Livingston - Moody's and S&P Ratings

8/6/2019 Livingston - Moody's and S&P Ratings

1/43Electronic copy available at: http://ssrn.com/abstract=1567665

Moody's and S&P Ratings: Are They Equivalent?

Conservative Ratings and Split Rated Bond Yields

Miles LivingstonUniversity of Florida and Erasmus University

P.O. Box 117168Gainesville, FL 32611-7168

Phone: (352) 392-4316Fax: (352) 392-0301

Jie (Diana) Wei*Office of the Comptroller of the Currency

Washington, DC 20219Phone: (202)874-6532Fax: (202) 874-5394

Lei Zhou

Northern Illinois UniversityCollege of Business

Department of FinanceDeKalb, IL 60115-2897Phone: (815) 753-7882Fax: (815) 753-0504

February, 2010

* The views expressed here are those of the individual authors alone and do not necessarily reflect those of theOffice of the Comptroller of the Currency or the Department of the Treasury.


2/43Electronic copy available at: http://ssrn.com/abstract=1567665



Abstract

We examine the relative impact of Moodys and S&P ratings on bond yields and find that atissuance yields on split rated bonds with superior Moodys ratings are, on average, 8 basis pointslower than yields on split rated bonds with superior S&P ratings. This pattern suggests thatinvestors differentiate between the two ratings and assign more weight to the ratings fromMoodys, the more conservative rating agency. Moody's ratings become relatively moreconservative after 1998 and the impact of a superior Moody's rating upon split rated bond yieldsis stronger. In addition, the differential impact of the two ratings on split rated bond yields ismore pronounced for Rule 144A issues, which are more opaque.


3/43

1



I. IntroductionMost publicly issued corporate bonds in the US receive ratings from two major rating

agencies, Moodys and Standard & Poors (S&P). About 50% of the time, the Moody's and the

S&P ratings are different at the notch level, resulting in so-called split ratings, with Moody's

more likely to have the conservative (lower) rating (Morgan, 2002, Van Roy, 2005).1

We show

that about 56% of split rated bonds have conservative Moodys ratings and investors differentiate

between these two ratings, especially during the period 1998-2008. When Moody's has the

superior (higher) rating, bond yields are approximately 8 basis points lower than when S&P has

the superior rating. Thus investors appear to hold Moodys reputation in higher regard than

S&Ps.

Split ratings and the differential impact of Moody's versus S&P are important for two

reasons. First, while virtually all public issues of bonds receive ratings from both rating agencies,

financial regulators generally do not differentiate between these ratings.2 Most rating-based

regulations require only one rating without specifying a particular rating agency (Cantor and

Packer, 1995, BIS, 2000). If the bond issue has multiple ratings, then either the highest or the

second highest rating is usually used regardless of which rating agency assigns the highest or

second highest rating (Cantor and Packer, 1995).3

In addition, under the Basel II framework,

1 See also Ederington (1986), Pottier and Sommer (1999), and Livingston et al. (2007).2 For a rating to be acceptable to regulators, the rating agency must be designated by the SEC as a nationallyrecognized statistical rating organization, or NRSRO. Moodys and S&P are both NRSROs.3 A notable exception to this general rule is that of the National Association of Insurance Commissioners (NAIC).In the case of split ratings, the NAIC can choose either the superior or inferior rating based on its own analysis(Cantor and Packer, 1996).


4/43

2

banks can choose to use either one or more rating agencies to risk-weight their credit exposures.

If a bank chooses to use one rating agency, it makes no difference whether it is Moodys or S&P.

If two rating agencies are used, the inferior of the two ratings determines the risk weights,

regardless of which agency assigns the inferior rating (Van Roy, 2005).

Second, many academic studies treat these ratings as interchangeable in spite of the fact

that Moody's and S&P ratings frequently disagree. Some studies use Moodys ratings as a proxy

for default risk (for example, Kidwell et al., 1984) while others use S&P ratings (for example,

Avramov et al., 2007). A few studies take advantage of both Moodys and S&P ratings, but use

the average of the two when they differ without regard to which rating is superior (for example,

Fenn, 2000). Another common practice is to use the Moodys (S&P) rating when it is available

and supplement with the S&P (Moodys) rating when the Moodys (S&P) rating is not available,

implicitly assuming that these two ratings are equivalent and interchangeable (for example, Yu,

2005, Butler, 2008).

This study uses a sample of 6,652 newly issued, split rated, non-financial US corporate

bonds from 1983 to 2008 to examine the relative impact of the two ratings on bond yields. By

focusing on split rated bonds, our analysis highlights the differences between Moody's and S&P

ratings. First, we confirm findings in earlier studies that Moodys is more likely to give a

conservative (or inferior) rating than S&P when these two differ. Second, when Moody's has the

superior rating, investors require lower yields, about 8 basis points on average, for split rated

bonds.4 Bond investors appear to differentiate between these two ratings and assign greater

4 The 8 basis points yield difference is statistically significant. While the sample size is very large, the statisticalsignificance is not just driven by the sample size. In a subsample of 1,291 Rule 144A bond issue, the yielddifference is also significant at the 1% level. In addition, we estimate the yield difference for each of the 33 splitrating categories. The yield differences are significant at the 1% or 5% level in 10 categories. The sample size forthese rating categories ranges from 26 to 643, indicating that the statistical significance is not a result of largesample size.


5/43

3

weight to the ratings from the more conservative agency. In addition, the differential impact of

the two ratings on bond yields is more pronounced for Rule 144A bond issues. As Rule 144A

issues are not registered with the SEC and have lower standards for disclosure, information about

them tends to be more opaque. Bond investors appear to be particularly concerned about the

information opaqueness of Rule 144A bond issues and therefore rely more heavily on the ratings

from the conservative rating agency in their assessment of default risk. Third, Moodys ratings

are relatively comparable to S&P ratings prior to 1998, but become more conservative than S&P

thereafter. Accordingly, the yield difference between bonds with a superior Moodys rating and

bonds with a superior S&P rating is minimal prior to 1998, but significantly larger (about 13

basis points) between 1998 and 2008.5 This evidence suggests that bond investors, mostly

institutional investors, are sufficiently sophisticated to detect evolving differences between the

two major rating agencies and act accordingly.

Furthermore, we also compare the yields for the sample of 6,652 split rated bonds to the

yields for a sample of 7,201 non-split rated bonds. Livingston and Zhou (2010) find that split

rated bonds average a 7-basis-point yield premium over non-split rated bonds of similar credit

risk and they attribute this yield premium to information opacity of split rated bonds. However,

they do not distinguish between splits with superior Moodys ratings and splits with superior

S&P ratings. We find that the yield premium is different in these two cases. When Moodys

(S&P) assigns the superior rating, the yield premium is much smaller (larger).

The main findings of the paper are summarized in Figure 1, which illustrates the yield

premiums assigned to split rated bonds over non-split rated bonds. When no distinction is made

5 Blume et al. (1998) find that S&P tightens rating standards and its ratings become more stringent from 1978 to1995. However, the study does not compare S&P ratings with Moodys ratings. Furthermore, the Blume et al.study covers a time period from 1978 to 1995, while we find Moodys becomes more conservative (relative to S&P)after 1998. Thus, our findings do not contradict those of Blume et al. (1998).


6/43

4

between splits with superior Moody's ratings and splits with superior S&P ratings, split rated

bond issues have an average yield premium of approximately 6.5 basis points above the average

of yields for non-split superior rated and non-split inferior rated bonds, similar to findings in

Livingston and Zhou (2010). When Moody's has the superior rating, the yield premium is only 2

basis points. Conversely, the yield premium is 10 basis points if S&P has the superior rating.

The difference in the yield premium, 8 basis points, indicates that yields on split rated bonds with

superior Moodys ratings are, on average, 8 basis points lower than those with superior S&P

ratings.

In order to put the 8-basis-point yield spread difference into perspective, we estimate that

the average yield spread difference between two adjacent notch rating categories is about 30

basis points. Thus, a yield difference of 8 basis points is approximately equivalent to a

difference of one fourth of a notch rating. Furthermore, for a typical split rated bond in our

sample, the 8-basis-point difference in yield spread translates to a difference of $1.42 million in

price.6

This study has two important implications. First, it calls into question the common

practice by financial regulators and by academic studies to treat the two major ratings equally.

While we do not advocate using one rating agency versus the other, regulators should

continuously monitor the performance of each rating agency. Although regulatory agencies in

many countries set criteria for eligible credit rating agencies for regulatory purposes, only three

countries (France, Italy and Japan) have ongoing monitoring of the recognized rating agencies

(BIS, 2000). In the US, once a rating agency is recognized as an NRSRO by the SEC, there is no

monitoring of the performance of the rating agency and no formal mechanism to strip its

6 For the 1998-2008 subsample period, the yield spread difference is about 13 basis points, equivalent to a differenceof half a notch rating or $2.3 million in price difference for a typical split rated bond.


7/43

5

NRSRO status. To increase the competition in the rating industry, the SEC has significantly

increased the number of NRSROs from three in 1975 to currently ten.7

The papers findings on

the evolving relative conservativeness of different rating agencies suggest that rating agencies

may not consistently maintain the quality of their ratings. Conceivably, some rating agencies

might, after being designated as an NRSRO, sell their SEC-sanctioned ratings to maximize

current profits. Thus, the SEC should not only be the gate-keeper of the NRSRO status, but

should also be the rater of the raters.

Second, the findings in this paper suggest that bond investors are quite sophisticated and

differentiate between the two major rating agencies. Our findings also highlight the importance

for rating agencies to protect their reputational capital. If one rating agency consistently

becomes more lenient (conservative) over time, bond investors will gradually adapt to such

changes by putting less (more) weight on that agencys rating in their assessment of default risk.

This finding supports the argument that rating agencies have strong incentives to issue honest

and accurate ratings to protect their reputation capital (Smith and Walter, 2002, Covitz and

Harrison, 2004). Such concerns for reputation capital can offset or mitigate the potential

conflicts of interest when rating agencies are paid by issuing firms.

The remainder of the paper is organized as follows. Section II summarizes the previous

literature, and Section III describes the data and provides summary statistics. Section IV

analyzes the differential impacts of Moody's and S&P ratings upon yields of split rated bonds.

Section V compares yields of split rated and non-split rated bonds. Section VI concludes the

paper.

7 The SEC website lists the ten NRSROs (http://www.sec.gov/answers/nrsro.htm).


8/43

6

II. Background and Literature ReviewGiven the dominance of the two major rating agencies, several studies compare Moodys

and S&P ratings. Ederington (1986) examines determinants of the two ratings for US corporate

bonds from 1975 to 1980. His study finds that the two rating agencies use a common set of

factors such as firm size and leverage ratio to estimate credit risk, and they assign similar

weights to these factors. In addition, there is no systematic difference in the rating scales used

by the two major rating agencies. Thus, Ederingtons (1986) findings suggest that the two

ratings are basically equivalent, implying that differences in the two ratings are merely random

errors. According to Ederington, the respective positions of the two agencies could easily have

been reversed; i.e., on another day or with a slightly different set of analysts, either agency might

assign a different rating. We call this view the rating equivalence hypothesis.

An implication of the rating equivalence hypothesis is that yields on split rated bonds

should be the same regardless of which rating agency assigns a superior rating. In other words, a

bond rated A+ by Moodys and A by S&P should have the same yield as another bond rated A

by Moodys and A+ by S&P.

Other studies, however, suggest that there are systematic differences between the two

rating agencies. Moon and Stotsky (1993) find that the two rating agencies use different

economic variables to determine ratings on municipal bonds. In addition, they find that the

rating scales of the two agencies differ systematically.8 Similarly, in a study of financial strength

ratings of property liability insurance companies by A.M. Best, Moodys and S&P, Pottier and

Sommers (1999) find that the three rating agencies use different factors in modeling an insurers

8 Note that these results should be treated with caution. Moon and Stotsky (1993) use outstanding municipal bondsin their study. Observed split ratings for outstanding bond issues might be caused by asynchronous changes inratings over time rather than by systematic difference between the two rating agencies.


9/43

7

financial strength, suggesting that different ratings convey different information and may not be

equivalent.

In addition to the empirical comparison of the two rating agencies, a survey study by

Baker and Mansi (2002) investigates the attitude of issuing firms and investors toward the rating

agencies. The study reports that issuing firms believe S&P ratings are more accurate than

Moodys, while investors do not see a difference. This finding is not a surprise since S&P tends

to assign superior ratings compared to Moodys. On the other hand, investors believe that

corporate bond prices more closely follow Moodys rating than S&P rating.9 This study

suggests that both investors and issuing firms perceive these two ratings differently. Consistent

with Baker and Mansis (2002) survey results, Gttler and Wahrenburg (2007) find that Moodys

updates its ratings to reflect changing default risk in a timelier manner than S&P.

Recent studies on split ratings also indicate that there might be systematic differences

between the two rating agencies. Morgan (2002) suggests that split ratings are caused by asset

opacity of issuing firms. He further argues that split ratings are likely to be lopsided; that is, one

rating agency will be more likely to assign a superior rating than the other, if asset opacity is the

cause of the split rating. On the other hand, split ratings should be symmetric if split ratings are

merely random errors. Morgan's idea is that the two rating agencies may not worry equally

about over-rating. When severe asset opacity problems exist, the more conservative rating

agency (or the agency that worries more about over-rating than under-rating) tends to assign an

inferior rating. Indeed, Morgan (2002) finds that Moodys ratings for banking firms are more

likely to be inferior compared to S&P ratings when the two differ. Livingston et al. (2007) and

Pottier and Sommers (1999) report similar patterns for corporate bond ratings and financial

9 The survey asks the following question: How would you rank the following rating agencies in terms of howclosely their ratings of corporate bonds compare to where these bonds actually trade? It only asks investors thisquestion.


10/43

8

strength ratings of insurance companies respectively. These findings suggest that Moodys is

more conservative and less likely to over-rate a bond issue. An empirical study of rating

accuracy by Gttler (2005) supports this view. The study finds that Moodys ratings are slightly

better at predicting default than S&P ratings. We call this view the systematic difference

hypothesis.10

An implication of the systematic difference hypothesis is that split rated bonds with

superior ratings from the more conservative rating agency should have lower yields if bond

investors differentiate between these two ratings. Thus, in examining the yields on split rated

bonds, we perform a joint test that 1) there is a systematic difference between the Moodys and

S&P ratings, and 2) bond investors differentiate between these two ratings.

This study is also linked to another line of research on the impact of split ratings on bond

yields. Some studies find that inferior ratings determine yields on split rated bonds (Billingsley

et al., 1985, Liu and Moore, 1987, Perry et al., 1988); others find that the superior ratings set

bond yields (Hsueh and Kidwell, 1988, Reiter and Ziebart, 1991). None of the studies, however,

distinguish split rated bonds with superior Moodys ratings from those with superior S&P

ratings. More recent studies find that both the superior and inferior ratings have an impact on

yields (Cantor et al., 1997, Jewell and Livingston, 1998). In addition, Livingston and Zhou

(2010) find that split rated bondsaverage a 7-basis-point yield premium over non-split rated

bonds of similar credit risk. Again, these studies do not test whether a superior rating from one

particular rating agency has a different impact on yields than a superior rating from another

rating agency.

10 Note that the systematic difference between the two rating agencies might be caused by 1) different rating scales,2) different weights assigned to risk factors, 3) relative costs of over-rating vs. under-rating. Regardless of theunderlying cause, systematic difference hypothesis suggests that one rating agency will be more conservative, thatis, more likely to assign inferior ratings than the other.


11/43

9

III. Data Collection and DescriptionWe collect data on fixed rated, US domestic, non-financial public and Rule 144A

corporate bond issues from the Thomson Financial SDC database. We use the data on original

bond issues for two reasons. First, bond ratings on new issues reflect the most up-to-date

information about the issuers.11 Second, split ratings on existing bond issues can be caused by

asynchronous changes in ratings by the two rating agencies in response to changes in underlying

default risk.12 Thus, split ratings on outstanding bonds may merely be the result of slow

updating by one agency instead of a systematic difference between the two ratings.

The sample period covers 1983 to 2008. We start in 1983 because Moodys began

issuing notch ratings after April 1982, in addition to letter ratings.13 Perpetual bonds, bonds

with credit enhancements, and putable bonds are excluded. We also exclude several issues that

are rated CCC- by at least one rating agency.14 The final sample consists of 13,853 bond issues

comprising 7,201 non-split rated issues and 6,652 split rated issues. All split rated bonds in the

sample have Moodys and S&P ratings that differ by one or two notches.15

Table 1 describes the sample. Non-split rated bonds have average maturity similar to

split rated bonds but slightly smaller issue size.16 The non-split rated sample has an average

original yield to maturity (YTM) of 7.86%, slightly lower than that of the split rated sample. To

make yields comparable between bonds of different maturities, we subtract the yield for Treasury

11

Some research has found that rating agencies tend to lag financial markets in reflecting new information(Holthausen and Leftwich, 1986, Ederington and Goh, 1998).12 Gttler and Wahrenburg (2007) document a lead-lag relation between the ratings of Moodys and S&P.13 S&P started to issue notch ratings in 1974 (Cantor and Packer, 1995).14 We exclude these issues as a data quality filter. It is highly unlikely that firms with a CCC- rating are able toaccess the public bond market. Inclusion of these issues in our sample does not, however, change our results.15 We exclude issues with three or more notches of split ratings because there are very few observations in each ofthese distinct rating combination categories.16 Investment grade bonds have an average maturity of 13.9 years while below-investment grade bonds have anaverage maturity of 9.4 years. This suggests that high quality firms are more likely to issue longer term bonds.


12/43

10

securities of similar maturity from the yield to maturity of each bond to calculate the Treasury

Spread. The average Treasury Spread is slightly lower for the non-split rated sample, but there is

no difference between the superior S&P rating subsample and the superior Moodys rating

subsample.

To summarize the credit quality of the sample, we create two numerical rating variables:

Moodys Rating and S&P Rating. Both variables range from 1 (for CCC) to 18 (for AAA). The

Average Rating is the average of Moodys and S&P Ratings. The Average Rating for non-split

rated bonds is 10.33, slightly above BBB, higher than the Average Rating for split rated bonds.

This is consistent with findings in Livingston et al. (2007). The split rated sample has an average

Moodys Rating of 9.87, lower than the average S&P Rating of 10.01, meaning that Moody's

gives an inferior (lower) average rating.

For each bond issue, we also calculate the Rating Difference, or Moodys Rating minus

S&P Rating. The average Rating Difference of the split rated sample is -0.14, statistically

significant at the 1% level. In other words, Moodys Rating is, on average, 0.14 notches below

the S&P Rating when the two ratings differ. In addition, 55.5% of the split rated issues in our

sample (3,691) have superior S&P ratings and 44.5% of the issues (2,961) have superior

Moodys ratings. These findings suggest that Moodys is more conservative than S&P,

consistent with Morgan (2002) and Livingston et al. (2007).

IV. Empirical Analysis of Split Rating Sample

In this section, we examine the yields on split rated bond issues. Specifically, we

compare yields on split rated bonds with superior Moodys ratings to the yields on split rated

bonds with superior S&P ratings.


13/43

11

1. Univariate Analysis

The summary statistics suggest that Moodys is, on average, more likely to assign a more

conservative rating than S&P. This section examines whether this pattern holds true for bonds of

different credit quality. First, we create 33 distinct rating categories, ranging from AAA/AA+ to

CCC+/CCC, based on the combination of the two ratings.17 For each rating category, we

distinguish between those with superior Moodys ratings and those with superior S&P ratings.

Figure 2 depicts the number of split rated bonds with superior Moodys ratings and the number

of splits with superior S&P ratings in each rating category. In 25 out of the 33 rating categories,

there are more issues with superior S&P ratings than issues with superior Moodys ratings.

Interestingly, for the 8 rating categories with more issues of superior Moodys ratings, 5 are

below-investment grade, consistent with our earlier finding that the Average Rating for issues

with superior Moodys ratings is slightly lower. This pattern might be explained by the fact that

the Moodys rating incorporates both the probability of default and the expected recovery rate,

while the S&P rating is strictly a measure of default risk (BIS, 2000). This difference has little

impact on investment grade bonds, but might create systematic differences between the two

ratings for below-investment grade bonds.

Figure 2 and the summary statistics confirm the findings in previous studies that Moodys

is more likely to give conservative ratings than S&P when these two differ. The next logical

question is whether this conservative tendency in Moodys rating is recognized by bond

investors and reflected in lower bond yields. Table 2 reports the average treasury spread for each

rating category of the split rated sample, as well as two sub-samples: those with superior

Moodys ratings and those with superior S&P ratings. In 20 out of the 33 rating categories, the

17 Moodys and S&P use slightly different rating notation but they are generally thought to be equivalent. Forexample, S&Ps BBB+ corresponds to Moodys Baa1. Following other studies, we use the S&P rating notation inthis paper.


14/43

12

superior Moodys rating sub-samples have lower treasury spreads than the superior S&P rating

sub-samples, and the differences are significant in 9 rating categories. For example, in the A+/A

split rating category, bonds with superior S&P ratings (S&P rated A+, Moodys rated A) average

a treasury spread of 94.14 basis points, while bonds with superior Moodys ratings (S&P rated A,

Moodys rated A+) average a treasury spread of 82.78 basis points, an 11-basis-point difference

with high statistical significance. Only in three rating categories do superior Moodys rating sub-

samples have significantly higher treasury spreads. These findings indicate that bond investors

differentiate between these two bond rating agencies and require lower yields when Moodys

assigns a superior rating.

2. Multivariate Analysis

This section examines yields on split rated bonds using multivariate regressions. The

dependent variable is the Treasury Spread (that is, the yield to maturity minus Treasury yield).

The explanatory variables include rating dummy variables and control variables. The test

variable is a dummy variable, SUPMOODY, set equal to one for issues with a superior Moodys

rating and zero otherwise. Thus, the base case is split rated bonds with a superior S&P rating. If

bond investors require lower yields for issues with a superior Moodys rating, the coefficient on

SUPMOODY should be significantly negative.

a. Control Variables


15/43

13

Previous studies have shown that many factors other than default risk can have an impact

on treasury spreads.18

Thus, three sets of control variables are included in addition to the bond

ratings: controls for different bond features, controls for registration types, and controls for

market conditions.

To control for differences in bond features, we include the MATURITY, PROCEEDS,

SENIOR dummy, CALL dummy, and UTILITY dummy variables in the regression models.

MATURITY is the natural log of years to maturity. Previous studies find that yield spreads vary

with bond maturity (for example, Kidwell et al., 1984, Chaplinsky and Ramchand, 2004).19

PROCEEDS is the total dollar proceeds of the bond issue. Large issues of bonds are usually

more liquid than small issues and consequently investors may require lower rates of return for

large issues of bonds. Hence, we expect the coefficient for PROCEEDS to be negative. A

SENIOR dummy is set equal to one if the issue is senior debt, and zero otherwise. Since senior

debt is less risky than subordinated debt, the coefficient for the SENIOR dummy is anticipated to

be negative. The CALL dummy variable is set equal to one if the bond is callable and zero

otherwise. We expect the coefficient for this variable to be positive because callable bonds are

riskier for investors. The UTILITY dummy equals one if the issuer is a utility firm and zero

otherwise.

We also include SHELF dummy and R144A dummy variables to control for different

methods of bond registration. SHELF equals one for shelf registered issues and zero otherwise.

R144A equals one for Rule 144A issues and zero otherwise. Kidwell et al. (1984, 1987) show

that shelf-registered bonds have lower yields. Thus, we expect the coefficient for the SHELF

18 For example, Houweling et al. (2005) finds a liquidity premium on corporate bonds. Fenn (2000) shows that issuesize and maturity have an impact on bond yield. Kidwell et al. (1984, 1987) document lower yields for shelf-registered bond issues.19 As a robustness check, we also run the regression models without the MATURITY variable. The results do notchange materially. Different specifications of the variable do not affect the results either.


16/43

14

dummy to be negative. Studies on Rule 144A issues find higher yields on Rule 144A issues than

non-Rule 144A issues (see Livingston and Zhou, 2002, Chaplinsky and Ramchand, 2004). Thus,

we include this dummy as a control variable.

Finally, since the bond default risk premium fluctuates with overall market conditions, a

RISKPREM variable is included in the regression to control for changes in the market default

risk premium. The RISKPREM is defined as the difference between the Moodys AAA

Corporate Bond Index Yields (obtained from the Federal Reserve website) and yields for 10-year

Treasury securities. The coefficient for this variable is expected to be positive. Other variables

to control for market conditions are a series of zero/one year dummy variables with 2008 as the

base case.

b. Main Regression ResultsIn Table 3, Model 1 uses the sample of split rated bonds to study whether splits with a

superior Moodys rating have a lower treasury spread than splits with a superior S&P rating. The

coefficient on SUPMOODY is -8.38 and significant, indicating that yields on bonds with a

superior Moodys rating average about 8 basis points lower than yields on bonds with a superior

S&P rating.20 The coefficients on most control variables have the expected signs with the

exception of the SENIOR dummy variable.21

In Model 2, we distinguish one-notch splits and two-notch splits by creating two test

dummy variables: SUPMOODY1 and SUPMOODY2. SUPMOODY1 (SUPMOODY2) equals

one for one-notch (two-notch) split rated bonds that have a superior Moodys rating and zero

20 Multiple bond issues by the same issuing firm may create a clustering problem (Wooldridge, 2002, 2003). Weuse the Cluster option in STATA to adjust for the potential clustering problem and report the cluster-robust p-values.21 The significantly positive coefficient for the SENIOR dummy variable indicates that senior bonds have higheryields, a counter intuitive result that may be caused by a tendency for rating firms to give senior bonds unjustifiedhigher ratings (John et al., 2010). Fridson and Garman (1997) and Fenn (2000) have similar findings.


17/43

15

otherwise.22 Livingston and Zhou (2010) find that multiple-notch split ratings are stronger

signals of information opacity and bond investors require higher yield premiums on multiple

splits than on one-notch splits. With greater information opacity and uncertainty, bond investors

are likely to be concerned about the accuracy of ratings and more worried about over-rating. If

Moodys is recognized by investors as a more conservative rating agency, superior Moodys

ratings will lower yields for two-notch split rated bonds more than for one-notch split rated

bonds. The empirical results confirm this conjecture. The coefficient on SUPMOODY1 notch is

-7.64 while the coefficient on SUPMOODY2 is -12.60; both of them are statistically significant.

Model 3 distinguishes between notch split rated bonds and letter split rated bonds by

creating two other test dummy variables: SUPMOODY_Notch and SUPMOODY_Letter.

SUPMOODY_Notch (SUPMOODY_Letter) equals one for notch (letter) split rated bonds that

have a superior Moodys rating and zero otherwise.23 Rating splits at the letter level may

indicate greater uncertainty and investors may be more worried about rating accuracy. As a

result, we expect that a superior Moodys rating may lower yields more when the two ratings

differ at the letter level than at the notch level. The coefficient on SUPMOODY_Letter, -13.75,

is much larger in magnitude than the -5.89 coefficient on SUPMOODY_Notch. In addition, the

coefficient on SUPMOODY_Notch is only marginally significant, while the coefficient on

SUPMOODY_Letter is significant at the 1% level.

Finally, to check if the results are driven by only a few credit rating categories, the Model

1 regression is run for each split rating category without the rating dummy variables. Table 4

reports the coefficient on SUPMOODY for each regression. The coefficient is negative in 26 out

22 Among the split rated sample, 83.87% (5,579) are one-notch splits and 16.13% (1,073) are two-notch splits.23 There are 2,158 letter split rated issues. Among them, 694 are two-notch splits and 1,464 are one-notch splits.Among the 4,494 notch split rated issues, 379 are two notch splits and 4,115 are one-notch splits.


18/43

16

of the 33 rating categories and is significant at the 1% or 5% level in 10 categories.24 In addition,

6 of the 10 significant rating categories are letter split ratings, consistent with the earlier finding

that a superior Moodys rating causes a larger reduction in yields for letter splits. On the other

hand, the coefficient is positive and marginally significant in only one rating category

(BB+/BB).25 These findings indicate that investors consistently require lower yields for bonds

with superior Moodys ratings.

c. Evolution of Conservative Ratings and its Impact on Treasury SpreadOur sample period spans 26 years. It is very plausible that the relative conservative

tendencies of the two rating agencies may evolve during such a long time period. This section

investigates the changing relative rating conservativeness and its impact on bond yields.

We first break the split rated sample into two time period sub-samples: 1983-1997 and

1998-2008.26 For the earlier period, the average Moodys Rating and S&P Rating are virtually

the same: 10.458 and 10.463 respectively. In addition, 49.6% of issues have conservative (lower)

Moodys ratings. On the other hand, for the latter period, the average Moodys Rating is 9.275,

significantly lower than the average S&P Rating of 9.551. Furthermore, the percentage of issues

with conservative (lower) Moodys ratings increases to 61.4%. Thus, the Moodys ratings are

not systematically higher or lower than the S&P ratings in the earlier period, but become more

conservative in the late 1990s and 2000s.

24 6 of the 10 rating categories with significant coefficients on SUPMOODY have fewer than 100 observations.This suggests that the statistical significance for the main results in Table 3 is not just driven by the large samplesize.25 To save space, we do not report regression results for control variables. Results are available upon request.26 We choose 1998 as the cutoff year so that the two sub-samples have roughly the same number of observations.We have also broken the sample into two 13-year periods by using 1996 as the cutoff year and the results arequalitatively the same.


19/43

17

If bond investors are cognizant of the evolving relative conservativeness of the two rating

agencies, the earlier (latter) period should exhibit smaller (greater) yield differences between

issues with superior and inferior Moodys ratings. To check this hypothesis, we run the main

regression (Model 1) for each of the two time period sub-samples and report the results in the

first two columns of Table 5. The coefficient on SUPMOODY is -4.57 and only marginally

significant for the 1983-1997 sub-sample. On the other hand, the coefficient on SUPMOODY is

-13.37 and highly significant for the 1998-2008 sub-sample, suggesting that our main results are

largely driven by the latter sample period, where Moodys is significantly more conservative

than S&P.

In addition to the sub-sample analysis, we also run the main regression on the full split

rated sample with an interaction term between the SUPMOODY and a Time Trend variable,

which is defined as issue year minus 1982. With the interaction term in the regression, the

coefficient on SUPMOODY becomes positive (3.94) though not significant. The coefficient on

the interaction term is -0.83 and significant at the 1% level.27 This finding indicates that bond

investors gradually differentiate between the two rating agencies as one agency becomes more

conservative than the other over time.28

The preceding results suggest that bond investors are sophisticated and can detect subtle

differences between the two major rating agencies and act accordingly. Thus, these findings also

highlight the importance for the rating agencies to protect their reputational capital. If one rating

agency consistently becomes more lenient (conservative) over time, bond investors will

27 For the sake of brevity, we do not report the complete regression results, but they are available upon request.28 We also run separate regressions for each year and the results are consistent with the main findings. For the 15years prior to 1998, the coefficient is negative and significant at the 1% or 5% level in only 2 years (1992 and 1995).For the 11 years in the latter period, the coefficient is significantly (at the 1% or 5% level) negative in 5 years. Inaddition, the magnitude of the coefficients is larger in more recent years than in earlier years.


20/43

18

gradually adapt to such changes by putting less (more) weight on that agencys rating in their

assessment of default risk.

d. Conservative Ratings and Rule 144AAn interesting development in the US bond market since the early 1990s is the significant

growth of Rule 144A issues. Rule 144A issues are not registered with the SEC but can be traded

among large institutional investors, or Qualified Institutional Buyers (QIB).29

Due to the lack of

registration and lower standards for disclosure, there may be greater information opacity

problems for Rule 144A bond issues.

30

Indeed, Livingston and Zhou (2002) report that over half

of Rule 144A bonds in their sample are issued by firms accessing the bond market for the first

time and almost a quarter of the issuing firms do not file periodic disclosures with the SEC.

Thus, bond investors are forced to rely more heavily on bond ratings to assess the default risk of

Rule 144A issues. In addition, information opacity problems may also decrease the accuracy of

bond ratings on Rule 144A issues and, as a result, bond investors will tend to be more concerned

about over-rating if the two major ratings split. Hence, we expect that more conservative ratings

will have a greater impact on yields of split rated Rule 144A issues.

To check this hypothesis, we utilize the 1998-2008 subsample of split rated bonds.31 We

break the sample into Rule 144A and non-Rule 144A issue subsamples and estimate the main

regression (Model 1) for the two subsamples separately. The regression results are reported in

the last two columns of Table 5. For Rule 144A issues, the coefficient on SUPMOODY is -22.81,

29 See Fenn (2000) and Livingston and Zhou (2002) for more details about Rule 144A issues.30 Lack of disclosure or lower quality of disclosure may lead to information opacity problems. Alternatively, firmswith information asymmetry problems may prefer to issue in the Rule 144A market.31 Rule 144A was first adopted in 1990 and the market grew significantly in the late 1990s. Indeed, most Rule 144Aissues in our sample are from the 1998-2008 sub-sample. We have also used the full sample of split rated bonds toexamine this issue and the results are similar. However, using the full sample introduces bias because most Rule144A bonds are issued in the latter time period, a period where, as documented in the previous section, Moodys ismuch more conservative than S&P and the impact of rating conservativeness on bond yields is more significant.


21/43

19

much larger in magnitude than its counterpart for the non-Rule 144A bonds, -7.02. This

evidence suggests that bond investors are particularly concerned about rating accuracy on bond

issues with severe information opacity problems and place greater trust in the ratings from the

conservative rating agency.

e. Economic SignificanceWhile the previous sections find the yield difference between bonds with superior

Moodys and superior S&P ratings statistically significant, this section estimates the economic

significance of the yield difference. We take two approaches to gauge the economic significance.

First, we compare the 8-basis-point (13-basis-point) yield difference for the whole sample (the

1998-2008 subsample) to the average yield difference between two adjacent notch rating

categories. We estimate, in Section V, that the average yield difference between two adjacent

notch rating categories is about 30 basis points. Thus, a yield difference of 8 (13) basis points is

approximately equivalent to a difference of 1/4 (1/2) of a notch rating. Second, we estimate how

much the bond price will differ due to the 8-basis-point (13-basis-point) yield difference for a

typical split rated bond in our sample. Table 1 reports that the average size of split rated bonds

in our sample is $235 million, with an average maturity of 12.6 years and yield to maturity of

8.18%. The modified duration for the average bond is approximately 7.5. Thus, a yield

difference of 8 (13) basis points translates to a price difference of 0.6% (0.98%), or $1.42 ($2.30)

million.


22/43

20

V. Conservative Ratings and Information Opacity Premiums

The previous section compares the yields on split rated bonds with superior Moodys

ratings to those with superior S&P ratings. A follow up question is how the yields on these two

different types of split rated bonds compare to non-split rated bonds. Livingston and Zhou (2010)

document a 7-basis-point yield premium on split rated bonds over non-split rated bonds of

similar credit quality and they attribute the yield premium to the information opacity of split

rated bonds. However, they do not distinguish between those with superior Moodys ratings and

those with superior S&P ratings. Our findings of lower yields on splits with superior Moodys

ratings suggest that the information opacity premium varies between splits with superior

Moodys ratings and splits with superior S&P ratings.

Using the methodology of Livingston and Zhou (2010), we estimate the information

opacity premiums for split rated bonds with superior Moody's ratings and for split rated bonds

with superior S&P ratings. The methodology is described in detail in Appendix A. This

methodology uses two treasury spread regression models to estimate the information opacity

premium. Each model is run with both split rated and non-split rated bonds, allowing a measure

of the impact of split ratings on treasury spreads.

In the first model, called the superior rating model, treasury spreads (for the full sample

of non-split rated bonds and split rated bonds) are regressed against rating dummy variables,

control variables, and a split rating dummy variable. For split rated bonds, the superior of the

two ratings is used to construct the rating dummy variables. Thus, the split rating dummy

variable reflects the fact that a split rated bond has an inferior second rating not captured by the

rating dummy variables. The coefficient on the split rating dummy variable can be interpreted as


23/43

21

the difference between the actual treasury spreads of split rated bonds and the estimated treasury

spreads of these bonds if both rating agencies had assigned the same superior rating.

The process is reversed in the second regression model, called the inferior rating model.

For the full sample of non-split rated and split rated bonds, the treasury spread is regressed

against rating dummy variables, control variables, and a split rating dummy variable. For split

rated bonds, the inferior of the two ratings is used. Thus, the split rating dummy variable reflects

the fact that a split rated bond has a superior second rating compared to the non-split rated bonds.

The coefficient on the split rating dummy variable can be interpreted as the difference between

the actual treasury spreads of split rated bonds and the estimated treasury spreads if both rating

agencies had assigned the same inferior rating.

Finally, the difference of the absolute values of the coefficients on the split rating dummy

for the superior rating model and the inferior rating model is divided by two to arrive at the

information opacity premium. The logic of this is explained in the Appendix.

We first replicate Livingston and Zhous (2010) main findings on our whole sample (of

both split rated bonds and non-split rate bonds) in Table 6.32 The coefficients on the split rating

dummy variable from the superior and inferior rating models are 24.80 and -11.76 respectively,

suggesting an information opacity premium of 6.5 basis points (that is, [24.80-11.76]/2). This is

very similar to the 7-basis-point premium reported in Livingston and Zhou (2010).

Next, we distinguish the cases of split rated bonds with superior Moodys and superior

S&P ratings. In the first set of regressions, we exclude splits with superior S&P ratings. Thus,

the yields of split rated bonds with superior Moodys ratings are compared with yields of non-

split rated bonds, and the results are reported in the first two columns of Table 7. The

32 Our sample is slightly different from that of Livingston and Zhou (2010) for two reasons. First, their samplecovers 1983 to September 2008, while ours extends to the end of 2008. Second, our sample excludes bonds withthree or more notches of split ratings.


24/43

22

coefficients on the split rating dummy variables from the superior and inferior rating models are

20.01 and -16.22 respectively, indicating an information opacity premium of 2 basis points (that

is, [20.01-16.22]/2). Then, we exclude splits with superior Moodys rating and compare the

yields of split rated bonds with superior S&P ratings and yields of non-split rated bonds in the

second set of regressions. The results are reported in the last two columns of Table 7. The 28.34

and -8.50 coefficients from the superior and inferior rating models imply an information opacity

premium of 10 basis points (that is, [28.34-8.5]/2).

This evidence indicates that the information opacity premium is significantly smaller

when Moodys assigns a superior rating (2 basis points), and higher (10 basis points) when S&P

assigns the superior rating. See Figure 1. The difference in the information opacity premium

between the two groups of split rated bonds is 8 basis points, which is in line with the estimated

average yield difference between the two groups as reported in Section IV.

Based on the regression results in Table 7, we also estimate the average difference in

yield spreads between two adjacent notch rating categories. For example, from the first column

of Table 7, the coefficients on AA- and A+ are -63.79 and -51.98 respectively, suggesting a 12

basis points difference in the yield spreads between the two adjacent rating categories. For each

rating category, we find the absolute yield spread difference from its adjacent higher rating

category. Then, we weight the absolute yield spread difference by the number of observations in

the rating category.33 The weighted average yield spread difference between all the adjacent

rating categories is about 30 basis points.34

33 A simple average is biased because the yield spread difference between below investment grade rating categoriesare much larger but there are fewer observations. For below investment grade rating categories, the average yielddifference is 67 basis points but they only account for 25% of the sample. For investment grade rating categories,the average yield difference is much smaller, about 16 basis points.34 Using the coefficients reported in the other three columns of Table 7, we obtain similar estimates.


25/43

23

VI. Discussion and Conclusion

While most public corporate bond issues have ratings from both Moodys and S&P,

regulators and many academic studies do not differentiate between the two ratings and treat them

as equivalent and interchangeable. In other words, a bond with an A+ rating from Moody's and

an A- rating from S&P is thought to be the same as another bond with an A+ from S&P and an

A- from Moody's. This wide perception of equivalence of the two major ratings is particularly

troublesome when previous studies have consistently shown that Moodys is a more conservative

rating agency and is more likely to assign a conservative rating than S&P when the two differ.

This study performs a joint test that 1) there is a systematic difference between the

Moodys and S&P ratings and 2) bond investors differentiate between these two ratings. We

find that split rated bonds with superior Moodys ratings have lower yields than similar bonds

with superior S&P ratings, suggesting that investors differentiate between these two situations.

The yield difference is both statistically and economically significant. In addition, the

differential impact of the two ratings on bond yields is more pronounced for Rule 144A bond

issues, which have greater information opaqueness problems. This evidence indicates that bond

investors are particularly concerned about opaque bond issues and rely more heavily on the

ratings from the conservative rating agency in their assessment of default risk.

Furthermore, the relative conservativeness of the two rating agencies is not static, but

evolving. Accordingly, bond investors differentiate between the two rating agencies only when

there is a systematic difference between them. This evidence highlights the importance for the

rating agencies to protect their reputational capital. If one rating agency consistently becomes

more lenient (conservative) over time, bond investors will gradually adapt to such changes by

putting less (more) weight on that agencys rating in their assessment of default risk. This


26/43

24

finding supports the argument that rating agencies have strong incentives to issue honest and

accurate ratings to protect their reputation capital. In addition, the finding suggests a need for the

regulatory agencies, such as the SEC, to monitor and evaluate the performance of the nationally

recognized rating agencies whose ratings are used as regulatory tools.


27/43

25

Appendix A

We follow Livingston and Zhous (2010) methodology to estimate the information

opacity premium of split rated bonds. Specifically, two treasury spread regression models are

used.

The first regression model compares treasury spreads for split rated bonds with non-split

rated bonds with superior ratings. The superior ratings are used to create seventeen rating

dummy variables: SUP_RATINGj (j = 1 to 17). To distinguish the split rated and non-split rated

bond issues, a dummy variable for split rating, SPLIT, is included in the regression. The SPLIT

dummy variable reflects the fact that a split rated bond has an inferior rating (in addition to its

split superior rating) not captured by the rating dummy variables. The regression model is as

follows:

17 8 25

i i ji ji ji

1 1 1

TS *SPLIT *SUP_RATING *Control Variable *YEAR .s j j jj j j

(A1)

Equation (A1) is called the Superior Rating Model. If yields for the split rated bonds are

determined by the superior rating alone and the second rating has no impact, Sshould be

insignificant. Alternatively, if investors price the inferior rating as well, Sshould be

significantly positive; that is, the inferior second rating should increase yields since it conveys

additional negative information. Thus, the coefficient for SPLIT, S, can be interpreted as the

difference between the actual treasury spreads of split rated bonds and the estimated treasury

spreads of these bonds if both rating agencies had assigned the same superior rating.

The procedure is then reversed. In the second regression model, yields for split rated

bonds are compared with yields for the inferior rating. Specifically, the inferior ratings are used


28/43

26

to create the rating dummy variables:INF_RATINGj (j = 1 to 17).A1 Thus, the SPLIT variable

reflects the fact that a split rated bond has a superior rating not captured by the rating dummy

variables. The regression model is as follows:

17 8 25

i i ji ji ji

1 1 1

TS *SPLIT *INF_RATING *Control Variable *YEAR .I j j jj j j

(A2)

Equation (A2) is called the Inferior Rating Model. The coefficient for SPLIT,I, can be

interpreted as the difference between the actual treasury spreads of split rated bonds and the

estimated treasury spreads of these bonds if both rating agencies had assigned the same inferior

rating.

The final step compares the two coefficients, Sand I. LetNbe the actual treasury

spreads of split rated bonds and S(I) be the estimated treasury spreads if both rating agencies had

assigned the same superior (inferior) rating. Then, as illustrated in Figure A1:

S = N |S| (A3)I = N + |I|

Let A be the average ofSandI, or:

A = (S+I)/2 = (N |S| +N+ |I|)/2 =N+ (|I| |S|)/2.

Thus, the information opacity premium of split rated bonds is:

PREM= NA=N (N+ (|I| | S|)/2) = (|S| |I|)/2 (A4)

That is, the information opacity premium (PREM) is the difference of the absolute values of the

two coefficients divided by two. The information opacity premium is shown in Figure A1.

If there is no information opacity premium on split rated bonds, then, per Equation (A4),

the absolute values of the two coefficients, |S| and |I|, should be same. Conversely, if there is an

information opacity premium on split rated bonds, then |S| should be larger than |I|.

A1 For non-split rated bonds, there is no difference between the SUP_RATING andINF_RATING variables.


29/43

27

Reference

Avramov, D., T. Chordia, G. Jostova, and A. Philipov, 2007, Momentum and Credit Rating,Journal of Finance 62, 2503-2520.

Bank for International Settlements, Basel Committee on Banking Supervision, 2000, CreditRatings and Complementary Sources of Credit Quality Information, Working Papers No.3.

Billingsley, R.S., R.E. Lamy, M.W. Marr, and G.R. Thompson, 1985, Split Ratings and BondReoffering Yields,Financial Management14, 59-65.

Baker, H.K, and S.A. Mansi, 2002, Assessing Credit Rating Agencies by Bond Issuers andInstitutional Investors,Journal of Business Finance & Accounting29, 1367-1398.

Blume, M., F. Lim, and C. Mackinlay, 1998, The Declining Credit Quality of

U.S. Corporate Debt: Myth or Reality? Journal of Finance 53, 1389-1413.

Butler, A.W., 2008, Distance Still Matters: Evidence from Municipal Bond Underwriting,Review of Financial Studies 21, 763-784.

Cantor, R., and F. Packer, 1995, The Credit Rating Industry,Journal of Fixed Income 5, 10-34.

Cantor, R., and F. Packer, 1996, Discretion in the Use of Ratings: the Case of the NAIC,Journal of Insurance Regulation 15,234-255.

Cantor, R., F. Packer, and K., Cole, 1997, Split Ratings and the Pricing of Credit Risk,Journalof Fixed Income 7, 72-82.

Chaplinsky, S., and L. Ramchand, 2004, The Impact of SEC Rule 144A on Corporate DebtIssuance by International Firms,Journal of Business 77, 1073-1097.

Covitz, D, and P. Harrison, 2004, Testing Conflicts of Interest at Bond Rating Agencies withMarket Anticipation: Evidence that Reputation Incentives Dominate, Federal ResearchWorking Paper No. 2003-68.

Ederington, L., 1986, Why Split Ratings Occur?Financial Management15, 37-47.

Ederington, L., and J. Goh, 1998, Bond Rating Agencies and Stock Analysts: Who KnowsWhat When?Journal of Financial and Quantitative Analysis 33, 569-585.

Fenn, G.W., 2000, Speed of Issuance and the Adequacy of Disclosure in the 144A High-YieldDebt Market,Journal of Financial Economics 56, 383-405.

Fridson, M., and M. Garman, 1997, Valuing Like-rated Senior and Subordinated Debt,Journal of Fixed Income 7, 83-93.


30/43

28

Gttler, A., 2005, Using a Bootstrap Approach to Rate the Raters,Financial Markets andPortfolio Management19, 277-295.

Gttler, A., and M. Wahrenburg, 2007, The Adjustment of Credit Ratings in Advance of

Defaults,Journal of Banking and Finance 31, 751-767.

Holthausen, R., and R. Leftwich, 1986, The Effect of Bond Rating Changes on Common StockPrices,Journal of Financial Economics 17, 57-89.

Houweling, P., A. Mentink, and T. Vorst, 2005, Comparing Possible Proxies of Corporate BondLiquidity,Journal of Banking and Finance 29, 1331-1358.

Hsueh, P., and D.S. Kidwell, 1988, Bond Ratings: Are Two Better Than One?FinancialManagement17, 46-53.

Jewell, J., and M. Livingston, 1998, Split Ratings, Bond Yields, and Underwriter Spreads forIndustrial Bonds,Journal of Financial Research 21, 185-204.

John, K., S.A. Ravid, and N. Reisel, 2010, The Notching Rule for Subordinated Debt and theInformation Content of Debt Rating,Financial Management, forthcoming.

Kidwell, D.S., W. Marr, and G.R. Thompson, 1984, SEC Rule 415: the Ultimate CompetitiveBid,Journal of Financial and QuantitativeAnalysis 19, 183-195.

Kidwell, D.S., W. Marr, and G.R. Thompson, 1987, Shelf Registration: Competition andMarket Flexibility,Journal of Law and Economics 30, 181-206.

Liu, P., and W. Moore, 1987, The Impact of Split Bond Ratings on Risk Premia,FinancialReview 22, 71-85.

Livingston, M., and L. Zhou, 2002, The Impact of Rule 144A Debt Offerings upon Bond Yieldsand Underwriter Fees,Financial Management31, 5-27.

Livingston, M., A. Naranjo, and L. Zhou, 2007, Asset Opaqueness and Split Bond Ratings,Financial Management36, 49-62.

Livingston, M., and L. Zhou, 2010, Split Bond Ratings and Information Opacity Premium,Financial Management, forthcoming.

Moon, C.G., and J.G. Stotsky, 1993, Testing the Differences between the Determinantsof Moodys and Standard & Poors Ratings,Journal of Applied Econometrics 8,51-69.

Morgan, D.P., 2002, Rating Banks: Risk and Uncertainty in an Opaque Industry,AmericanEconomic Review 92, 874-888.


31/43

29

Perry, L.G., P. Liu, and D.A. Evans, 1988, Modified Bond Ratings: Further Evidence on theEffect of Split Ratings on Corporate Bond Yields,Journal of Business Finance &Accounting15, 231-241.

Pottier, S.W., and D.W. Sommer, 1999, Property-liability Insurer Financial Strength Ratings:Differences across Rating Agencies, The Journal of Risk and Insurance 6, 621-642.

Reiter, S., and D. Ziebart, 1991, Bond Yields, Ratings, and Financial Information: Evidencefrom Public Utility Issues,Financial Review 26, 45-73.

Smith, R.C., and I. Walter, 2002, Rating Agencies: Is There an Agency Issue? in R.M. Levich,G. Majnoni, and C. Reinhart, Eds.,Rating, Rating Agencies and the Global FinancialSystem, Boston, Kluwer Academic Publishers.

Van Roy, P., 2005, Credit Ratings and the Standardised Approach to Credit Risk in Basel II,

European Central Bank Working Paper No. 517.

Wooldridge, J.M., 2002,Econometric Analysis of Cross Section and Panel Data, Cambridge,MA: MIT Press.

Wooldridge, J.M., 2003, Cluster-Sample Methods in Applied Econometrics,AmericanEconomic Review 93, 133-138.

Yu, F., 2005, Accounting Transparency and the Term Structure of Credit Spreads,Journal ofFinancial Economics 75, 53-84.


32/43

30

TreasurySpread

(Basis Points)

S

I

I: Non-Split Inferior Rating

S: Non-Split Superior

Rating

A: Average of Non-Split

Superior and Inferior

Ratings

L: All Splits

SP: Split-S&P Higher

M: Split-Moodys Higher

SP

L

M

A

2

6.5

10

Superior Inferior Rating

30

8

Figure 1. Split Rated Bond Risk Premium. This figure illustrates the risk premium on split rated bonds over non-split rated bonds. The difference of 30 basis points between I and S is the average difference in treasury spreadbetween two adjacent ratings and is derived in Section V. The difference of 10 basis points between SP and A andthe 2-basis-point difference between M and A are derived from Table 7 and discussed in Section V. The difference

of 6.5 basis points between L and A are derived from Table 6 and also discussed in Section V.


33/43

31

Figure 2. Number of Split Rated Issues in Each Rating Category. This figure depicts the number of split rated bonds winumber of splits with superior Moodys ratings in each split rating category.

0

50

100

150

200

250

300

350

400

450

AAA/AA+

AAA/AA

AA+/AA

AA+/AA-

AA/AA-

AA/A+

AA-/

A+

AA-/

A

A+/A

A+/A-

A/A-

A/BBB+

A-/

BBB+

A-/

BBB

BBB+/BBB

BBB+/BBB-

BBB/BBB-

BBB/BB+

BBB-/

BB+

BBB-/

BB

BB+/BB

BB+/BB-

BB/BB-

BB/B+

BB-/

B+

B B

/ B

NumerofIssues

Superior S&P Rating Superior Moody's Rating


34/43

32

Figure A1. Illustration of Information Opacity Premium. I stands for the estimated treasury spreads on split rated bonds ifboth rating agencies had assigned the same inferior rating. S stands for the estimated treasury spreads on split rated bonds ifboth rating agencies had assigned the same superior rating. A is the average of I and S. N stands for the actual treasuryspreads of split rated bonds. The difference between N and A is the information opacity premium (PREM).

InformationOpacity

Premium


35/43

33

Table 1

Summary Statistics

This table reports the descriptive statistics of the Non-Split Rated sample, Split Rated sample, the Superior S&PRating sub-sample, and the Superior Moodys Rating sub-sample. The Moodys Rating and the S&P Rating are twonumerical variables ranging from 1(for CCC rating) to 18 (for AAA rating). Average Rating is the average of the

Moodys Rating and the S&P Rating.

Non-SplitRated Sample

SplitRated Sample

SuperiorS&P Rating

SuperiorMoodys Rating

Proceeds(in million dollars)

223.78 235.46 243.80 225.07

Maturity 12.35 12.60 11.86 13.52

Yield to Maturity 7.86% 8.18% 7.97% 8.45%

Treasury Spread

(in basis points) 197.91 215.73 215.17 216.43

Moodys Rating 10.33 9.87 9.43 10.42

S&P Rating 10.33 10.01 10.60 9.27

Average Rating 10.33 9.94 10.01 9.84

Rating Difference(Moodys Rating S&P Rating)

0.00 -0.14 -1.17 1.15

% of Senior Bond 87.46% 86.83% 89.65% 83.32%

% of Shelf-registration 66.42% 60.70% 61.64% 59.54%

% of Utility Issues 37.65% 40.33% 37.06% 44.41%

% of Rule 144A Issues 22.09% 23.08% 26.28% 19.08%

% of Callable Bonds 33.90% 35.75% 31.94% 40.49%

No. of Obs. 7,201 6,652 3,691 2,961


36/43

34

Table 2

Mean Treasury Spreads of Split Rated Bonds by Rating Category

This table reports the mean treasury spreads of each split rating category for the Split Rated sample, Superior S&PRating sub-sample, and Superior Moodys Rating sub-sample.

Split Rated Sample Superior S&P Rating Superior Moodys Rating

AAA/AA+ 60.19 54.48 65.37

AAA/AA 101.34 110.64 88.01

AA+/AA 62.70 51.90 65.60**

AA+/AA- 104.49 106.86 92.65

AA/AA- 66.77 67.41 66.11

AA/A+ 81.41 81.37 81.46

AA-/A+ 89.09 92.00 82.16

AA-/A 109.04 120.22 81.74***

A+/A 88.81 94.14 82.78***

A+/A- 118.13 113.19 124.09A/A- 113.11 111.69 115.82

A/BBB+ 135.90 112.51 159.73***

A-/BBB+ 137.85 143.99 132.91**

A-/BBB 126.00 120.42 132.46

BBB+/BBB 150.42 151.30 149.47

BBB+/BBB- 168.74 157.91 191.67

BBB/BBB- 175.08 173.67 177.13

BBB/BB+ 196.98 183.73 237.76*

BBB-/BB+ 201.32 191.80 217.82

BBB-/BB 233.39 240.33 214.17

BB+/BB 288.43 277.18 309.12BB+/BB- 333.31 334.11 331.07

BB/BB- 299.53 300.10 298.29

BB/B+ 363.19 401.68 311.12***

BB-/B+ 367.12 369.06 365.43

BB-/B 437.13 484.05 366.74***

B+/B 423.94 446.13 394.60***

B+/B- 461.08 491.04 415.78***

B/B- 486.03 496.84 475.26*

B/CCC+ 569.09 552.74 574.73

B-/CCC+ 583.64 626.89 553.78***

B-/CCC 528.64 558.95 515.81

CCC+/CCC 716.84 819.24 599.81

***,**, * indicate the difference between the Superior S&P Rating sub-sample and the Superior Moodys Ratingsub-sample is significant at the 1%, 5% or 10% level.


37/43

35

Table 3

Treasury Spread Regressions for Split Rated Sample

This table reports the treasury spread regression results for the Split Rated sample. The dependent variableis the treasury spread in basis points. The control variables include 32 split rating dummy variables withBBB+/BBB as the base case. MATURITY is the natural log of the number of years to maturity.

PROCEEDS is the gross proceeds of the bond issue in millions of dollars. SENIOR equals 1 for seniorbonds, 0 otherwise. CALL equals 1 for callable bonds, 0 otherwise. UTILITY equals 1 for utility issues, 0otherwise. R144A equals 1 for Rule 144A issues, 0 otherwise. SHELF equals 1 for shelf registered issues,0 otherwise. RISKPREM is the difference (in basis points) between Moodys AAA Bond Index Yield and10-Year Treasury yield. The regressions also include 25 year dummies with 2008 as the base case. InModel 1, the test variable is SUPMOODY, equal to 1 if Moodys assigns a superior rating and 0 otherwise.In Model 2, the test variables are SUPMOODY1 and SUPMOODY2. SUPMOODY1 (SUPMOODY2)equals 1 if Moodys rating is one (two) notch above the S&P rating. In Model 3, the test variables areSUPMOODY_Notch and SUPMOODY_Letter. SUPMOODY_Notch equals 1 if Moodys rating is abovethe S&P rating but they are in the same letter rating category, 0 otherwise. SUPMOODY_Letter equals 1 ifMoodys rating is in a letter category superior to the S&P rating, 0 otherwise. The p-values (in theparenthesis) have been adjusted for potential clustering problems that might arise from multiple bond issuesby the same firm.

Model 1 Model 2 Model 3

Intercept 58.19 (0.00) 57.60 (0.00) 56.58 (0.00)

SUPMOODY -8.38 (0.00)

SUPMOODY1 -7.64 (0.01)

SUPMOODY2 -12.60 (0.03)

SUPMOODY_Notch -5.89 (0.07)

SUPMOODY_Letter -13.75 (0.00)

AAA/AA+ -81.35 (0.00) -81.41 (0.00) -77.46 (0.00)

AAA/AA -75.22 (0.00) -73.33 (0.00) -72.06 (0.00)

AA+/AA -72.70 (0.00) -72.91 (0.00) -73.54 (0.00)

AA+/AA- -55.64 (0.00) -54.60 (0.00) -54.86 (0.00)AA/AA- -67.20 (0.00) -67.22 (0.00) -67.32 (0.00)

AA/A+ -49.91 (0.00) -47.83 (0.00) -46.52 (0.00)

AA-/A+ -59.45 (0.00) -59.30 (0.00) -56.64 (0.00)

AA-/A -53.38 (0.00) -51.85 (0.00) -50.65 (0.00)

A+/A -55.37 (0.00) -55.34 (0.00) -55.31 (0.00)

A+/A- -47.32 (0.00) -45.05 (0.00) -47.27 (0.00)

A/A- -45.72 (0.00) -45.62 (0.00) -45.40 (0.00)

A/BBB+ -9.83 (0.00) -7.40 (0.00) -5.98 (0.00)

A-/BBB+ -24.83 (0.00) -24.89 (0.00) -20.70 (0.00)

A-/BBB -15.62 (0.00) -13.34 (0.00) -11.93 (0.00)

BBB+/BBB- 27.95 (0.00) 29.66 (0.00) 28.35 (0.00)

BBB/BBB- 26.02 (0.00) 26.09 (0.00) 26.23 (0.00)

BBB/BB+ 60.54 (0.00) 61.98 (0.00) 63.07 (0.00)

BBB-/BB+ 64.22 (0.00) 64.35 (0.00) 67.43 (0.00)

BBB-/BB 101.13 (0.00) 102.66 (0.00) 103.76 (0.00)

BB+/BB 140.26 (0.00) 140.40 (0.00) 140.70 (0.00)

BB+/BB- 197.94 (0.00) 199.47 (0.00) 198.64 (0.00)


38/43

36

BB/BB- 137.79 (0.00) 137.99 (0.00) 138.29 (0.00)

BB/B+ 212.26 (0.00) 214.51 (0.00) 215.85 (0.00)

BB-/B+ 229.76 (0.00) 229.80 (0.00) 233.92 (0.00)

BB-/B 280.53 (0.00) 282.68 (0.00) 284.01 (0.00)

B+/B 289.28 (0.00) 289.41 (0.00) 289.51 (0.00)

B+/B- 329.39 (0.00) 331.49 (0.00) 329.73 (0.00)B/B- 360.50 (0.00) 360.56 (0.00) 360.60 (0.00)

B/CCC+ 434.04 (0.00) 437.58 (0.00 439.41 (0.00)

B-/CCC+ 463.65 (0.03) 463.62 (0.03) 468.25 (0.03)

B-/CCC 417.29 (0.06) 420.64 (0.06) 422.37 (0.06)CCC+/CCC 594.53 (0.01) 594.62 (0.02) 594.79 (0.01)MATURITY 17.05 (0.00) 17.07 (0.00) 17.08 (0.00)

PROCEEDS -0.01 (0.09) -0.01 (0.09) -0.01 (0.09)

SENIOR 59.68 (0.00) 59.62 (0.00) 59.70 (0.00)

UTILITY -12.48 (0.00) -12.40 (0.00) -12.27 (0.00)

CALL 13.93 (0.00) 13.89 (0.00) 13.90 (0.00)

R144A 8.85 (0.07) 8.88 (0.07) 8.96 (0.07)SHELF -16.12 (0.00) -16.02 (0.00) -16.02 (0.00)

RISKPREM 1.04 (0.00) 1.04 (0.00) 1.04 (0.00)

Year dummies Yes Yes Yes

No. of Obs. 6,652 6,652 6,652

R-squared 0.81 0.81 0.81


39/43

37

Table 4

Treasury Spread Regressions for Split Rated Sample for Each Rating Category

The dependent variable is the treasury spread in basis points. Model 1 (from Table 3) treasury spreadregressions without the split rating dummy variables are estimated for each split rating category. Thecoefficients on SUPMOODY are reported with the cluster-robust p-values. The last two columns report the

number of observations and the R-squared value for each regression. Some control variables are droppedfrom the regressions when there is only one level of variation.

SUPMOODY p-value No. of Obs R-squared

AAA/AA+ 9.77 0.26 42 0.84

AAA/AA -94.54 0.02 26 0.91

AA+/AA 8.59 0.30 123 0.58

AA+/AA- -28.54 0.01 36 0.93

AA/AA- -3.91 0.16 285 0.75

AA/A+ -30.79 0.00 77 0.86

AA-/A+ -13.07 0.02 338 0.50

AA-/A -30.14 0.04 86 0.82A+/A -12.63 0.00 643 0.65

A+/A- 16.86 0.18 106 0.75

A/A- -5.45 0.14 599 0.68

A/BBB+ -25.22 0.06 109 0.76

A-/BBB+ -6.24 0.15 559 0.66

A-/BBB -0.12 0.99 123 0.84

BBB+/BBB -1.30 0.77 685 0.66

BBB+/BBB- -34.11 0.05 81 0.84

BBB/BBB- -2.89 0.70 492 0.53

BBB/BB+ -33.83 0.47 53 0.77

BBB-/BB+ 19.41 0.12 186 0.70

BBB-/BB -31.49 0.14 49 0.88

BB+/BB 32.35 0.07 142 0.69

BB+/BB- -19.56 0.77 53 0.75

BB/BB- 22.45 0.26 187 0.59

BB/B+ 59.68 0.53 40 0.80

BB-/B+ -18.38 0.21 197 0.55

BB-/B -122.32 0.04 55 0.83

B+/B -39.38 0.00 386 0.47

B+/B- -28.30 0.38 103 0.69

B/B- -12.82 0.22 543 0.42

B/CCC+ -23.66 0.79 39 0.78

B-/CCC+ -77.70 0.02 142 0.42

B-/CCC -168.44 0.22 37 0.82

CCC+/CCC -116.00 0.55 30 0.58


40/43

38

Table 5

Treasury Spread Regressions for Split Rated Sub-Samples

The dependent variable is the treasury spread in basis points. This table reports results of the Model 1(from Table 3) treasury spread regressions for several sub-samples. The first two columns report the resultsfor two sub-samples of different time periods: 1983 1997 and 1998 2008. The third column excludes

Rule 144A issues. The fourth column contains the Rule 144A sample. The p-values (in parentheses) havebeen adjusted for potential clustering problems that might arise from multiple bond issues by the same firm.

1983 -1997 1998-20081998-2008

Non-Rule 144A1998-2008

Rule 144A Issue

Intercept -70.61 (0.00) -11.55 (0.65) 28.90 (0.36) 66.97 (0.28)

SUPMOODY -4.57 (0.07) -13.37 (0.00) -7.02 (0.12) -22.81 (0.01)

AAA/AA+ -78.21 (0.00) - 85.66 (0.00) -82.98 (0.02) n.a

AAA/AA -68.23 (0.00) - 79.61 (0.00) -70.55(0.00) -61.15(0.00)

AA+/AA -63.71 (0.00) -89.02 (0.00) -79.47(0.00) -180.78(0.00)

AA+/AA- -58.29 (0.00) - 54.48 (0.00) -53.45(0.00) -24.82(0.19)

AA/AA- -59.23 (0.00) - 81.84 (0.00) -76.21(0.00) -176.99(0.00)AA/A+ -47.20 (0.00) - 47.74 (0.00) -62.54(0.00) n.a.

AA-/A+ -58.03 (0.00) -60.15 (0.00) -49.28(0.00) -97.21(0.00)

AA-/A -54.72 (0.00) - 50.12 (0.00) -49.43(0.00) -3.25(0.91)

A+/A -46.28 (0.00) -63.45 (0.00) -59.96(0.00) -16.01(0.42)

A+/A- -32.46 (0.00) - 56.95 (0.00) -47.43(0.00) -67.59(0.00)

A/A- -33.89 (0.00) - 59.03 (0.00) -52.18(0.00) -48.31(0.01)

A/BBB+ -7.86 (0.30) - 13.92 (0.14) -16.20(0.10) 3.39(0.89)

A-/BBB+ -21.74 (0.00) - 29.09 (0.00) -20.43(0.00) -9.81(0.58)

A-/BBB -16.20 (0.03) - 12.68 (0.08) -8.68(0.21) -10.93(0.59)

BBB+/BBB- 29.40 (0.04) 37.09 (0.01) 28.30(0.03) 65.12(0.01)

BBB/BBB- 22.60 (0.00) 29.27 (0.00) 28.12 (0.00) 34.50 (0.07)

BBB/BB+ 65.51 (0.00) 59.63 (0.00) 61.81(0.00) 58.90(0.03)

BBB-/BB+ 50.29 (0.00) 75.72 (0.00) 87.11(0.00) 90.47(0.00)

BBB-/BB 92.56 (0.00) 138.77 (0.00) 115.34(0.01) 184.36(0.00)

BB+/BB 148.42 (0.00) 134.51 (0.00) 131.83(0.00) 149.61(0.00)

BB+/BB- 207.02 (0.00) 195.08 (0.00) 140.09(0.00) 232.89(0.00)

BB/BB- 166.73 (0.00) 127.78 (0.00) 111.02(0.00) 166.74(0.00)

BB/B+ 247.79 (0.00) 181.61 (0.00) 78.61(0.20) 204.87(0.20)

BB-/B+ 259.79 (0.00) 213.23 (0.00) 190.47(0.00) 237.76(0.00)

BB-/B 282.59 (0.00) 282.66 (0.00) 363.98(0.00) 287.10(0.00)

B+/B 323.70 (0.00) 270.98 (0.00) 236.21(0.00) 297.12(0.00)B+/B- 376.45 (0.00) 295.84 (0.00) 303.57(0.00) 320.07(0.00)

B/B- 395.10 (0.00) 343.86 (0.00) 287.02(0.00) 370.07(0.00)

B/CCC+ 454.34 (0.18) 432.25 (0.00) n.a. 468.65 (0.00)

B-/CCC+ 486.12 (0.87) 456.81 (0.00) 488.50(0.00) 500.55(0.00)

B-/CCC 408.76 (0.00) 460.72 (0.00) 289.62(0.00) 512.70(0.00)CCC+/CCC 490.20 (0.00) 619.58 (0.00) n.a 670.22 (0.00)

MATURITY 18.53 (0.00) 18.74 (0.00) 19.10 (0.00) -9.85 (0.19)


41/43

39

PROCEEDS -0.02 (0.08) -0.01 (0.22) 0.01(0.07) -0.07(0.00)

SENIOR 75.58 (0.00) 51.11 (0.00) 15.29 (0.43) 65.17 (0.00)

UTILITY -3.74 (0.20) -20.43 (0.00) -7.25 (0.12) -38.55 (0.00)

CALL 9.78 (0.00) 13.62 (0.12) 13.19 (0.22) 4.38 (0.74)

R144A -10.18 (0.13) 29.20 (0.01)

SHELF -10.90 (0.01) -0.24 (0.98) 1.16 (0.91) n.aRISKPREM 0.38 (0.00) 1.40 (0.00) 1.16 (0.00) 2.02 (0.01)

Year dummies Yes Yes Yes Yes

No. of Obs. 3,339 3,313 2,022 1,291

R-squared 0.88 0.75 0.70 0.66


42/43

40

Table 6

Information Opacity Premium Regressions for Full Sample

The dependent variable is the treasury spread in basis points. The base case is BBB+ rated bonds. SPLIT isequal to 1 for split rated bonds and 0 otherwise. MATURITY is the natural log of the number of years tomaturity. PROCEEDS is the gross proceeds of the bond issue in millions of dollars. SENIOR equals 1 forsenior bonds, 0 otherwise. CALL equals 1 for callable bonds, 0 otherwise. UTILITY equals 1 for utility

issues, 0 otherwise. R144A equals 1 for Rule 144A issues, 0 otherwise. SHELF equals 1 for shelf registeredissues, 0 otherwise. RISKPREM is the difference (in basis points) between Moodys AAA Bond IndexYield and 10-Year Treasury yield. The regressions also include 25 year dummies with 2008 as the base case.In the Superior (Inferior) Rating Model, we use the superior (inferior) rating of split rated bonds to constructthe rating dummy variables. Thus, the coefficient for SPLIT measures the impact of the Inferior (Superior)second rating on the treasury spreads of split rated bonds. The p-values (in parentheses) have been adjustedfor potential clustering problems that might arise from multiple bond issues by the same firm.

Superior Rating Model Inferior Rating Model

Intercept 36.72 (0.00) 43.86 (0.00)

SPLIT 24.80 (0.00) -11.76 (0.00)

AAA -84.21 (0.000 -90.33 (0.00)

AA+ -74.41 (0.00) -65.57 (0.00)AA -66.32 (0.00) -60.28 (0.00)

AA- -61.06 (0.00) -53.29 (0.00)

A+ -52.25 (0.00) -42.96 (0.00)

A -37.26 (0.00) -35.12 (0.00)

A- -21.89 (0.00) -21.33 (0.00)

BBB 17.33 (0.00) 13.35 (0.00)

BBB- 48.50 (0.00) 42.28 (0.00)

BB+ 137.20 (0.00) 93.21 (0.00)

BB 157.14 (0.00) 161.49 (0.00)

BB- 219.25 (0.00) 183.85 (0.00)

B+ 282.39 (0.00) 252.58 (0.00)

B 349.28 (0.00) 318.80 (0.00)

B- 423.03 (0.00) 392.65 (0.00)

CCC+ 546.11 (0.00) 488.51 (0.00)

CCC 461.52 (0.00) 507.13 (0.00)

MATURITY 17.38 (0.00) 17.58 (0.00)

PROCEEDS -0.01 (0.07) -0.01 (0.00)

SENIOR 63.42 (0.00) 60.41 (0.00)

UTILILTY -11.86 (0.00) -10.79 (0.00)

CALL 14.87 (0.00) 15.27 (0.00)

R144A 7.67 (0.09) 10.18 (0.02)SHELF -17.18 (0.00) -15.72 (0.00)

RISKPREM 0.98 (0.00) 0.98 (0.00)

YEAR Dummies Yes Yes

No. of Obs. 13,853 13,853

R-square 0.81 0.81


43/43

Table 7

Information Opacity Premium Regressions for Two Subsamples

The dependent variable is the treasury spread in basis points. The base case is BBB+ rated bonds. SPLIT isequal to 1 for split rated bonds and 0 otherwise. MATURITY is the natural log of the number of years tomaturity. PROCEEDS is the gross proceeds of the bond issue in millions of dollars. SENIOR equals 1 forsenior bonds, 0 otherwise. CALL equals 1 for callable bonds, 0 otherwise. UTILITY equals 1 for utility

issues, 0 otherwise. R144A equals 1 for Rule 144A issues, 0 otherwise. SHELF equals 1 for shelf registeredissues, 0 otherwise. RISKPREMIUM is the difference (in basis points) between Moodys AAA Bond IndexYield and 10-Year Treasury yield. The regressions also include 25 year dummies with 2008 as the base case.In the Superior (Inferior) Rating Model, we use the superior (inferior) rating of split rated bonds to constructthe rating dummy variables. Thus, the coefficient for SPLITmeasures the impact of the Inferior (Superior)second rating on the treasury spreads of split rated bonds. The p-values (in parentheses) have been adjustedfor potential clustering problems that might arise from multiple bond issues by the same firm.

Superior Moodys Splits and Non-Splits Superior S&P Splits and Non-Splits

Superior

Rating Model

Inferior

Rating Model

Superior

Rating Model

Inferior

Rating Model

Intercept 37.59 (0.01) 40.15 (0.00) 34.61 (0.01) 44.45 (0.00)

SPLIT 20.01 (0.00) -16.22 (0.00) 28.34 (0.00) - 8.50 (0.00)AAA -86.87 (0.000 -90.33 (0.00) -83.74 (0.00) -89.16 (0.00)

AA+ -79.37 (0.00) -66.97 (0.00) -67.16 (0.00) -69.70 (0.00)

AA -67.03 (0.00) -61.37 (0.00) -65.43 (0.00) -63.21 (0.00)

AA- -63.79 (0.00) -56.52 (0.00) -60.50 (0.00) -57.47 (0.00)

A+ -51.98 (0.00) -47.14 (0.00) -49.52 (0.00) -43.98 (0.00)

A -36.33 (0.00) -36.73 (0.00) -37.42 (0.00) -35.45 (0.00)

A- -22.71 (0.00) -19.95 (0.00) -18.68 (0.00) -22.59 (0.00)

BBB 14.26 (0.00) 12.56 (0.00) 14.23 (0.00) 10.13 (0.00)

BBB- 43.49 (0.00) 41.70 (0.00) 44.35 (0.00) 38.32 (0.00)

BB+ 131.07 (0.00) 107.63 (0.00) 128.84 (0.00) 89.31 (0.00)

BB 175.92 (0.00) 176.81 (0.00) 153.08 (0.00) 157.83 (0.00)

BB- 210.51 (0.00) 197.38 (0.00) 217.74 (0.00) 181.93 (0.00)

B+ 268.30 (0.00) 258.46 (0.00) 286.73 (0.00) 255.08 (0.00)

B 347.71 (0.00) 320.27 (0.00) 345.47 (0.00) 328.64 (0.00)

B- 419.78 (0.00) 401.99 (0.00) 423.72 (0.00) 400.23 (0.00)

CCC+ 521.10 (0.00) 487.62 (0.00) 558.49 (0.00) 515.55 (0.00)

CCC 464.65 (0.00) 456.23 (0.00) 460.13 (0.00) 569.75 (0.00)

MATURITY 17.74 (0.00) 17.86 (0.00) 18.16 (0.00) 18.38 (0.00)

PROCEEDS -0.00 (0.29) -0.01 (0.19) -0.01 (0.06) -0.01 (0.07)

SENIOR 65.95 (0.00) 65.44 (0.00) 65.37 (0.00) 60.03 (0.00)

UTILILTY -11.92 (0.00) -10.58 (0.00) - 9.51 (0.00) -8.48 (0.00)CALL 14.40 (0.00) 15.95 (0.00) 14.01 (0.00) 12.71 (0.00)

R144A 1.93 (0.71) 7.88 (0.12) 9.98 (0.07) 7.58 (0.14)

SHELF -17.35 (0.00) -14.41 (0.00) -16.76 (0.00) -18.20 (0.00)

RISKPREM 0.94 (0.00) 0.94 (0.00) 0.96 (0.00) 0.97 (0.00)

YEAR Dummies Yes Yes Yes Yes

Documents

Livingston - Moody's and S&P Ratings