics
Variable
Deal Maturity (in months)# Covenants
P-Covenants
C-Covenants
Covenant Ratio
Capex Covenant
Plain Vanilla Capex
Tailored Capex
Capex State Contingent Provision
Capex Carryforward Provision
Leverage
Size
Market to Book
Profitability
Cash Flow Volatility
Not Rated# Lenders# Previous Deals# Facilities
Deal Amount (in millions)N
11,046
11,046
11,046
11,046
10,933
11,048
10,674
10,674
10,674
10,674
11,046
11,046
11,046
11,046
11,046
11,046
11,046
11,046
11,046
11,046

Mean
44.09
2.63
1.59
0.79
0.67
0.24
0.11
0.10
0.02
0.10
0.28
6.42
1.71
0.10
0.07
0.58
8.15
4.91
2.79
404.61

Median
44.39
3.00
2.00
1.00
0.67
0.00
0.00
0.00
0.00
0.00
0.26
6.41
1.42
0.10
0.04
1.00
6.00
4.00
1.00
160.00

Std Dev
20.12
1.13
0.96
0.85
0.35
0.43
0.31
0.31
0.15
0.29
0.21
1.76
0.97
0.10
0.09
0.49
8.31
4.35
3.29
664.42

25th Pctl
31.00
2.00
1.00
0.00
0.50
0.00
0.00
0.00
0.00
0.00
0.12
5.18
1.11
0.05
0.02
0.00
2.00
2.00
1.00
50.00

75th Pctl
60.00
3.00
2.00
1.00
1.00
0.00
0.00
0.00
0.00
0.00
0.40
7.61
1.95
0.16
0.08
1.00
11.00
7.00
4.00
450.00

Table 3. The table reports descriptive statistics for the variables used in the sample. Following previous research, I
exclude financial firms (SIC code 6000-6999) and utilities (SIC code 4900-4999). I exclude firm-years with missing
values for control variables. All variables are described in the appendix. All continuous variables are winsorized at
the 1% level.

39

Table 4: Distribution of Covenants by Maturity Quartiles

Quartile 1
Maturity

Quartile 2
Maturity

Quartile 3
Maturity

Quartile 4
Maturity

Mean

Mean

Mean

Mean

Deal Maturity (months)

17.15

36.74

56.70

73.38

# Covenants

2.46

2.77

2.50

3.01

P-Covenants

1.17

1.57

1.67

2.17

C-Covenants

1.08

0.92

0.63

0.48

Covenant Ratio

0.52

0.64

0.74

0.83

Capex Covenant

0.22

0.28

0.19

0.35

Plain Vanilla Capex

0.14

0.17

0.06

0.06

Tailored Capex

0.04

0.09

0.11

0.24

Capex State Contingent Provision

0.01

0.02

0.03

0.06

Capex Carryforward Provision

0.04

0.08

0.10

0.23

Table 4. The table presents descriptive statistics about covenant structure across deal maturity quartiles. Following
previous research, I exclude financial firms (SIC code 6000-6999) and utilities (SIC code 4900-4999). I exclude firmyears with missing values for control variables. All variables are described in the appendix. All continuous variables
are winsorized at the 1% level.

40

Table 5: Maturity and Accounting-Based Covenants

Dependent Variable =Deal Maturity
Leverage
Size
Market-to-book
Profitability
Cash Flow Volatility
Not Rated# Lenders# Previous Deals# Facilities
Log (Deal Amount)
Fixed Effects
Firm
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year
N
R-Squared# Covenants

P-Covenants

C-Covenants

Covenant
Ratio

(1)

(2)

(3)

(4)

0.000
(0.26)
0.114(0.85)-0.034(-0.79)-0.040(-1.57)
0.039(0.16)-0.204(-0.85)0.086(0.86)
0.002(0.80)
0.001(0.08)
0.009(1.44)
0.018

0.003***(3.76)
0.260**(2.35)-0.007(-0.19)-0.029(-1.44)0.263(1.47)-0.042(-0.21)
0.055(0.70)
0.004**(2.21)-0.013(-1.24)0.005(1.04)
0.085***-0.003***(-3.99)-0.313***(-3.87)0.009(0.36)
0.020(1.24)-0.013(-0.09)-0.123(-0.80)-0.021(-0.33)-0.002(-1.15)0.019**(2.31)
0.004(1.11)-0.060***0.001***(3.70)
0.140***(4.26)-0.029***(-2.67)-0.008(-1.27)0.024(0.43)
0.030(0.51)-0.005(-0.21)0.001(1.33)-0.004(-1.08)-0.001(-0.54)0.034***(0.65)(3.46)(-3.10)(4.48)

Yes
Yes
Yes
Yes
Yes
Yes
11,046

Yes
Yes
Yes
Yes
Yes
Yes
11,046

Yes
Yes
Yes
Yes
Yes
Yes
11,046

Yes
Yes
Yes
Yes
Yes
Yes
10,933

0.674

0.731

0.763

0.794

Table 5. The table investigates whether deal maturity affects the inclusion of accounting-based covenants in debt
contracts. Following previous research, I exclude financial firms (SIC code 6000-6999) and utilities (SIC code 49004999). I exclude firm-years with missing values for control variables. All variables are described in the appendix. All
continuous variables are winsorized at the 1% level. ***, **, and * denote significance at the 1%, 5%, and 10% levels,
two-tailed, respectively.

41

Table 6: Maturity and Capital Expenditure Covenant Types
Capex
Covenant

Plain Vanilla
Capex

Tailored Capex

(1)

(2)

(3)

-0.001(-1.62)0.162***(2.93)-0.040**(-2.51)-0.030***(-3.11)-0.192**(-2.03)-0.033(-0.34)0.054(1.41)-0.001(-0.59)-0.004(-0.92)-0.002(-0.72)-0.005-0.001***(-3.67)
0.098**(2.23)-0.020*(-1.65)-0.021***(-2.59)0.036(0.44)-0.009(-0.11)0.017(0.66)-0.000(-0.26)-0.004(-1.33)-0.001(-0.30)-0.020**0.001***(2.60)
0.060(1.27)-0.022*(-1.79)-0.008(-1.13)-0.196***(-2.65)-0.004(-0.06)0.036(1.07)-0.000(-0.06)-0.001(-0.33)0.000(0.18)
0.016*(-0.46)(-2.44)(1.84)

Fixed Effects
Firm
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year
N

Yes
Yes
Yes
Yes
Yes
Yes
11,046

Yes
Yes
Yes
Yes
Yes
Yes
10,674

Yes
Yes
Yes
Yes
Yes
Yes
10,674

R-Squared

0.652

0.609

0.570

Dependent Variable =Deal Maturity
Leverage
Size
Market-to-book
Profitability
Cash Flow Volatility
Not Rated# Lenders# Previous Deals# Facilities
Log (Deal Amount)

Table 6. The table investigates whether deal maturity affects the type of capital expenditure covenant included in debt
contracts. Following previous research, I exclude financial firms (SIC code 6000-6999) and utilities (SIC code 49004999). I exclude firm-years with missing values for control variables. All variables are described in the appendix. All
continuous variables are winsorized at the 1% level. ***, **, and * denote significance at the 1%, 5%, and 10% levels,
two-tailed, respectively.

42

Table 7: Within Firm-Year Specification
Panel A: Covenant Ratio

Dependent Variable =Deal Maturity (Quartiles)

Covenant Ratio

Covenant Ratio

Covenant Ratio(1)
0.018**(2.39)(2)
0.015*(1.91)
0.000(0.49)-0.001(-0.35)0.011(1.26)(3)
0.014*(1.77)
0.001(0.98)-0.002(-1.12)0.009(1.03)

Yes
No
No
3,429
0.915

Yes
No
No
3,429
0.916

Yes
Yes
Yes
3,429
0.917

Plain Vanilla
Capex

Plain Vanilla
Capex

Plain Vanilla
Capex

(1)
-0.013*(-1.94)(2)-0.013*(-1.73)0.000(0.14)
0.000(0.20)-0.003(-0.37)(3)-0.017*(-1.79)-0.000(-0.03)-0.000(-0.22)-0.004(-0.57)

Yes
No
No
3,258
0.828

Yes
No
No
3,258
0.828

Yes
Yes
Yes
3,258
0.831

# Lenders# Facilities
Log (Deal Amount)
Fixed Effects
Firm-Year
Loan Purpose
Loan TypeN
R-Squared

Panel B: Plain Vanilla Capex

Dependent Variable =Deal Maturity (Quartiles)# Lenders# Facilities
Log (Deal Amount)
Fixed Effects
Firm-Year
Loan Purpose
Loan TypeN
R-Squared43Panel C: Tailored Capex

Dependent Variable =Deal Maturity (Quartiles)

Tailored Capex

Tailored Capex

Tailored Capex(1)
0.018**(2.06)(2)
0.011(1.11)-0.001(-0.59)0.002(0.89)
0.028***(2.88)(3)
0.003(0.30)-0.001(-0.45)-0.002(-0.57)0.023**(2.28)

Yes
No
No
3,258
0.834

Yes
No
No
3,258
0.837

Yes
Yes
Yes
3,258
0.844

# Lenders# Facilities
Log (Deal Amount)
Fixed Effects
Firm-Year
Loan Purpose
Loan TypeN
R-Squared

Table 7. The table investigates whether deal maturity affects the types of accounting-based and capital expenditurecovenants in debt contracts using a within firm-year specification. This analysis is conducted at the Dealscan level. I
exclude observations with missing values for control variables. All variables are described in the appendix. All
continuous variables are winsorized at the 1% level. ***, **, and * denote significance at the 1%, 5%, and 10% levels,
two-tailed, respectively.

44

Table 8: Tests based on propensity to face unanticipated investment decisions
Panel A: High Market-to-Book

Dependent Variable =Covenant Ratio

Tailored Capex(1)
0.002***(7.09)
0.001**(2.35)-0.036(-1.38)(2)0.001***(4.83)
0.001*(1.83)-0.025*(-1.79)

Yes

Yes

Yes
Yes
Yes
Yes
Yes
Yes
10,933
0.356

Yes
Yes
Yes
Yes
Yes
Yes
10,6740.169

Covenant Ratio

Tailored Capex(1)0.001***(5.96)
0.004***(7.12)-0.182***(-6.69)(2)0.001***(4.78)
0.001**(2.34)-0.027*(-1.74)

Yes

Yes

Yes
Yes
Yes
Yes
Yes
Yes
10,933
0.361

Yes
Yes
Yes
Yes
Yes
Yes
10,6740.169

Deal Maturity
Deal Maturity x High Market-to-Book
High Market-to-Book

All Controls
Fixed Effects
Industry
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year
N
R-Squared

Panel B: R&D Intensity
Dependent Variable =Deal Maturity
Deal Maturity x R&D Intensive
R&D Intensive
All Controls
Fixed Effects
Industry
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year
N
R-Squared45

Panel C: High Sales Growth

Dependent Variable =Deal Maturity
Deal Maturity x High Sales GrowthHigh Sales Growth

All Controls
Fixed Effects
Industry
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year
N
R-Squared

Covenant Ratio

Tailored Capex(1)0.001***(5.96)
0.001**(1.99)-0.043***(-2.59)(2)0.001***(4.98)-0.000(-0.86)-0.004(-0.34)

Yes

Yes

Yes
Yes
Yes
Yes
Yes
Yes
10,914
0.357

Yes
Yes
Yes
Yes
Yes
Yes
10,6570.169

Table 8. The table investigates whether the relation between deal maturity and covenant design becomes stronger forborrowers with more complex investments. Following previous research, I exclude financial firms (SIC code 60006999) and utilities (SIC code 4900-4999). I exclude firm-years with missing values for control variables. R&D
Intensive is a dummy variable equal to one for borrowers with a ratio of R&D to total assets greater or equal to ten
percent, zero otherwise. All variables are described in the appendix. All continuous variables are winsorized at the 1%
level. ***, **, and * denote significance at the 1%, 5%, and 10% levels, two-tailed, respectively.

46

Table 9: Incentive Alignment and Maturity

Dependent Variable =High Incentive Alignment
Deal Maturity x High Incentive Alignment
Deal Maturity

All Controls
Fixed Effects
Industry
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year
N
R-Squared

Covenant Ratio

Tailored Capex(1)-0.173***(-8.86)0.003***(7.67)
0.001***(4.58)(2)-0.034***(-2.64)0.001**(2.09)
0.001***(4.29)

Yes

Yes

Yes
Yes
Yes
Yes
Yes
Yes
10,933
0.356

Yes
Yes
Yes
Yes
Yes
Yes
10,6740.168

Table 9. The table investigates the effect of incentive alignment and maturity on covenant choice. Following previous
research, I exclude financial firms (SIC code 6000-6999) and utilities (SIC code 4900-4999). I exclude firm-years
with missing values for control variables. All variables are described in the appendix. All continuous variables are
winsorized at the 1% level. ***, **, and * denote significance at the 1%, 5%, and 10% levels, two-tailed, respectively.

47

Table 10: Sample Restricted to Contracts with a Capital Expenditure Covenant

Panel A: Descriptive Statistics
Quartile 1
Maturity

Quartile 2
Maturity

Quartile 3
Maturity

Quartile 4
Maturity

Mean

Mean

Mean

Mean

Maturity (months)# Covenants
P-Covenants
C-Covenants
Covenant Ratio
Plain Vanilla Capex
Tailored Capex
Capex State Contingent Provision
Capex Carryforward Provision
Loosening Capex Threshold
Fixed Capex Threshold

19.97
3.34
1.58
0.76
0.70
0.76
0.24
0.06
0.20
0.16
0.73

36.55
3.35
1.71
0.64
0.75
0.67
0.33
0.05
0.30
0.26
0.62

54.95
3.46
2.07
0.38
0.87
0.37
0.63
0.16
0.57
0.26
0.61

72.58
3.71
2.46
0.23
0.93
0.19
0.81
0.18
0.78
0.38
0.47

Tightening Capex Threshold

0.11

0.12

0.14

0.17

48

Panel B: Cross-sectional Tests

Covenant
Ratio

Plain
VanillaCapexTailored
Capex

Capex State
Contingent
Provision

Capex
Carryforward
Provision

Loosening
Capex
Threshold

(1)

(2)

(3)

(4)

(5)

(6)

0.002***-0.006***0.006***

0.001***

0.006***

0.002***(5.69)(-9.32)(9.32)(2.65)(9.12)(3.04)All Controls

Yes

Yes

Yes

Yes

Yes

Yes

Fixed Effects
Industry
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year

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

N

2,533

2,274

2,274

2,274

2,274

1,722

R-Squared

0.335

0.372

0.372

0.133

0.354

0.130

Dependent Variable =Deal Maturity

49

Panel C: Within-firm Tests

Covenant
Ratio

Plain
VanillaCapexTailored
Capex

Capex State
Contingent
Provision

Capex
Carryforward
Provision

Loosening
Capex
Threshold

Deal Maturity

(1)
0.001
(1.61)(2)-0.003**(-2.19)(3)0.003**(2.19)(4)0.001(0.84)(5)
0.003**(2.20)(6)0.001(0.24)All Controls

Yes

Yes

Yes

Yes

Yes

Yes

Fixed Effects
Firm
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year
N
R-Squared

Yes
Yes
Yes
Yes
Yes
Yes
2,533

Yes
Yes
Yes
Yes
Yes
Yes
2,274

Yes
Yes
Yes
Yes
Yes
Yes
2,274

Yes
Yes
Yes
Yes
Yes
Yes
2,274

Yes
Yes
Yes
Yes
Yes
Yes
2,274

Yes
Yes
Yes
Yes
Yes
Yes
1,722

0.869

0.838

0.838

0.754

0.842

0.798

Dependent Variable =Table 10. The table investigates whether deal maturity affects covenant choice when the sample is restricted to only contracts that have a capital expenditurecovenant. Panel A presents descriptive statistics by maturity quartile. Panel B presents regression results when including industry fixed effects. Panel C presents
regression results when including firm fixed effects. Following previous research, I exclude financial firms (SIC code 6000-6999) and utilities (SIC code 49004999). I exclude firm-years with missing values for control variables. All variables are described in the appendix. All continuous variables are winsorized at the
1% level. ***, **, and * denote significance at the 1%, 5%, and 10% levels, two-tailed, respectively.

50

Table 11: Covenant Strictness

Covenant
Strictness

P-Covenant
Strictness

C-Covenant
Strictness

(1)

(2)

(3)

0.000

0.000

-0.000(0.23)(0.03)(-0.69)All Controls

Yes

Yes

Yes

Fixed Effects
Firm
Credit Rating
Loan Purpose
Loan TypeMacro Interest Rates
Year

Yes
Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes
Yes

Yes
Yes
Yes
Yes
Yes
Yes

N

9,470

9,470

9,470

R-Squared

0.636

0.642

0.598

Dependent Variable =Deal Maturity

Table 11. The table investigates whether deal maturity affects covenant strictness. Following previous research, I
exclude financial firms (SIC code 6000-6999) and utilities (SIC code 4900-4999). I exclude firm-years with missing
values for control variables. All variables are described in the appendix. All continuous variables are winsorized at
the 1% level. ***, **, and * denote significance at the 1%, 5%, and 10% levels, two-tailed, respectively.

51