Does Concentrated Arranger Structure In US Syndicated Loan Markets Benefit Large Firms?

Does concentrated arranger structure in US syndicated loan markets benefit large firms?

Yener Altunbaşa and Alper Karab*

aBangor Business School, University of Wales, Bangor.bAberdeen Business School, The Robert Gordon University, Aberdeen

Abstract

This paper explores the nature of the concentrated lender and borrower formationof the syndicated loan market from the perspective of pricing structure. Categorizing the borrowers into groups according to asset size as well as credit ratings assigned by Moody’s at the time of issuance, the interests spread and the fees paid by each group are analyzed. The relationship between firm financial attributes and loan prices are examined by means of OLS regressions. Additionally, the impact of arranger’s reputation on loan price is assessed. The pricing structure of syndicated loans reveals that borrowers with a larger liquidation value, a superior repayment potential, a higher growth potential, a low financial leverage, and those that operate in a regulated industry enjoy lower costs in the syndicated loan market. Financially distressed firms in need of larger funds relative to their size are found to be riskier and charged higher spreads. Results also indicate that larger firms are charged significantly lower when compared to smaller firms in the same risk category. In contrast, when the level of credibility decreases, large firms carrying high credit risk seem to access the market by paying an extra premium when compared to smaller firms. Moreover, firms are found to pay lower spreads by choosing reputable arrangers and the level of fees paid is found to be decreasing in line with an increase in the credit quality of the borrower.

* Corresponding author: Alper Kara, Aberdeen Business School, The Robert Gordon University, Garthdee Road, AB10 7QG, Aberdeen, UK. Tel: 00441224263130, e-mail:[email protected]

1. INTRODUCTION

Today’s syndicated loan market is a vital segment of the global financial system.

According to Thomson Financial (2007) in 2006 the syndicated lending market reached

an all-time high with issuance of over $3.5 trillion, amounting to one third of total

international financing including bond and equity issuance. In 1972, when syndications

were introduced to the banking world, the total volume of activity in the syndicated

loans market stood at $7 billion. Compared to its major alternative, the bond markets

(with origins dating back to the 17th century), syndicated loans are relatively new and

the market has developed expeditiously over the last few decades. Syndicated lending

is often characterized as a hybrid of private and public debt. It constitutes an alternative

both to the bond markets due to its ability to offer sizable loans and as also to bilateral

bank lending due to its capacity to provide relationship banking. In fact, recent studies

(Denis and Mihov, 2003; Myers, 2001; Bolton and Scharfein, 1996) have argued that

equity issues represent a minor fraction of firm external financing while debt financing

is the dominant form of debt.

Although syndicated lending activity represents one third of total global international

financing the market is highly concentrated; there are only a limited number of players

in both the supply and demand side of the market. The US market constitutes a

benchmark for syndicated lending business as it absorbs more than 65% of global

syndicated lending activity. On the demand side large firms constitute the main clients -

more than 50% of syndicated loans (in value) in US market are issued to a limited

number of firms with assets size over $10 billion. Looking at the lenders side, one can

also see a concentrated group of institutions operating in the market. According to

Thomson Financial 2006 league tables, in the US around 85% of all syndicated loans

are underwritten by only ten large banks of which the top three (JP Morgan, Bank of

America and Citigroup) coordinate 68% of all activity in this market. Overall it can be

argued that the supply side of the syndicated loans market is controlled by a few major

players that earn noteworthy fee1 income from these activities. In a typical syndicated

1 Thomson Financial (2005) reports that the fee income from global debt underwriting activities amounts to $6.6 billion and two thirds of this figure was earned by the top 10 underwriters.

lending procedure these banks (also called lead banks or arrangers) are situated at the

core of the loan syndication and participants of the syndicate rely on the agent for

information related to the borrower. Moreover, in loan syndications monitoring is also

conducted by the arranger banks. Simons (1993) notes that syndicate participants

evaluate the credit of the borrower by relying on the loan documentation provided by

the syndication arranger (typically the relationship lender of the borrower) which

possesses insider knowledge relating to the borrower’s financial condition. This gives

rise to the possibility that syndicate members may not be fully informed and may be

exploited by the agent bank, that is, the lead bank may sell a larger proportion of a

potentially problematic loan to syndicate members, while retaining a larger proportion

of a loan of high quality in its own portfolio (Panyagometh and Roberts 2002).

Agent banks might exploit this advantageous position and assist debt distressed

borrowers to the syndicated loan market in return for underwriting fees. Thomson

Financial reports that the fee income from global debt underwriting activities (including

bond and loans) amounted to $6.6 billion in 2004 and two thirds of this figure was

earned by the top 10 underwriters (mainly investment banks). Therefore, the motivation

of investment banks to engage in syndicated lending business as arrangers is

straightforward – they earn a substantial fee income from their underwriting activities.

Undoubtedly, in a competitive banking environment where the financial firms are

forced to create alternative income sources, investment banks aim to stay at the top of

the league of loan underwriting business by keeping tight relations with large firms

issuing debt in this market.

Recent academic literature has explored the role of the agent bank and highlighted

possible moral hazard issues - such as misleading the junior participants and transferring

riskier loans to their portfolios - in the syndication process. Studies by Simons (1993),

Panyagometh and Roberts (2002), Jones et al. (2000) have investigated this possible

exploitative behaviour of agent banks on other syndicate members and concluded that

agency problem does not appear to exist in the syndicated loans business. However in a

recent study, Altunbas et al. (2005) have argued that agent banks in fact are offloading

potentially riskier loans to junior lenders, especially when the senior syndicate members

have lower capitalisation and worse quality loan portfolios (details of the studies will be

discussed in the literature review section shortly). It is also argued that reputable

arrangers, the ones that are well known in the market as experienced in organizing

successful loan syndicates by facilitating the sale of loans to a wider range of creditors

(typically the top 10 investment banks), has a significant impact on the pricing of the

loan and also has the potential to provide lower yields for large debt issues.

Apart from the likelihood that large firms might be accessing the syndicated loan

market through reputable agents that are exploiting junior creditors, the incentive for

these financial distressed firms to approach the syndicated loan market might be related

to arranger banks’ monitoring abilities (rather than exploitation of their advantageous

position in the syndicate hierarchy). This could mitigate agency problems or value

growth opportunities superior to bond markets, as well as offer cheaper prices.

The goal of this paper is twofold. Firstly, it aims to discover how the quality of the

borrower shapes the pricing structure of the syndicates and how (or if) the pricing

influences the incentives that attract larger financially distressed firms as recurrent

customers to the syndicated loan market. Secondly, it aims to detect if agent banks, in

return for underwriting income, play a role in facilitating large firms access to funds

(which otherwise may not be provided to them given their current credit quality and

debt exposure). At the outset borrowers are categorized into groups according to asset

size as well as credit quality (assigned by Moody’s) at the time of loan issuance in order

to compare the interest and fees paid by these firms. Subsequently, the relationship

between firm’s financial characteristics (i.e. size, leverage, growth options, information

asymmetry, profitability and liquidation value) and low price are examined by means of

OLS regressions (controlling for loan attributes such as maturity or size). Furthermore,

the components of loan price, namely interest and fees, are then examined separately,

examining the influence of arranger reputation on the impact on the pricing.

The analysis undertaken in this paper differs from the established literature. Primarily,

the sample selected includes firms which raise debt in this market for solely capital

structure purposes and disregards loans that are issued for corporate takeover activities,

project finance and for other corporate structuring purposes. This allows one to be able

to test the arguments of the capital structure theory (such as the effect of agency costs,

renegotiation, disclosure concerns, firm growth options and liquidation value) on

pricing of the syndicated loans. Secondly, although studies have explored the

relationship between firm (borrower) information and interest rates spreads on

syndicated loans, this study is the first (to the authors knowledge) to investigate these

relationships analysing firms according to various credit risk groups. The data is

gathered from Dealogic’s Loanware database, and the sample used in this study

comprises of 4,800 syndicated loan issued to US firms for capital structure purposes

between 1993 and 2004.

The rest of the paper is organized as follows. Section 2 reviews the literature related to

syndication structure and role of the arranger. Section 3 describes the main data sources

and the empirical methodology. The estimation and descriptive results are presented

and discussed in Sections 4 and 5. Section 6 summarizes findings and concludes the

paper.

2. LOAN SYNDICATION STRUCTURE – THE ROLE OF THE

ARRANGER AND AGENCY ISSUES

A syndicated loan facility involves a number of lenders extending a loan to a single

borrower collectively. Mandated by the borrower, an arranger (or lead) bank promotes

the loan to potential lenders that have interest in taking exposure to the issuer firm. The

lead arranger provides probable participants with firm specific information

memorandum2; the contents of which have been previously agreed by the borrowing

firm with the lead bank. Each participant creditor partially funds the loan at identical

conditions and is responsible for their share of the loan and, therefore has no legal

responsibility to other participants’ shares. In a typical syndicated lending procedure

lead banks are situated at the core of the loan syndication and both borrower and

participants of the syndicate rely on the agent for information. Apart from various fees

involved in the loan syndication process, arranger banks additionally are remunerated

by an arrangement fee. As mentioned above, the fee income from global debt

2 Information memorandum are prepared by both the arranger and the borrower and sent out by the arranger to potential syndicate members. The arranger assists the borrower in writing the information memorandum on the basis of information provided by the borrower during the due diligence process. It contains a commercial description of the borrower's business, management and accounts, as well as the details of the proposed loan facilities being given. It is not a public document and all potential lenders that wish to see it usually sign a confidentiality undertaking (LMA 2006).

underwriting constitutes a major source of income for investment banks (around $4.4

billion for the top ten), where a handful control the business.

Syndicate participants rely on the agent bank to evaluate the credibility of the borrower.

Panyagometh and Roberts (2002) argue that such reliance give rise to a possible

exploitation by the arranger bank that have more information on borrowers financial

conditions than the other syndicate participants. Several papers have focused on the

arranger’s role and influence on formation and pricing of loan syndications. Studies by

Simons (1993) and Jones et al. (2000) focus on arranger behaviour and whether the

arranger banks are likely to behave opportunistically. Both studies use loan ratings as a

measure of borrower credibility and examine if the arranger retains a larger share on

loans. They find a negative relationship between the arrangers’ share and the quality of

the loan and conclude that evidence of exploitative behaviour is not detected. However

Jones et al. (2000) highlights that arrangers may still exploit their informational

advantage and syndicate more of the low quality loans that the syndicate members

would have accepted under a symmetric-information environment. Similarly

Panyagometh and Roberts (2002) test the role of private information and the prevalence

of agency problems in loan syndications through proxies for changes in borrowers credit

rating and find evidence that the lead bank syndicates a larger proportion of a loan when

firm’s credit rating is subsequently upgraded. This implies that agency problems do not

prevail in loan syndications.

On the contrary, Altunbas et al. (2005) find that agent banks offload potentially riskier

loans to junior lenders, particularly when the senior syndicate members have lower

capitalisation and poorer quality loan portfolios. In addition, certification effects are

identified, as information about borrowers becomes less transparent, junior banks

appear to rely more on senior bank reputation to determine the level of their

participation in the syndicate. In sum, the established literature is ambiguous as to

whether moral hazard prevails in the syndicated loan market.

2.1 Arranger reputation and the success of syndication

The influence of arranger reputation on the success of a syndication is also investigated

in the literature. Dennis and Mullineux (2000) and Lee and Mullineux (2001), for

instance, argued that a syndication loan process is more successful when the arranger is

a reputable firm in the market, and when the arranger has strong lending relationships

with the borrower. Dennis and Mullineux (2000) point out that a larger share of the

loan is syndicated when the arranger is reputable. Panyagometh and Roberts (2002)

provide evidence on the impact of agent reputation on marketability of the loan.

Focusing on the syndicated loan market between 1987 and 1999 they conclude that a

loan is more likely to be syndicated and to be sold in larger proportions when the lead

bank is reputable and gains the trust of the syndicate members.

Furthermore, Casolara et al. (2003) examines banks’ ability to mitigate informational

asymmetries, by verifying whether in syndications the arranger retains a larger share of

the loan. If this is the case then the loan is considered to be less risky by syndicate

participants and such syndicates should carry a lower interest rate. For smaller size

loans Casolara et al. (2003) conclude that the presence of certification effects of the

arranger (retaining a larger share of the loan) leads to lower interest rates. Casolara et

al. (2003) additionally provide evidence in favour of banks’ role in screening and

monitoring the financial condition of smaller and less reputable opaque borrowers.

However for large loans they do not find evidence of certification effects and the pricing

of the loan appears to be fully accounted for by borrower and deal-specific

characteristics.

The function of the arrangers in the syndication process is comparable to those of

investment banks underwriting bonds. There is an established literature related to

agency reputation in bond underwriting business. In their theoretical work Chemmanur

and Fulghieri (1994) model how underwriters (investment banks) gain reputation and

show that reputation is established by adopting stringent evaluation standards. In

equilibrium, arrangers with reputation underwrite less risky issues, obtain higher prices

for the issuers, and receive higher compensation. Booth and Smith (1986) emphasize

the certification role of the agency under asymmetric information. Fang (2005) finds

that more reputable banks obtain lower yields for issuers compared to their less

reputable competitors. She also posits that these reputable banks charge higher fees,

which she interprets as economic rents on reputation.

Overall, the consensus view is that a reputable arranger (or underwriter) has a

significant influence on the participant banks and provides lower yields for large debt

issues both in loan and bond markets. In case of loan syndicates, a reputable arranger

facilitates the sale of the loan to a wider range of creditors.

2.2. Firm characteristics, credit spreads and loan ratings

Several recent studies have explored how borrower and loan characteristics explain

variation in loan spreads (pricing) in debt (bond and loan) issues. Typically loan

maturity and size as well as borrower features (size, financial leverage, liquidity, and

profitability) are utilized in model specifications. Looking at a sample of over 3,500

loans issued in the syndicated loan markets Coleman et al. (2002) uses the borrower

specific characteristics together with the features of lenders (including capital adequacy,

loan portfolio quality and monitoring ability). Their findings demonstrate that the level

of borrower firm’s financial leverage results in higher loan spreads while liquidation

measures (fixed asset ratio) and firm size are negatively related to the cost of the loan.

The study also reports a positive relationship between loan maturity and spreads

suggesting that firms with higher credit risk prefer longer-term debt to limit re-financing

risk (see Diamond 1991). Additionally, from a lenders perspective, Coleman et al.

argue that banks that are superior in monitoring are able to make longer maturity loans

than less competent monitors, and lenders with inferior monitoring skills need to restrict

loans to shorter time-periods.

Angboza et al. (1998) examines over 4,000 loan transactions (used to finance LBO’s) to

gauge the determinants of credit risk spread and finds that larger firms pay lower

spreads in the syndicated loan market (and spreads increase with maturity). One other

key finding of their work is that upfront fees have a positive and significant coefficient

in their yield spread regression, which is inconsistent with the hypothesis that loan rates

and fees are substitutes. That is banks do not appear to charge lower loan rates with

expectation of extracting higher upfront fees from borrowers.

Hubbard et al. (2002), using over 1200 loan contracts, find that larger firms can access

cheaper funds in loan markets. Contrary to the aforementioned studies Hubbard et al.

report that the loan maturity has a negative impact on the cost of borrowing (longer term

loans are cheaper). This is supported by Barclay and Smith (1995) and Stohs and

Mauer (1996) who find that maturity is negatively related to loan spreads as long-term

debt is more likely to be issued by less risky borrowers.

The literature also finds that secured loans are more costly. For instance, Coleman et al.

(2002), Angbazo et al. (1998), and Yi and Mullineux (2005) all find that firms with

high credit risk are expected to secure their loans to be able to access the syndicated

loan market and this does not reduce the overall risk premium charged by lenders.

These studies also report that larger firms pay lower spreads in loan markets. While

profitability is accredited by lenders as a positive sign for ability to payback, firms are

punished with higher costs of funding if their financial leverage is high.

Following a similar approach to those applied by the above studies, this paper aims to

analyze the supply and demand structure of the syndicated loan market from a pricing

perspective. The paper varies from previous studies in several ways. Unlike other

studies the sample includes loans issued for solely capital structure purposes (and funds

borrowed for takeover activities, project finance or for other purposes are disregarded

from the sample). Firstly, this allows one to be able to test the arguments of the capital

structure theory (such as the effect of agency costs, renegotiation, disclosure concerns,

firm growth options and liquidation value) on pricing of the syndicated loans.

Secondly, the major focus is given to capital structure loans as the pricing dynamics as

well as the motivation of borrowers and lenders to extend loans for different purposes is

more likely to vary. For example loans extended for M&A (corporate control) purposes

are charged significantly higher spreads (on average 50 basis points) when compared to

loans for capital structure purposes. Similarly, a typical loan extended for capital

structure bears a maturity of around 3 years whereas a project finance loan’s average

maturity is over 8 years (see Altunbas et al. 2006, Chapter 3 for more detail).

Furthermore, this study is the first (to authors knowledge) to investigate the how debt

issues of firms bearing the same risk (as a metric of credit risk, Moody’s loan ratings are

used to group the borrowers), are priced.

3. CREDIT RATINGS AND THE FIRM’S COST OF BORROWING

The sample comprises 4839 syndicated loans issued to 1756 US firms for capital

structure purposes between 1993 and 20043. Borrowers are grouped into three

categories according to their size;

(i) Small → Firms with total assets smaller than USD 1 billion,

(ii) Medium → Firms with total assets between USD 1 billion and 10 billion,

(iii) Large → Firms with total assets larger than USD 10 billion.

Subsequently, firms are segregated by their credit quality indicators prior to the issuance

of the debt. Three benchmark indicators for credit quality are;

(i) Credit rating assigned by Moody’s prior to issuance,

(ii) Firms’ debt intensity, measured by the debt to total assets ratio,

(ii) Firms’ repayment capacity, measured by earnings before interest, taxes,

depreciation and amortization to total debt.

Ratings are utilized as a tool to group similar sized firms bearing the same credit risk

rating in order to compare the interest and fees paid in loans syndications. Typically a

loan rating is very close to issuing firms overall credit rating, and adjusted slightly

(notched up or down) in relation to the characteristics of the debt instrument. The

rating process involves historical and peer-group based financial ratio analysis,

consideration of operating and financial policies, projections of cash flows and

3 Loan and firm specific characteristics are compiled from Dealogic’s Loanware and Thomson One Analytics’ Worldscope databases. Loanware provides detailed information on the characteristics of loans including maturity, spread, fees, size, year of issuance, the type and name of borrowing entity, credit quality etc. Worldscope supplies financial statement, earnings and fundamental ratio information of firms listed on global stock exchanges all around the world.

profitability, examinations of organizational and governance structures and the

borrower’s strategic and operational goals (Yi and Mullineaux 2005)4.

However some studies highlight that agency credit ratings might not reflect the full

credit risk of the borrowers. The agencies (such as Moody’s, S&P or Fitch) claim that

ratings do not simply reflect public information, but also contain private information

obtained from the borrower during the rating process (Yi and Mullineaux 2005).

Wakeman (1984) argues that ratings (in the case of bond issues) do not reveal

significant private information to investors. Similarly John, Lynch and Puri (2000)

claim that rating agencies fail to incorporate agency problems when assigning credit

rating on bonds. Conversely, in a study on loan ratings, Yi and Mullineaux (2005)

conclude that loan ratings can contain private as well as public information. Even

though the literature does not concur on the private information content of credit ratings,

there at least is a consensus that credit ratings are an appropriate overall measure of

firm’s financial state.

In addition to credit ratings, debt intensity and repayment capacity are selected as the

two key indicators to asses the credit quality of the borrower. Loan syndications also

often involve covenants. A covenant can be described as a condition that the borrower

must comply in order to adhere to the terms in the loan agreement. In general, lenders

include covenants in loan contracts in order to maintain loan quality, adequate cash

flow, and to provide a mechanism that allows changes in the light of the borrower’s

financial performance and condition. In case of a breach of covenants, the loan can be

considered in default and the lender has the right to demand payment. In loan

syndications the most common covenants are benchmarked using debt to total assets

(debt intensity) and earnings before interest, taxes, depreciation and amortization

(EBITDA) to total debt (repayment capacity) ratios. After scrutinizing the imposed

covenants in the sample, the critical levels, that is the limits for a possible breach, for

debt intensity (measured by debt to total assets ratio) are found to be between 60% to

4 According to Yi and Mullineaux (2005) during the 1990’s institutional investors (pension funds, mutual funds, investment banks, and insurance companies) became increasing interested in bank loans as a alternative investment class. This motivated leading rating agencies (Moody’s, S&P and Fitch) to enter the loan rating business. Loan ratings have further led to an increase in the activity both in primary and secondary markets.

80% while for repayment capacity [measured by EBITDA to total debt] those are

typically between 25% to 50%.

Similar to credit ratings, the firms in the sample are grouped according to risk categories

on the basis of their debt intensity and repayment capacity as follows;

Debt to total assets ratio EBITDA to debt ratio

Low Risk < 30% > 75%

Medium Risk 30% - 60% 50% - 75%

High Risk 60% - 80% 25% - 50%

Highest Risk > 80% < 25%

3.1 Descriptive Statistics: Risk vs. Cost

Out of 4839 loan issues a total of 4017 have credit scores assigned by Moody’s.

Descriptive statistics of the loans segregated by firm size and Moody’s Credit Risk

Ratings are presented in Table 1. Overall 50% of all loans (in value) are extended to

Low Risk borrowers (a total of $1.048 trillion) and 32% are issued by Medium Risk

borrowers while the Highest Risk firms only managed to obtain only 1% of total

issuence. The largest firms obtained the highest percentage of loans (in value) with

57% while medium size firms share was only 6%. Maturities do not differ across

subgroups of credit quality or firm size, and on average are around 3 years. Mean loans

size is the largest for firms with the highest credit quality, especially large firms which

have an average loan size of $1.5 billion. Figures presented in Table 1 clearly illustrates

that the typical customers of the syndicated loans markets are very large firms with low

credit risk. Firms, in the highest risk category appear to have little opportunity to issue

debt in this market.

Table 1: Descriptive statistics of syndicated loans segregated by firm size and Moody's credit risk ratings

This table presents descriptive statistics for loan maturity and size by grouping borrowing firms by firm size and credit risk (rated by Moody's). Small Firms → with total assets smaller than USD 1 billion, Medium Firms → with total assets between USD 1 billion and 10 billion, Large Firms → with total assets larger than USD 10 billion. Mean and median maturity are in years, mean and median loan size are in $ billion.

Moody's Credit Rating

Firm sizeMean

maturityMedian maturity

Mean loan size

Median Loan Size

Total loans issued

Percentage to total value of

loans

Number of loans

Percentage to total number of

loans

Low risk Small 3.3 3.0 258 100 9819 0.5% 38 0.9%(Aaa, Aa, A) Medium 3.0 3.0 433 300 264395 12.7% 610 15.2%

Large 3.0 3.0 1517 1000 773814 37.1% 510 12.7%All Firms 3.0 3.0 905 500 1048028 50.3% 1158 28.8%

Medium risk Small 3.0 3.0 173 150 16103 0.8% 93 2.3%(Baa) Medium 3.3 3.0 409 300 309216 14.8% 756 18.8%

Large 3.0 3.0 1062 826 350604 16.8% 330 8.2%All Firms 3.2 3.0 573 350 675923 32.4% 1179 29.4%

High risk Small 3.0 3.0 122 98.75 96724 4.6% 796 19.8%(Ba, B) Medium 3.2 3.0 286 205 164872 7.9% 577 14.4%

Large 3.3 3.0 629 470 73615 3.5% 117 2.9%All Firms 3.1 3.0 225 150 335211 16.1% 1490 37.1%

Highest risk Small 3.2 3.0 65 42.25 7447 0.4% 114 2.8%(Caa, Ca, C) Medium 2.6 2.0 200 131.6 14805 0.7% 74 1.8%

Large 2.0 2.0 1100 1100 2200 0.1% 2 0.0%All Firms 3.0 2.7 129 70 24452 1.2% 190 4.7%

Total Small 3.0 3.0 125 100 130094 6.2% 1041 25.9%Medium 3.1 3.0 373 275 753288 36.2% 2017 50.2%Large 3.0 3.0 1252 800 1200233 57.6% 959 23.9%All Firms 3.1 3.0 519 250 2083614 100.0% 4017 100.0%

* Moody's ratings: Aaa - gilt grade, Aaa - high grade, Aa - upper medium grade, Baa - medium grade, Ba - speculative elements, B - lacks characteristics of desirable investment, Caa - poor standing, Ca -speculative in a high degree, C - lowest rated

Table 2: Spread and fees paid in the syndicated loan market segregated by firm size and Moody's credit risk ratings *†

This table presents descriptive statistics for loan maturity and size by grouping borrowing firms by firm size and credit risk (rated by Moody's). Small Firms → with total assets smaller than USD 1 billion, Medium Firms → with total assets between USD 1 billion and 10 billion, Large Firms → with total assets larger than USD 10 billion. Mean and median maturity are in years, mean and median loan size are in $ billion.

Spread FeesFirm Size

Statistics Small Medium Large All Firms Small Medium Large All FirmsLow Risk Mean 83 45 37 43 25 10 7 9(Aaa, Aa, A) Median 63 35 29 33 13 8 7 8

Std. Dev. 63 37 32 37 24 11 4 9Maximum 275 350 436 436 88 138 40 138Number of Loans 32 521 459 1012 26 502 444 972

Medium Risk Mean 98 99 94 98 23 19 18 19(Baa) Median 88 88 88 88 23 15 15 15


High Risk Mean 244 240 303 247 45 44 51 45(Ba, B) Median 250 225 275 250 50 50 50 50


Highest Risk Mean 343 348 350 346 45 60 51(Caa, Ca, C) Median 325 313 350 325 50 50 50

Std. Dev. 135 130 0 131 22 28 26Maximum 900 750 350 900 125 100 125Number of Loans 77 54 2 133 58 36 0 94

Total Mean 233 133 90 147 42 22 15 24Median 250 88 50 100 43 15 10 15Std. Dev. 118 117 105 126 25 21 17 23Maximum 900 925 650 925 250 200 150 250Number of Loans 857 1792 863 3512 568 1464 791 2823

* Moody's ratings: Aaa - gilt grade, Aaa - high grade, Aa - upper medium grade, Baa - medium grade, Ba - speculative elements, B - lacks characteristics of desirable investment, Caa - poor standing, Ca - speculative in a high degree, C - lowest rated† Spread and fees are basis point over LIBOR

Table 2 displays the spread and fees paid over LIBOR for the loans described above5.

As expected the segregation by credit ratings reveals that firms with lower credit risk

can obtain loans with lower cost. While firms in the highest risk category pay around

350 basis points spread over LIBOR, firms in the low risk category can access loans

with a spread as low as 43 basis points. Medium sized firms, even though they are in

the same low risk categories, pay more than double (83 basis points) the spread when

compared to larger firms (paying 43 basis point) with the same credit rating. A

surprising result of the analysis is the fact that firms in the low risk category pay

different spreads depending on their size even though they bear the same credit risk. In

contrast, large firms with high risk ratings (Ba, B categories) seem to be allowed to

access the market by paying on average an extra 63 basis points (303 basis points vs.

240 basis points) more than similar risk medium sized firms. As suggested in Table 1,

if creditors extend loans to firms in the high risk category, then they are more likely to

prefer to lend to medium sized firms. Perhaps extending to smaller borrowers decreases

their loss relatively in case of a default.

Overall firms pay an average fee of 24 basis points over LIBOR, however small firms

pay more than twice when compared to the large firms in the market (15 basis points vs.

42 basis points). The level of fees decreases in-line with an increase in the credit

quality of the borrower, firms in the high risk category pay almost 5 times as much

when compared to low risk borrowers. These results, also argued by Angboza et al.

(1998), signify that the risk of the borrower is not solely reflected in the interest rate

spread charged, but also to the fees paid by the firm to obtain the loan.

Similar to the results obtained above from the spread analysis (Table 2), one surprising

result of the analysis is the fact that firms belonging to the same risk category pay

different fees relative to their size. A small sized firm in the low risk category is

charged more then three times when compared to the largest firm in the same category.

Additionally, although large firms pay the lowest fees in the low and medium risk

categories, they appear to lose this privilege when they carry high risk and pay larger

fees to be able to access the market. In general, however, these finding signify that

5 Out of 4017 loans that are assigned a credit rating 3512 have available data for interest spread while 2823 have available data for fees.

large US firms can access the syndicated loan markets with lower cost compared

smaller size firms. This fact raises further questions for arranger moral hazard in the

pricing process of loan syndications. Arrangers (top investment and commercial banks)

may favour large borrowers by using banks reputation to facilitate large firms’ access to

the market. As noted earlier, in loan syndications lenders are predominantly dependent

on the arranger for firm specific information about the borrowers and arrangers might

exploit this information asymmetry.

Similar results are obtained when debt intensity and repayment capacity levels are

examined (Table 3 and Table 4). Small firms with less than 30% debt intensity and

with a 75% debt repayment capacity have to pay three times more interest spread (190

basis points versus 63 basis points) when compared to the largest firms in the same risk

category. However, the largest firms at critical levels of debt intensity (60% to 80%) are

allowed to fund their activities only if they pay an extra 100 basis points more than

small sized firms.

Table 3: Spread and fees paid in the syndicated loan market segregated by firm size and debt intensity*This table presents descriptive statistics for loan maturity and size by grouping borrowing firms by firm size and credit risk (rated by Moody's). Small Firms → with total assets smaller than USD 1 billion, Medium Firms → with total assets between USD 1 billion and 10 billion, Large Firms → with total assets larger than USD 10 billion. Mean and median loan size are in $ billion.


Statistics Small Medium Large All Firms Small Medium Large All Firms<30% Mean 190 96 63 147 34 19 12 26

Median 175 63 32 125 30 13 7 23Std. Dev. 103 91 79 110 19 18 16 20Maximum 1138 925 475 1138 225 200 135 225Number of Loans 1997 997 423 3417 1492 854 403 2749

30% - 60% Mean 226 148 103 177 40 25 18 30Median 225 113 74 150 38 18 13 25Std. Dev. 107 119 98 120 28 23 20 26Maximum 1000 750 600 1000 600 238 150 600Number of Loans 1405 1073 497 2975 995 855 455 2305


>80% Mean 281 278 277 280 51 57 29 52Median 275 275 400 275 50 50 29 50Std. Dev. 117 125 212 120 33 39 30 34Maximum 800 500 400 800 200 150 50 200Number of Loans 205 56 3 264 124 38 2 164


* Spread and fees are basis point over LIBOR, Debt intensity is measured by total debt divided by total assets

Table 4: Spread and fees paid in the syndicated loan market segregated by firm size and repayment capacity*This table presents descriptive statistics for loan maturity and size by grouping borrowing firms by firm size and credit risk (rated by Moody's). Small Firms → with total assets smaller than USD 1 billion, Medium Firms → with total assets between USD 1 billion and 10 billion, Large Firms → with total assets larger than USD 10 billion. Mean and median loan size are in $ billion.


Statistics Small Medium Large All Firms Small Medium Large All Firms

>75% Mean 168 75 52 118 31 15 11 21Median 150 50 25 100 25 10 6 15Std. Dev. 93 73 70 97 19 15 19 19Maximum 650 525 400 650 225 138 135 225Number of Loans 606 417 180 1203 380 358 173 911



<25% Mean 254 206 153 221 42 33 24 35Median 250 200 113 225 48 30 18 38Std. Dev. 93 121 127 115 21 24 20 23Maximum 650 688 650 688 200 238 100 238Number of Loans 860 577 294 1731 490 380 245 1115


* Spread and fees are basis point over LIBOR, Debt intensity is measured by EBITDA divided by total debt

4. ARRANGER’S REPUTATION AND THE FIRM’S COST OF

BORROWING

In this section a descriptive analysis similar to the one conducted above is used to

scrutinize the effect of arranger reputation on the cost of borrowing. The sample is

divided into two groups according to the arrangers as follows6;

(i) Reputable arrangers: Banks that are declared as top 10 arrangers (in terms

of number of deals) by Thomson Financial League tables7 between 1993 and

2004. In the sample 30 banks are regarded as reputable arranging 53% of all

loans.

(ii) Standard arrangers: Rest of the arrangers not listed in the top 10 list. In the

sample 523 banks are regarded as standard arrangers.

Borrowers tend to prefer reputable arrangers as they may have the ability to establish a

wider array of participants to join the syndication than a standard arranger.

Additionally, reputable arrangers may have stronger negotiation power within the

syndication to assist borrowers to access funds at a cheaper price. Dennis and

Mullineux (2000), Lee and Mullineux (2001) and Panyagometh and Roberts (2002)

have argued that a syndication process is more successful and the loan is more

marketable (a larger share of the loans is distributed) when the arranger is a reputable

firm in the market, and when the arranger has a strong lending relationship with the

borrower. Table 5 presents the descriptive statistics for both of the arranger types.

6 Loans organized by more than one arranger are excluded from the sample, and therefore the selected sample only embraces loans with single arranger banks.7 Thomson Financial's standard league tables are rankings of Investment Banks in terms of the dollar volume of deals they work on. New standard league table sessions in compliance with 2004 league table criteria for Debt, Equity, Syndicated Loans, Project Finance and M&A are currently available.

Table 5: Interest spread paid to loan syndications*

This table presents descriptive statistics for interest (basis points over LIBOR) paid on loans by grouping borrowing firms by size and credit risk (rated by Moody's†) and arrangers by reputation. Small Firms → with total assets smaller than USD 1 billion, Medium Firms → with total assets between USD 1 billion and 10 billion, Large Firms → with total assets larger than USD 10 billion. Mean and median spreads are all basis points over LIBOR.

Loans by reputable arranger Loans by standard arrangerFirm Size

Statistics Small Medium Large All Firms Small Medium Large All FirmsLow Risk Mean 175 55 32 48 79 33 26 34(Aaa, Aa, A) Median 175 38 18 33 50 28 25 25

Std. Dev. 141 52 23 51 60 24 12 27Maximum 275 200 88 275 200 200 65 200


Std. Dev. 59 140 41 114 63 49 71 56Maximum 250 925 153 925 250 300 300 300

High Risk Mean 222 239 221 227 222 219 235 222(Ba, B) Median 225 225 325 225 225 200 213 225

Std. Dev. 102 134 180 112 103 129 166 116Maximum 625 750 325 750 500 688 650 688

Highes Risk Mean 324 439 359 306 327 312(Caa, Ca, C) Median 325 325 325 325 350 325

Std. Dev. 156 220 182 103 66 94Maximum 900 750 900 600 400 600

Total Mean 225 158 54 174 208 109 59 136Median 225 113 30 150 216 50 25 75Std. Dev. 118 163 64 145 116 119 88 126Maximum 900 925 325 925 600 688 650 688

†Moody's ratings: Aaa - gilt grade, Aaa - high grade, Aa - upper medium grade, Baa - medium grade, Ba - speculative elements, B - lacks characteristics of desirable investment, Caa -poor standing, Ca - speculative in a high degree, C - lowest rated. *Spread is basis points over LIBOR

On average, low risk firms that have standard arrangers have paid 14 basis points more

interest spread then their peers working with reputable arrangers (34 basis points vs. 48

basis points). For medium risk borrowers the difference rises to 22 basis points while in

the high risk category it reads 47 basis points. Furthermore, t-tests are also employed to

examine if borrowers with reputable arrangers are charged less in syndicated loan

markets. The results are presented in Table 6. Except for the highest risk borrower

category the t-tests confirm that there is a significant difference between interest spreads

paid by firms working with reputable arrangers than compared to those working with

standard arrangers8. Overall, these results are supported by Dennis and Mullineux

(2000), Lee and Mullineux (2001) and Panyagometh and Roberts (2002) who find that

borrowers are better off by choosing a reputable arranger in the market, as they pay

lower interest spreads compared to firm with same credit risk who works with standard

arrangers.

Table 6: T-test results for mean comparison of spreads (basis points over LIBOR) paid by firms working with a reputable arranger and firms working with standard arrangers

Number of ObservationsRisk Categories T- Value P- Value Reputable Standard Total

All 5.8731 0.0000 1059 595 1654Low Risk (Aaa, Aa, A) 3.2904 0.0011 274 97 371Medium Risk (Baa) 1.9199 0.0557 239 118 357High Risk (Ba, B) 1.9221 0.0549 484 336 820

Highest Risk (Caa, Ca, C) 1.1560 0.2503 62 44 106

The above analysis is repeated, but this examines fee levels. The results are reported in

Table 7. When all the risk categories are examined there is a significant difference (at

the 10% level) between the two groups, namely, firms with reputable arrangers pay

lower fees (descriptive statistics are presented in Appendix 3). The same results are

also obtained (at the 10% level) when only the difference between low risk categories

are tested. Overall these findings coincide with Fernando et al. (2005) who argue that

high quality issuers are more likely to link with high quality underwriters. By

measuring firm quality according to the loan rating assigned to the issuer one can see

that low risk borrowers typically work with reputable underwriters.

8 Moreover, average loan size arranged by reputable arrangers is significantly different than other group

Table 7: T-test results for mean comparison of fees (basis point over LIBOR) spreads paid by firms working with a reputable arranger and firms working with standard arrangers

Number of ObservationsRisk Categories T- Value P- Value Reputable Standard Total

All 1.7504 0.0803 922 396 1318Low Risk (Aaa, Aa, A) 1.6654 0.0967 271 83 354Medium Risk (Baa) 0.6851 0.4938 213 84 297High Risk (Ba, B) -0.1532 0.8783 374 205 579

Highest Risk (Caa, Ca, C) -1.4972 0.138 62 24 86

5. DETERMINANTS OF SPREAD AND FEES – A PERSPECTIVE

FROM CAPITAL STRUCTURE THEORY

A limitation of the descriptive analysis presented above is that the analysis is mainly

based on Moody’s credit ratings. However, as mentioned above some researchers (such

as Wakeman, 1984 and John et al., 2000) argue that credit ratings assigned by agencies

do not reveal significant private information of the borrower to the creditors and

moreover, the content of the credit ratings fail to incorporate problems arising from

asymmetric information (agency problems). This section of the paper aims to link the

arguments of the theory capital structure (discussed in paper 1), such as agency issues,

negotiation concerns, liquidation concerns or growth options, with the spreads and fees

paid by using the financial attributes of the borrowers. In other words, rather than

relying on issued credit ratings the credit quality of the borrower is assessed by its

financial indicators derived from capital structure theory.

5.1 Methodology

Following similar approaches as Coleman et al. (2002), Angboza et al. (1998) and

Hubbard et al. (2002) the effect of firms’ financial attributes on loan price is examined

via OLS regression. Typically these studies utilize spread and fees (both in basis

points) paid for loans as the dependent variable and employ financial characteristics of

the firm as independent variable. In a similar method following OLS regression is

estimated;

(t-Value = -6.3982, P-Value = 0.000).

Spread and fees = β0 + β1 Maturity + β2 Loan Size

+ β3 Number of arrangers + β4 Secured loan dummy

+ β5 Financial Leverage + β6 Financial Stress (3)

+ β7 Profitability + β8 Market to book value

+ β9 Loan size to total assets + β10 Regulation dummy

+ β11 Liquidation value + β12 Reputable arranger dummy + ε

Where;

Dependent variables:

(i) Spread = Yearly payment of interest measured as basis point over LIBOR

(ii) Fees = Yearly payment of fees measured as basis point over LIBOR

Loan attributes:

(iii) Maturity = Length of the loan in years

(iv) Number of Arrangers = Number of arrangers involved in the syndicated

(v) Secured loan dummy = Takes the value of 1 if the loan is secured, 0

otherwise

Borrower attributes:

(vi) Firm Size = Natural log of borrowers total assets

(vii) Financial Leverage = AssetsTotal

DebtTotal

(viii) Financial Stress = DebtTotal

DebtTermShort

(ix) Profitability = Return on Equity

(x) Market to Book Value = FirmtheofValueBook

FirmtheofValueMarket

(xi) Liquidation Value = AssetsTotal

AssetsFixed

(xii) Regulation dummy= 1 if the firm operates in a regulated industry9, 0

otherwise.

9 These industries are: Electric, gas, and sanitary services, Gas production and distribution, Combination utility services, Electric and other services combined, and Gas and other services combined.

Arranger attributes:

(xiii) Reputable arranger dummy = 1 if the arranger is reputable, 0 otherwise.

5.2 Variable descriptions

Spread and fees are utilized as dependent variables and they are both priced as a spread

over LIBOR rate. Fees include commitment, utilization, facility, and prepayment paid

by the borrower to the creditor participants in loan syndication. The purpose of

including fees in the model is twofold. Firstly, the true cost of the borrowing from the

syndicated loan markets is captured only if both fees and spreads are included. One of

the major differences between bilateral and syndicated loans is the fact that borrowers

pay several extra fees in the process of issuance. Secondly, the inclusion of fee data

might allow one to investigate the level of moral hazard by arrangers - mostly large

reputable investment and commercial banks – by analysing whether they assist risky

borrowers by promoting them to potential lenders and charge higher fees in return.

Maturity, the secured loan dummy, and number of arrangers, are explanatory variables

relating to loan characteristics. Maturity is simply the lifetime of the loan in years.

Findings of earlier studies on the effects of maturity on loan spreads points to a negative

relationship between maturity and credit risk. Guedes and Opler (1996) argue that

riskier firms are willing to issue longer term debt in an attempt to avoid inefficient

liquidation. Firms issuing short-term debt can face costly liquidation at maturity

therefore firms facing financial stress are motivated to choose longer-term debt due to

refinancing risk. At the same time lenders prefer short term debt to control agency

problems, such as asset substitution and underinvestment (Gottesman and Roberts

2002). Consequently, longer term loans would bear higher spreads as the risk of the

borrower increases with uncertainty. Kale and Noe (1990) note that less risky firms

prefer to borrow shorter term loans to signal to the market that they are not facing costs

relating to agency problems. Flannery (1986) demonstrates that as a result of

asymmetric information costs, better quality borrowers consider their long term debt to

be underpriced and issue short maturity debt. In empirical studies, Dennis et al. (2000)

find that loan spreads decline with maturity. Kale and Noe (1990), Kleimeier and

Megginson (2000) and Coleman et al. (2002) all report a negative relation between

spreads and maturity. Gottesman and Roberts (2002), creating a sample of matched

pairs of different maturities made by the same lead and participant banks on the same

day to the same company, demonstrate that longer loans have higher spreads than

shorter loans. In sum the effect of maturity on the pricing of loans is generally not

found to be uniform in the academic literature; therefore the sign of this coefficient is

ambiguous.

If a loan is secured by a pledge of specific assets or equity of the borrower, the risk of

principal and interest default is likely to be lower, leading to lower yield spreads

(Angboza et al. 1998). On the other hand studies such as Battacharya and Thakor

(1993), Gottesman and Roberts (2002) and John et al. (2002) provide evidence that only

high risk borrowers have to pledge collateral. These finding posit that creditors view

collateral as a signal of higher risk. These borrowers require more monitoring (Berger

and Udell 1990) and hence they are charged higher spreads.

The number of arranger banks in the syndications varies relative to the size of the

issuance, and therefore this indicator is expected to have a high correlation with loan

size. A syndicate with a higher number of arrangers is expected to be large and involve

more participant (junior) banks. Preece and Mullineaux (1996) argue that large

syndicates (involving many participants) complicate loan restructurings and increase

contractual inflexibility because of the greater likelihood of hold-out problems among

syndicate members. As borrowers prefer greater contractual flexibility for

restructurings and are likely to be willing to pay a premium for this flexibility (Coleman

et al. 2002) the number of arrangers should be related negatively to the spread.

Alternatively, if the borrower follows a strategy to appoint a number of arrangers, either

because of the size of the issue, or because the arrangers’ reputation allows for more

creditor banks, then this strategy is expected to have an extra cost to the borrowing firm.

Firm Size is incorporated in the model to capture the impact of firm’s size on the cost of

the loan. Coleman et al. (2002) and Angboza et al. (1998) report a negative

relationship between firm size and spread. On the other hand, the impact of firm size is

measured by the size of the loan in studies such as Gottesman and Roberts (2002) and

Hubbard et al. (1999), both report insignificant results. In the sample used here loan

size is found to be highly correlated (r = 0.83) with firm size, therefore both variables

could be used to capture the size affect of the firm10.

Total debt to total assets is utilized to measure the impact of financial leverage on the

cost of borrowing. Coleman et al. (2002) and Esho et al. (1999) posit that a higher level

of financial leverage signify a lower credit quality (or a higher probability of default).

Conversely, Denis and Mihov (2003) argue that firms with higher leverage already have

a positive credit quality for their ability to fund a higher leverage; therefore a higher

leverage would lead to lower cost of borrowing. Hubbard et al. (2002), Coleman et al.

(2002) and Angboza et al. (1998) all provide evidence that a higher financial leverage

will lead to a higher spread.

Financial stress is measured by Short-term debt to total debt. Short-term debt includes

the maturity of debt shorter than 1 year. As suggested by Esho et al. (1999) the amount

of short term debt reflects the firm’s inability to have previously raised long term debt,

therefore deemed by the creditors to have a lower credibility. In such a case short term

debt to total debt is expected to be positively related to loan price. In contrast (and as

discussed above under maturity), it is argued that short-term debt exposes the firm to

refinancing risk which might lead to liquidation. Therefore the highest quality firms

that do not have to face refinancing risk will issue shorter term debt. If that is the case

then the coefficient of short-term debt to total debt should indicate a negative

relationship with the cost of funds.

Return on equity measures the firms’ ability to payback the loan. It is anticipated that a

higher profitability ratio by borrowers will lead to a lower cost of borrowing. Smith and

Watts (1992), Barclay and Smith (1995), Krishnaswami et al. (1999), and Denis and

Mihov (2003) employ the market to book ratio to measure the growth potential of the

firm. Hadlock and James (1997) argue that firms with higher growth option are the

ones with higher adverse selection cost and therefore creditors demand a greater return

for this11. In contrast Coleman et al. (2002) reports a negative relationship between

10 A correlation matrix of all variables is presented in Appendix 1. 11 Additionally Rajan (1992) argues that bank debt gives creditors an information monopoly that may be used to increase loan rates.

market to book value and spread; however they do not provide an explanation for this

finding.

Following Coleman et al. (2002), loan size, (the relative size of the facility to total

assets) is utilized to measure the loan concentration of the borrower. Coleman et al.

argues that this variable may proxy alternative sources of private and public debt

currently available to the firm, and suggest two alternative explanations for the relation

between loan concentration and spread. A low loan concentration ratio signals that

there are other debt holders or lenders monitoring the firm and that less monitoring may

be required on this loan, hence the spread will be lower. Alternatively (also argued by

Petersen and Rajan 1994) loan concentration may proxy the strength of the bank-

borrower relationship. The relationship becomes stronger when the borrower has a

good record. In this case loan concentration might lead to lower spreads.

The liquidation value of the borrowing firm is measured using the fixed to total assets

ratio as has been used in previous studies (Denis and Mihov, 2003; Johnson 1997; Esho

et al. 1999). A larger proportion of fixed assets act as collateral for the creditors in the

syndicated loan market where in case of a default the probability of recovering the loan

will be higher. Therefore the expected relationship between liquidation value and the

cost of the loan is negative.

Finally, the regulation dummy is employed to measure the impact of moral hazard on

the cost of borrowing within the firm12. Smith (1986) posits that asset substitution and

underinvestment occurs less in state regulated industries. Smith and Watts (1992) also

argue that compared to unregulated firms, those which are regulated are less likely to

engage in asset substitution and underinvestment because state utility commissions and

12 These industries are: Electric, gas, and sanitary services, Gas production and distribution, Combination utility services, Electric and other services combined, and Gas and other services combined. Regulated firms are selected by using SIC (these codes are four digit numerical codes assigned by the U.S. government to business establishments to identify the primary business of the establishment) codes, and firms with SIC codes between 4900 and 4939 are assigned the value of 1.The classification was developed to facilitate the collection, presentation, and analysis of data; and to promote uniformity and comparability in the presentation of statistical data collected by various agencies of the federal government, state agencies, and private organizations. The classification covers all economic activities: agriculture, forestry, fishing, hunting, and trapping; mining; construction; manufacturing; transportation; communications, electric, gas, and sanitary services; wholesale trade; retail trade; finance, insurance, and real estate; personal, business, professional, repair, recreation, and other services; and public administration.

other regulatory authorities supervise management's decisions. It is expected that firms

operating in a regulated industry will have higher credit quality since regulatory

oversight should decrease the level of asymmetric information and managerial moral

hazard. One would expect a negative sign on the regulation dummy variable.

5.3 Results

The results of the OLS regression that link the dynamics of firm financial structure and

the price of loan syndications are presented in Table 8. Spread (basis point over

LIBOR) and fees (basis point over LIBOR) are regressed separately with the selected

explanatory variables (Models marked as III and IV in Table 8 includes the dummy

variable for arranger reputation). Coefficients of the regressors respond in the same

way in terms of relation and significance in both models regardless of whether one

utilizes interest spread or fees (both basis points) as a dependent variable in the

regressions13 (also found by Angboza et al. (1998)].

Although maturity was expected to have a negative impact on loan price (that is longer

term loans should cost more) the coefficients of this variable is not significant in both

the spread and fees regressions. On the other hand, as also found by Yi and Mullineaux

(2003), Coleman et al. (2002), and Angboza et al. (1998), loan size has a significant

negative relationship with interest levels and fees. According to Angboza et al. (1998)

larger loans tend to be associated with large public borrowers and there is more public

information available regarding such borrowers. As such, default risk may be lower than

for smaller loans; leading to a lower yield spread.

13 An exception is liquidity which is insignificant in latter model.

Table 8: Loan and firm characteristics effects on pricing structure of syndicated loans

This table reports the OLS estimates of loan and firm characteristics regressed on spread and fees (both basis points over LIBOR) paid in the syndicated loan market by borrowers. Maturity is measured as years. Secured loan, dummy variable taking tha value of 1 if the loan is secured. Number of arranger is the total number of arranger banks involved in the syndication. Firm size is measured by log total assets (billions of dollars). Financial stress is measured by short term debt to total debt. Financial leverage is measured by total debt to equity ratio. Liquidation value is measured by fixed assets to total assets ratio. Profitability is measured by return on equity ratio. Market to book ratio is book value of assets minus book value of equity plus market value of equity. Regulation dummy takes the value of 1 if the firm operates in a state regulated industry. Reputable arranger takes the value of 1 is the arranger is a top investment bank. Specifications (III) and (IV) include dummy variables for arranger reputation.

(I) (II) (III) (IV)

Spread Fees Spread Fees

Maturity 0.11 0.09 -0.21 0.15

0.49 0.15 0.72 0.66

Secured Loan 53.38†

10.71†

52.78†

8.97†

4.22 0.87 4.18 1.39

Number of Arrangers 4.09†

0.32†

0.85 0.24

Firm size -25.35†

-3.38†

-24.94†

-2.97†

0.93 0.29 1.33 0.44

Financial Leverage 138.24†

19.66†

122.40†

15.83†

7.82 2.53 11.87 3.94

Financial Stress 1.57 -3.75 16.31‡

-2.96§

4.82 1.50 6.94 2.26

Profitability -145.17†

-20.39†

-115.00†

-18.50†

7.64 2.41 11.46 3.70

Market to Book Value -5.32†

-0.98†

-4.67†

-1.18†

0.72 0.22 1.15 0.38

Loan Size 36.14†

5.83†

49.27†

4.96†

3.61 1.28 8.52 2.61

Liquidation Value -10.48‡

-1.73 20.19‡

3.64

5.60 1.76 8.97 2.94

Regulation -21.25†

-1.96†

-29.89†

-3.38

4.21 1.23 9.46 2.91

Reputable Arranger -6.23§

0.03

3.77 1.24

Constant 227.89†

36.48†

239.77†

32.12†

5.94 1.96 10.30 2.84

Number of Observations 4839 3559 2341 1570

Prob > F 0 0 0 0

Adjusted R-Square 44.9 22.4 38.6 16.5†, §, and ‡ indicates 1%, 5% and 10% significance levels, respectively

Secured loans are charged higher interest rates and fees compared to unsecured loan as

found by Yi and Mullineaux 2003, Gottesman and Roberts (2002) and John et al.

(2002). In general riskier loans are secured by the borrower to be able to access the

market and attract new lenders. Although secured loans provide the ability of firms to

obtain funds from the market, creditors still view the borrower as risky and existence of

collateral does not help to reduce the cost of the loan.

The number of arrangers organizing the syndicated has a significant positive impact on

the spreads and fees, which does not confirm Preece and Mullineaux (1996) argument.

They posit that borrower’s contractual flexibility reduces as the number of creditors in

the deal increases; therefore the borrowers are ready to pay a premium for more

compact syndicates. The findings reveal that appointing more arrangers to be able to

attract more creditors comes to the borrower with a cost.

The coefficient of leverage has a significant positive relationship both with interest

spread and fees. Firms with higher debt liabilities in their balance sheets are required to

pay higher prices for obtaining funds from the syndications loan market. This result is

in-line with Coleman et al. (2002), Hubbard et al. (2002) and Esho et al.’s (1999)

findings and confirms that creditors relate higher leverage with higher credit risk and

ask for an extra premium.

In specification I, where the reputable arranger variable is not included, short term debt

to total debt ratio is found to be insignificant. However, in specification III (where the

reputable arranger variable is included) the coefficient of short term debt to total debt

ratio has a positive and significant sign. The major difference between specification I

and III is the number of observation in the two samples. Specification III only covers

those observations with a single arranger (whether the arranger is reputable or not) and

leaves out deals with multiple arrangers (due to the complexity in separating multiparty

arrangers as reputable and standard). As a consequence of this limitation, the size of the

loans in specification III are smaller than in specification I due to the fact that loans with

only a single arranger are (in general) smaller when compared to loans with more than

one arranger14. Therefore, the results, confirm the findings of Esho et al. (1999), and

suggest that in smaller size syndicates creditors assign a higher credit risk to borrowers

with higher shorter term liabilities and require a higher risk premium. Firms’ ability to

generate income, and therefore their ability to pay back debt, is measured by return on

14 Average loan size in specification III is $212 billion as compared to $546 billion in specification I. T-test for mean difference = -14.73, p < 0.000

equity which displays a negative association with both spread and fees. This result is

also found by Yi and Mullineaux (2003); borrowers generating higher returns on their

equity are expected to payback more comfortably and therefore awarded with lower cost

of funds.

Firms with growth potential, measured by market to book value, are found to pay lower

spreads and fees in the syndicated loan market and this result is in-line with Coleman et

al. (2002). Unlike Hadlock and James’ (1997) line of reasoning that growth potential

leads to more agency costs (underinvestment and asset substitution) which will be

penalized by creditors with higher costs reflecting uncertainty, firms with a potential for

growth pay lower spreads and fees. The desire of banks to increase business and

strengthen the bank-borrower relationship with firms that have a future growth

potential, provided that their monitoring abilities can tackle the potential agency issues,

might be a plausible explanation for lower spreads and fees charge.

The loan size to total assets ratio, measuring loan concentration, has a positive and

significant coefficient. Creditors charge higher prices if the size of the loan is large

relative to borrowers’ size. This result was not captured by Yi and Mullineaux (2002)

and Angboza et al. (1998) as they employ facility size (that is the size of the loan) to

gauge the impact of loan size on spreads. In contrast to their findings (Yi and

Mullineaux 2002 and Angboza et al. 1998), where loan size has a negative impact on its

cost, measuring facility size relative to firms’ size hints that a higher price is charged for

larger loans in relation to borrowers’ assets size. This result implies that firms with a

higher loan concentration ratio needs more monitoring and creditors charge a premium

for these costs. As expected, firms with higher liquidation value (measured by fixed to

total assets) pay lower interest spread and fees (as found by Coleman et al. 2002). A

larger proportion of fixed assets act as collateral for the creditors in the syndicated loan

market where in case of a default the probability of recovering the loan will be higher.

Firms operating in a regulated industry enjoy lower costs in the syndicated loan market

when compared to unregulated firms. Smith (1986), Smith and Watts (1992) and

Krishnaswami et al. (1999) have all argued that regulation lowers managerial moral

hazard. This result is partially confirmed in evidence presented here where regulated

firm are deemed to be less risky by the market and charged lower spreads and fees.

The explanatory variable capturing the impact of the number of arrangers has a

significant positive relationship both with loan spread and fees paid. Although the

number of arrangers and loan size have a high positive correlation (r = 0.50), their

coefficients have opposite signs (the signs of these variables’ coefficients do not differ

when the regressions are run excluding either of them). Therefore the results indicate

that borrowers are charged higher interest spreads and fees when the syndication

structure involves more lenders even though larger loans are priced cheaper.

The coefficient for the reputable arranger is only found to be significant and negatively

related to loan spreads but not fees. This result signifies that borrowers who tap

syndicated markets with the assistance of reputable arrangers pay lower spreads, and

therefore are better off when compared to firms working with “standard” agent banks.

On the other hand, although in the descriptive statistics (Table 7, p. 193) some evidence

was provided that firms using reputable arrangers pay lower spreads, regression results

do not confirm this conclusion for the whole sample. Overall, this particular result for

syndicated loans market differs significantly from the literature related to agency

reputation in bond underwriting (Fang 2005; Chemmanur and Fulghieri 1994; Booth

and Smith 1986; Klein and Leffler 1981; Shapiro 1983; Allen 1984), which argues that

a reputable underwriter provides lower yields for large bond issues in return for higher

fees.

6. CONCLUSION

This paper explores the nature of the concentrated lender and borrower structure of the

syndicated loan market from the perspective of pricing structure. Categorizing the

borrowers into groups according to asset size as well as credit ratings assigned by

Moody’s at the time of issuance, the interests spread and the fees paid by each group are

analyzed. Moreover, the relationship between firm financial attributes and price are

examined by means of OLS regressions. Additionally, the impact of arranger’s

reputation on loan pricing is also assessed.

Our results show that the typical US corporate customer in the syndicated loan market

has an asset size over $10 billion and is generally deemed to be carrying low risk by

credit rating agencies. Over 50% of the value all syndicated lending to US corporations

were assigned to low risk borrowers between 1993 and 2004 and 57% of all loans (in

real value) were extended to the largest borrowers. The pricing structure of syndicated

loans revealed that borrowers with larger liquidation values, superior repayment

potential, higher growth potential, low financial leverage, and those that operate in

regulated industries enjoy lower issuance costs. On the other hand, financially

distressed firms in need of larger funds relative to their size are found to be riskier and

charged higher spreads.

On the costs side, the analysis has shown that firm size has a significant impact on the

cost of funds. Although they are assigned the same credit rating by credit agencies and

therefore bear the same risk, large firms are charged significantly lower when compared

to smaller firms in the same risk category. In contrast, when the level of credibility

decreases, the large firms with the highest risk seem to access the market by paying an

extra premium when compared to smaller firms. The level of fees paid is found to be

decreasing inline with an increase in the credit quality of the borrower. However, as in

the case of spreads, for the borrowers carrying the same credit risk, larger firms are

charged significantly lower fees in comparison to smaller borrowers. Additionally,

firms are found to pay lower spreads by choosing reputable arrangers (although the

situation with regards fees is less clear cut).

Overall this study provides empirical evidence that large US firms are favoured in the

syndicated loan market. Firstly, they are charged significantly lower spreads relative to

smaller firms which have identical credit quality. Secondly, larger firms, possessing

higher credit risk, are allowed to access the market by paying an extra premium and by

paying higher fees to agent institutions. Policymakers should perhaps focus more

acutely on syndicated loan markets. They need to assure that large but financially

distressed firms, which seem to access the syndicated lending markets with ease, do not

take an exceedingly risk positions that may have systemic implications.

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APPENDIX 1

Table 9: Fees spread paid to loan syndications*This table presents descriptive statistics for fees (basis points over LIBOR) paid on loans by grouping borrowing firms by size and credit risk (rated by Moody's†) and arrangers by reputation. Small Firms → with total assets smaller than USD 1 billion, Medium Firms → with total assets between USD 1 billion and 10 billion, Large Firms → with total assets larger than USD 10 billion. Mean and median maturity is in years, mean and median interest are all basis points over LIBOR.

Loans by reputable arranger Loans by standard arrangerFirm Size

Statistics Small Medium Large All Firms Small Medium Large All Firms

Low Risk Mean 38 14 7 12 30 9 7 9(Aaa, Aa, A) Median 38 9 6 7 13 8 7 8

Std. Dev. 18 11 4 11 29 4 3 9Maximum 50 50 18 50 88 28 20 88


Std. Dev. 15 16 5 15 9 10 41 19Maximum 63 63 18 63 48 70 130 130

High Risk Mean 41 40 41 45 38 47 43(Ba, B) Median 38 38 38 50 38 50 38

Std. Dev. 22 19 22 23 17 23 21Maximum 150 75 150 150 100 75 150

Highes Risk Mean 51 53 51 48 74 56(Caa, Ca, C) Median 50 50 50 50 75 50

Std. Dev. 15 6 13 22 26 26Maximum 75 63 75 125 100 125

Total Mean 41 25 8 29 42 21 15 27Median 38 20 7 25 38 13 8 19Std. Dev. 21 18 4 22 23 20 22 24Maximum 150 75 18 150 150 100 130 150

†Moody's ratings: Aaa - gilt grade, Aaa - high grade, Aa - upper medium grade, Baa - medium grade, Ba - speculative elements, B - lacks characteristics of desirable investment, Caa - poor standing, Ca - speculative in a high degree, C - lowest rated. *Fees are basis points over LIBOR

APPENDIX 2Table 10: Correlation matrix for selected variables used in specification I

Sp

read

(b

asis

poi

nt

over

LIB

OR

)

Mat

uri

ty

Loa

n s

ize

(log

)

Tot

al a

sset

s (l

og)

Deb

t to

tot

al a

sset

s

Sh

ort-

term

deb

t to

to

tal d

ebt

Fix

ed t

o to

tal a

sset

s

Reg

ula

tion

du

mm

y

Ret

urn

on

eq

uit

y

Pri

ce t

o m

ark

et v

alu

e

Sec

ure

d lo

an d

um

my

Loa

n s

ize

to t

otal

deb

t

Nu

mb

er o

f ar

ran

gers

Spread (basis point over LIBOR) 1Maturity -0.0205 1Loan size (log) -0.4711 0.0436 1Total assets (log) -0.482 0.0441 0.8315 1Debt to total assets 0.2366 0.0157 0.0944 0.124 1Short-term debt to total debt -0.0058 0.0159 0.1208 0.1266 0.2662 1Fixed to total assets -0.0576 0.0334 0.1555 0.1851 0.266 0.2252 1Regulation dummy -0.1219 0.0103 0.1858 0.2958 0.1882 0.0514 0.3806 1Return on equity -0.405 0.0015 0.1916 0.1469 -0.2031 0.0373 -0.0136 0.0266 1Price to market value -0.2714 -0.0038 0.1616 0.1645 -0.1802 -0.0862 -0.1192 -0.1334 0.302 1Secured loan dummy 0.4507 -0.0483 -0.3835 -0.434 0.0708 -0.0258 -0.1151 -0.1401 -0.1993 -0.1545 1Loan size to total debt 0.1156 -0.0123 0.0131 -0.3131 -0.0455 -0.0677 -0.0476 -0.1126 -0.0192 0.0035 0.0972 1Number of arrangers -0.2036 0.0498 0.5218 0.5342 0.058 0.102 0.1154 0.1833 0.0917 0.0468 -0.2056 -0.1068 1

Number of observations =4389

APPENDIX 3

Table 11: Correlation matrix for selected variables used in specification II

Fee

s (b

asis

poi

nt

over

L

IBO

R)

Mat

uri

ty

Loa

n s

ize

(log

)

Tot

al a

sset

s (l

og)

Deb

t to

tot

al a

sset

s

Sh

ort-

term

deb

t to

tot

al

deb

t

Fix

ed t

o to

tal a

sset

s

Reg

ula

tion

du

mm

y

Ret

urn

on

eq

uit

y

Pri

ce t

o m

ark

et v

alu

e

Sec

ure

d lo

an d

um

my

Loa

n s

ize

to t

otal

deb

t

Nu

mb

er o

f ar

ran

gers

Fees (basis point over LIBOR) 1Maturity -0.0088 1Loan size (log) -0.3267 0.041 1Total assets (log) -0.3495 0.0322 0.8323 1Debt to total assets 0.1645 -0.0127 0.0722 0.1076 1Short-term debt to total debt 0.0413 -0.0015 0.0955 0.1041 0.2539 1Fixed to total assets -0.028 0.0217 0.1331 0.1793 0.2762 0.2204 1Regulation dummy -0.0633 0.0075 0.1686 0.2892 0.2273 0.0625 0.4127 1Return on equity -0.2765 0.0015 0.2202 0.1751 -0.186 0.0236 -0.0058 0.0127 1Price to market value -0.2122 -0.0147 0.1869 0.1796 -0.1709 -0.0856 -0.1369 -0.1684 0.3255 1Secured loan dummy 0.3566 -0.0405 -0.3983 -0.4566 0.0839 -0.0135 -0.1106 -0.1415 -0.2237 -0.1663 1Loan size to total debt 0.1072 0.0056 -0.0337 -0.3888 -0.04 -0.0876 -0.0801 -0.1386 -0.015 -0.0482 0.1507 1Number of arrangers -0.1542 0.0411 0.5048 0.5203 0.0498 0.0778 0.1012 0.1783 0.1085 0.0466 -0.2087 -0.1393 1

Number of observations = 3559

APPENDIX 4

Table 12: Correlation matrix for selected variables used in specification III

Sp

read

(b

asis

poi

nt

over

L

IBO

R)

Mat

uri

ty

Loa

n s

ize

(log

)

Tot

al a

sset

s (l

og)

Deb

t to

tot

al a

sset

s

Sh

ort-

term

deb

t to

tot

al

deb

t

Fix

ed t

o to

tal a

sset

s

Reg

ula

tion

du

mm

y

Ret

urn

on

eq

uit

y

Pri

ce t

o m

ark

et v

alu

e

Sec

ure

d lo

an d

um

my

Loa

n s

ize

to t

otal

deb

t

Rep

uta

ble

arr

ange

r d

um

my

Spread (basis point over LIBOR) 1Maturity -0.0226 1Loan size (log) -0.4476 0.0394 1Total assets (log) -0.4604 0.0456 0.7891 1Debt to total assets 0.208 0.0247 0.1133 0.1418 1Short-term debt to total debt -0.0456 0.0058 0.1198 0.122 0.2545 1Fixed to total assets -0.0248 0.0188 0.1463 0.1648 0.2275 0.2482 1Regulation dummy -0.0999 -0.0223 0.1292 0.2334 0.1455 0.0815 0.3323 1Return on equity -0.343 -0.0204 0.1774 0.1347 -0.2277 0.0397 0.0053 0.0162 1Price to market value -0.2301 -0.0004 0.1284 0.1867 -0.1893 -0.0918 -0.0701 -0.079 0.2456 1Secured loan dummy 0.438 -0.0453 -0.3654 -0.4332 0.0768 -0.0605 -0.1324 -0.1259 -0.2102 -0.1493 1Loan size to total debt 0.0829 -0.0341 0.1343 -0.361 -0.0051 -0.017 -0.0239 -0.112 0.0552 -0.0616 0.1336 1Reputable arranger dummy -0.0896 0.0123 0.1091 0.1244 -0.0202 -0.0041 -0.0315 -0.0197 0.0042 0.0639 -0.0484 -0.0441 1


APPENDIX 5

Table 13: Correlation matrix for selected variables used in specification IV

Fee

s (b

asis

poi

nt

over

L

IBO

R)

Mat

uri

ty

Loa

n s

ize

(log

)

Tot

al a

sset

s (l

og)

Deb

t to

tot

al a

sset

s

Sh

ort-

term

deb

t to

tot

al

deb

t

Fix

ed t

o to

tal a

sset

s

Reg

ula

tion

du

mm

y

Ret

urn

on

eq

uit

y

Pri

ce t

o m

ark

et v

alu

e

Sec

ure

d lo

an d

um

my

Loa

n s

ize

to t

otal

deb

t

Rep

uta

ble

arr

ange

r d

um

my

Fees (basis point over LIBOR) 1Maturity 0.001 1Loan size (log) -0.2727 0.0498 1Total assets (log) -0.278 0.0379 0.8032 1Debt to total assets 0.1615 -0.0069 0.0816 0.1027 1Short-term debt to total debt 0.0358 -0.0265 0.095 0.0968 0.2441 1Fixed to total assets 0.012 0.0026 0.1298 0.152 0.2222 0.2368 1Regulation dummy -0.0409 -0.0258 0.1276 0.2299 0.1602 0.0904 0.3584 1Return on equity -0.2481 -0.0128 0.2104 0.171 -0.2271 0.0463 0.0136 0.0085 1Price to market value -0.1984 -0.0165 0.1786 0.2248 -0.1643 -0.0819 -0.0635 -0.1027 0.2641 1Secured loan dummy 0.3025 -0.0409 -0.3974 -0.4768 0.087 -0.0533 -0.1137 -0.1249 -0.2394 -0.1856 1Loan size to total debt 0.0742 -0.0091 0.0673 -0.3946 0.0307 -0.0319 -0.0284 -0.1159 0.0111 -0.0843 0.1798 1Reputable arranger dummy -0.0475 0.0009 0.1334 0.1797 0.0203 -0.0052 -0.0009 -0.0082 0.0161 0.0875 -0.0723 -0.0863 1


Does Concentrated Arranger Structure In US Syndicated Loan Markets Benefit Large Firms?

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