J Finan Serv Res (2008) 33:57–76
DOI 10.1007/s10693-007-0021-4
The Impact of Rating Agency Reputation on Local
Government Bond Yields
Arthur C. Allen & Donna M. Dudney
Received: 20 June 2006 / Revised: 10 September 2007 / Accepted: 27 September 2007 /
Published online: 10 November 2007
# Springer Science + Business Media, LLC 2007
Abstract This study examines a sample of 12,562 dual-rated local government bond issues
including 6,104 split-rated issues to determine which rating agency has the greatest impact
on yields. Using a database of municipal bond issues from 1986 to 2002, we show that
Moody’s rated significantly more issues than S&P, and that Moody’s ratings were more
conservative. However, from 1993 to 1997, there was a reduction in ratings disagreements
and in Moody’s market share. Beginning in 1995, Moody’s received negative publicity
related to a Department of Justice anti-trust investigation. Moody’s appears to have
responded by sharply increasing their relative conservatism in 1997. From 1986 to 1994,
Moody’s ratings had a greater impact on bond yields than S&P ratings, but their dominant
influence on yields disappears in the recent sample period from 1995 to 2002.
JEL classifications G12 . G24
Keywords Split ratings . municipal bonds . rating agencies . reputation
Investors look to bond ratings to provide guidance on the default risk of bonds. The
literature suggests that ratings provide information to the market beyond the information
found in published financial reports (Liu et al. 1999). Moody’s and Standard and Poor’s are
the oldest and largest rating agencies and have well-established reputations among
investors. Bond rating studies indicate that both agencies do a reasonable job of assessing
relative credit risks, with lower-rated bonds defaulting more frequently than higher-rated
bonds (Cantor and Packer 1995).
A. C. Allen
College of Business, School of Accountancy, University of Nebraska-Lincoln,
Lincoln, NE 68588-0488, USA
e-mail: aallen1@unl.edu
D. M. Dudney (*)
College of Business, Department of Finance, University of Nebraska-Lincoln,
P.O. Box 880490, Lincoln, NE 68588-0490, USA
e-mail: ddudney1@unl.edu
DO21; No of Pages
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J Finan Serv Res (2008) 33:57–76
While Moody’s and S&P assign the same rating a majority of the time, in approximately
44% of the rated municipal issues from 1986 to 2002 the ratings assigned by Moody’s and
S&P were different. These differences could be attributed to differing rating criteria (or
differing weights applied to similar criteria) or to random differences occurring in
borderline cases. The differences could also be due to rating agency efforts to gain a
competitive advantage with issuers or investors. Regardless of the reason for the split
rating, the existence of splits provides an opportunity to analyze the relative reputations of
the two dominant credit agencies. We examine 12,562 municipal issues (including 6,104
split-rated issues) to determine whether the pricing on primary market issues is more
influenced by the S&P or the Moody’s rating.
Rating agencies earn revenue from issuers purchasing ratings for new issues, and from
investors who subscribe to ratings publications and databases. In a competitive market, an
agency may attempt to gain more market share among issuers by awarding higher ratings
than competing rating agencies. Of course, if investors recognize that an agency is
consistently more lenient, the agency’s reputation among investors may suffer, and yields
on bond issues rated by the agency will be adjusted upward to offset the rating inflation
bias. Issuers consider both the cost of a rating and the impact of the rating on expected bond
pricing when selecting a rating agency. Therefore, a rating agency’s attempt to increase
market share by using more lenient rating standards will be unsuccessful in the long
run if detected by investors. However, it is conceivable that an agency with an
established reputation could, in the short run, become more lenient relative to its
competitors without incurring a market yield penalty. An agency may pursue this shortrun strategy to make up market share lost to competitors or to gain market share in
targeted issuer segments.
To examine the interplay between rating agency market share and the influence of rating
agency reputation on bond yields, we analyze the time series behavior of 66,820 rated
municipal bonds to see if changes have occurred in the relative influence, conservatism or
market share of the dominant rating agencies. A change in these variables could occur
because one agency develops a superior reputation for more accurate analysis, because of
changes in relative leniency (perhaps motivated by an agency’s short-run marketing
strategies), or because of damage to the reputational capital of an agency.
As an example of potential reputational damage, the rating agency practice of releasing
unsolicited ratings on municipal issues was the subject of a highly-publicized Justice
Department investigation of Moody’s Investors Service in 1995. Moody’s was accused of
using the threat of an unsolicited rating to coerce issuers to purchase a solicited rating from
Moody’s. While this study is not a test of the effects of the Department of Justice
investigation, we note that the events surrounding this investigation, including the negative
publicity, may have contributed to a loss in market share and relative influence of a
Moody’s rating.
Prior studies of the effect of split-ratings on yields offer evidence that both Moody’s
and S&P ratings provide useful information to the market, but generally conclude that
neither agency has more influence in determining bond yields. However, most prior
studies focus on the corporate bond market, and are characterized by small split-rating
sample sizes. There are several unique features of the local government bond and rating
environment that allow the municipal market to provide a stronger test of rating agency
reputation.
The municipal market differs from the corporate bond market in both the sophistication
of the investors and the quality of issuer information. While institutional investors play a
dominant role in the corporate bond market, the municipal market is characterized by less
J Finan Serv Res (2008) 33:57–76
59
sophisticated investors. In September 2004, individual investors directly held 30% of
outstanding municipal bonds, compared to 13% of outstanding corporate bonds.1 In
addition, as noted by Perry et al. (1991), information about municipal issuers is less readily
available to investors because municipal issues are exempt from most disclosure and
registration requirements. Compared to corporations, municipal financial accounting
information is less standardized, less timely and less comparable cross-sectionally. These
factors make it more difficult for investors to obtain reliable information about the credit
quality of issuers. In this environment, we expect investors to rely more heavily on bond
ratings, and to be more interested in the relative reputations of the agencies providing these
ratings. When different ratings are assigned by the rating agencies, investors will place
more weight on the rating assigned by the agency perceived to be more accurate and
reliable, and will demand yields commensurate with the rating assigned by the more
reputable agency.
Moody’s and S&P claim to rate virtually all issues of public corporate debt but make no
such claim for local governments. Our analysis shows that a large percentage of all
municipal issues are unrated by one or the other agency. Therefore, it is possible that one
agency could rate more municipal issuers and become more experienced as well as more
familiar to and trusted by bond buyers. Historically, Moody’s has rated substantially more
municipal issues than S&P, although its lead has been eroding.
Because of the differences between the corporate and municipal markets, findings from
the corporate split-rating studies cannot be generalized to the municipal bond market.
Instead, the municipal market may provide a better setting to study the impact of rating
agency reputation because municipal bond investors are forced to rely on ratings to a much
greater degree than corporate bond investors. Understanding the value of ratings in the
municipal market and the competitive forces that drive rating agencies will help issuers and
investors alike make more informed decisions about choosing rating agencies and bond
selection, respectively. Our study may also help future researchers construct more accurate
models of ratings and bond yields.
Our study has several additional advantages over prior studies of split-ratings. First, our
sample contains virtually all of the dual-rated municipal bonds issued between 1986 and
2002, including 6,104 split-rated bonds. In the largest previous sample of split-rated
government issues (135 split-rated issues), Hsueh and Kidwell (1988) analyze whether the
market interest rate was influenced more by the higher or lower bond rating. However, their
research design did not distinguish whether the higher rating assigned to an issue was a
Moody’s or S&P rating, and therefore could not determine which rating agency carried
more weight.2 Allen (1996) did distinguish between Moody’s and S&P ratings, but his
1
For the period from 1980 to 2004, individual investor holdings of municipal securities have ranged from a
low of 26.2% of total municipal holdings in 1980 to a high in 1990 of 48.5% . The holdings percentage
declined gradually to 30.4% in 1998, and has since fluctuated between 30.9 and 35.8%. Data is from the
Federal Reserve Statistical Release Z.1 Flow of Funds Accounts of the United States report for the third
quarter of 2004, published by the Board of Governors of the Federal Reserve System (2004), and from the
Bond Market Association “Trends in the Holdings of Municipal Securites 1980–2004”, online at www.
bondmarkets.com.
2
An example of their split ratings variable was Aaa/Aa, where either the Moody’s or the S&P rating could
be the higher rating. Therefore, they could only draw inferences on whether the higher or lower rating was
more influential. As discussed in the methodology section, we use two variables, Aaa/AA and AAA/Aa, for
this type of split-rating, and therefore, our research design allows us to determine both whether the higher or
lower rating is more influential and whether the Moody’s or S&P rating is more influential.
60
J Finan Serv Res (2008) 33:57–76
results are based on monthly secondary market observations for just 91 split-rated bond
issues.
Local government studies that have addressed the relative influence of Moody’s or S&P
rating have employed very small sample sizes in each rating category. For example, Perry et
al. (1988) analyze the influence of Moody’s versus S&P ratings, but had only 54 split-rating
observations using main rating categories. On average, each split-rating category contained
only nine observations (54 total observations divided by six categories) when using main
ratings3. By comparison, we have an average of 678 observations per category (6,104 splitrated observations divided by nine main rating categories). Using a much larger sample
increases the power of statistical tests, and allows us to examine whether Moody’s or S&P
ratings are more influential. Second, our data spans a longer time frame and includes more
recent data (1986–2002). This data allows us to examine trends in market share and
conservatism of each rating agency, and to examine the relative influence of each rating
agency on new issue yields.
We find that Moody’s rated far more issues than S&P over the sample period. However,
ratings disagreements declined substantially from 1994 to 1996, and Moody’s market share
diminished substantially from 1993 to 1997. Beginning in 1993, Moody’s received negative
publicity related to a lawsuit filed against Moody’s. This lawsuit was the genesis of a
Department of Justice anti-trust investigation that began in 1995. Moody’s appears to have
responded to these events by sharply increasing their relative conservatism in 1997.
Although Moody’s did not recover their previously dominant market share, their relative
market share stabilized beginning in 1997. For the period from 1986 to 1994, Moody’s
ratings had a greater impact on bond yields than S&P ratings, but their dominant influence
on yields disappears in the recent sample period from 1995 to 2002.
Because Moody’s and S&P have been the dominant rating agencies in the municipal
market, we choose to focus on dual-rated Moody’s and S&P issues. However, because
Fitch has been gaining market share in the municipal market, we also consider the impact of
Fitch ratings. We find that while Fitch has substantially increased its market share, it
continues to rate a much smaller number of new issues, and the addition of a Fitch rating to
an issue already rated by S&P and Moody’s generally does not significantly affect yields.
Fitch tends to attract larger issuers, and Fitch ratings are generally purchased as a third
rating in addition to the S&P and Moody’s ratings.4
1 Literature Review
A substantial body of literature examines rating differences between agencies. Cluff and
Farnham (1984) and Morton (1976) study the criteria used in determining municipal ratings
and conclude that Moody’s and S&P use different criteria or different weighting of the same
criteria. Both agencies claim to consider four general categories of variables in determining
ratings: the economic base, financial, debt, and administrative factors. However, Cluff and
3
Perry et al. (1991) had 54 split-rating observations using main rating categories and 97 observations using
modified categories. On average, each split-rating category contained 5.39 observations (97 total
observations divided by 18 categories) when using the modified categories.
4
The tendency for Fitch ratings to be purchased by larger issuers is not surprising since the cost of a rating
per dollar issued is much smaller for larger issues. Given the small yield advantage associated with the
purchase of a Fitch rating, only large issuers can achieve interest costs savings sufficient to warrant the
purchase of a third rating.
J Finan Serv Res (2008) 33:57–76
61
Farnham find that S&P tends to place more emphasis on economic and demographic factors
while Moody’s weights debt burden and other financial information more heavily.
Given that the agencies appear to take different approaches to determining municipal
ratings, several studies have examined the relative influence of the two major agencies.
Ellis (1998) and Baker and Mansi (2002) surveyed issuers and institutional investors and
found that investors rated S&P first in credibility, followed by Moody’s. In the Ellis study,
issuers placed Duff and Phelps and Moody’s in a tie for second place behind S&P, while in
the Baker and Mansi (2002) survey both issuers and investors assessed the ratings of Duff
and Phelps and Fitch as less accurate than Moody’s and S&P. In both studies, the average
scores for Moody’s and S&P were not significantly different, but the survey respondents
primarily invest in corporate securities. With the exception of the survey work noted above,
most studies of the relative influence of ratings from the two major agencies have examined
yields on split-rated issues to see if these yields are consistently different from yields on
dual-rated bonds with the same rating from both agencies. If yields differ, the studies test
whether yields tend to track a particular agency’s ratings.
Previous research on the impact of split ratings on yields is summarized in Table 1.
Three studies focus on the municipal bond market. Hseuh and Kidwell (1988) examine
1,512 Texas issues rated between 1976 and 1983. They find that yields on 135 split-rated
bonds are not significantly different from yields on dual-rated bonds with a rating equal to
the higher split-rating. When yields on split-rated bonds are compared to yields on dualrated bonds with a rating equal to the lower split-rating, yields on the split-rated bonds are
significantly lower than yields on the dual-rated bonds. Using a 1983 sample of 250 general
obligation bonds, and a sample of 55 split ratings, Perry et al. (1991) find that if modifiers
are not included in bond ratings, split generic ratings do not affect bond yields. Difference
in yields associated with modified rating splits are attributed to the lack of a one-to-one
correspondence between Moody’s and S&P’s modified rating systems during the time
period covered by the study.5 Allen (1996) used monthly observations on 395 secondary
market general obligation bonds from 1978 to 1987 and concluded that yields on split-rated
bonds are in between those of congruently-rated adjacent categories. When ratings are split
Aa/AAA or Aaa/AA, Moody’s ratings have more influence in determining bond yields.
Similar results are found for bonds rated Aa/A instead of AA/A.
Results of split-rating studies on corporate bonds have been mixed. Comparing splitrated bonds with bonds receiving the same rating from both agencies, Billingsley et. al.
(1985), Perry et al. (1988), and Liu and Moore (1987) find that yields on split-rated issues
are not significantly different from yields on bonds with the lower rating from both
agencies. In contrast, Jewell and Livingston (1998) find that yields on split-rated bonds are
an average of the yields of the two ratings. Thompson and Vaz (1990) compare single-rated
bonds to dual-rated bonds and find that two matching ratings reduce yields below those on
bonds with the same rating from only one agency. In the Thompson and Vaz study, yields
on split-rated bonds are significantly higher than yields on bonds with the higher rating
from both agencies.
Most corporate bond studies find that neither rating agency has more influence in
determining bond yields (see Billingsley et. al. 1985; Ederington 1986; Liu and Moore
1987; Kish and Hogan 1999; and Jewell and Livingston 1998). Beattie and Searle (1992)
find a very high correlation between Moody’s and S&P ratings (0.97) for a 1990 sample of
5,284 corporate bonds.
5
Moody’s began using a single modifier in each rating class in 1982, while S&P began using two modifiers
in each rating class beginning in 1975. Moody’s adopted a second modifier in 1996.
Monthly
Municipal
observations on
secondary
395 GO bonds
from 1978 to 1987
Billingsley 258 industrial bonds Corporate
et al.
1977–1983
primary
(1985)
Ederington 493 industrial bonds Corporate
(1986)
from Jan. 1975 to
secondary
Dec. 1980
282 corporate bonds Corporate
Liu and
secondary
from June 1984
Moore
(1987)
Allen
(1996)
Municipal
secondary
Perry et al. 250 GO bonds
(1991)
December 1983
Market
Municipal
primary
Sample
Hsueh and 1,512 Texas GO
Kidwell
bonds 1976–1983
(1988)
Authors
Findings
Which rating agency
has more influence in determining bond yields?
Purchase of a second rating lowers NIC (net of
Not tested
transactions costs) by 5.2 basis points. Yields on splitrated bonds are not significantly different from adjacent
higher ratings category; are significantly lower than
adjacent lower ratings category
97
Split generic ratings have no effect on bond yields. For Moody’s—but probably due to lack of
modified ratings splits, no difference if Moody’s used as correspondence between Moody’s and S&P
base rating. If S&P used as base rating, superior ratings modified ratings
assigned by Moody’s result in significantly lower yields
Monthly
Yields of split-rated bonds are in between those of
Moody’s when bonds are split Aa/AAA or Aaa/
observations congruently-rated adjacent categories
AA; Moody’s when bonds are split Aa/A or
on 91 split
A/AA; neither when bonds split Baa/A or A/
ratings
BBB
33
Yields on split-rated bonds are not significantly different Neither
from adjacent lower ratings category; are significantly
higher than adjacent upper ratings category
63
No systematic differences between Moody’s and S&P
Neither
ratings. Split ratings represent random differences of
opinion
150
Yields on split-rated bonds reflect the lower of the two Neither
ratings
135
Number of
split ratings
Table 1 Summary of prior split rating research. We report the authors, sample composition, type of market, and sample size. We summarize the authors’ findings including
the rating agency with the largest influence on bond yields
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Sample
Number of
split ratings
221
Jewell and 1,277 industrial
Livingston bonds from 1980
(1998)
to 1983
Corporate
primary
61
Corporate 69
secondary
Market
Thompson 426 industrial bonds Corporate
and Vaz
from 1977 to 1983 primary
(1990)
Perry, Liu 269 non-financial
and Evans corporations 1982
(1988)
Authors
Table 1 (continued)
Which rating agency
has more influence in determining bond yields?
Split-rated bonds have yields significantly different from Mixed
bonds with identical S&P and Moody’s ratings. Find a
significant difference in yields only if second rating is
lower than base rating for May 1982 sample
Two matching ratings reduce yields below those on bonds Not tested
with the same rating from only one agency. Yields on
split-rated bonds are significantly higher than on issues
receiving the higher of the two ratings from both
agencies
Yields on split-rated bonds are an average
Neither
of the yields on the two ratings. Split ratings reflect
random differences between rating agencies
Findings
J Finan Serv Res (2008) 33:57–76
63
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J Finan Serv Res (2008) 33:57–76
In summary, prior research finds that ratings have a separate influence on yields apart
from the influence of the publicly-available economic and financial factors used in the
determination of ratings. While Moody’s and S&P appear to have different rating
methodologies, there does not appear to be strong evidence that either agency has more
influence on bond yields. Evidence of the impact of split-ratings on bonds yields is mixed.
A number of studies find that the yields on split-rated bonds are not significantly different
from yields on bonds with the lower of the split-ratings, while others find that yields on
split-rated bonds are between the yields on high and low ratings. Common shortcomings of
prior studies are the small split sample sizes (ranging from 33 to 221 issues), and the limited
time frames covered by the studies (the longest study covered a 10-year period from 1978
to 1987). These shortcomings limit the statistical power of yield difference tests and limit
the analysis of trends in market share and rating agency influence.
2 Rating Agency Market Share and Conservatism
We initially include all primary market municipal bonds included on the Securities Data
Corporation (SDC Platinum) Public Finance database from 1986 to 2002, except unrated,
insured, and other credit enhanced issues. We exclude insured bonds because these bonds
automatically receive the rating of the insurer (typically Aaa). For similar reasons, we also
exclude bonds with other credit enhancements such as letters of credit or state guarantees.
Based on our comparisons of the total number of issues and volume of issues for each
year in the SDC database to published annual summary reports in the Bond Buyer, we
believe that the SDC database contains virtually all competitive and negotiated bonds
issued during the sample period. Therefore, our analysis of rating agency market share and
conservatism are based on population data for the time period studied rather than a sample.
We focus on the period from 1986 to 2002 for several reasons. First, the mix of
municipal bond issue types changed substantially with the passage of the 1986 tax reform
act. This act classified many historically tax-exempt municipal bond types as private
activity bonds subject to the alternative minimum tax. Second, the yield spreads between
rating categories were very large in the 1970s. Spreads between rating categories narrowed
until 1985 and stabilized after that point. Our regression methodology utilizes average
spreads between rating categories, so it is important to use a time period where these
spreads exhibit little cross-time variation. Finally, Moody’s did not use any modifiers on
rating categories until 1982, while S&P began using modifiers in 1975. Choosing a time
period when both agencies used similar modifiers reduces the incidence of rating
disagreements caused by incongruent rating scales.
Prior research has investigated the effect of Fitch ratings for corporations (Jewell and
Livingston 1999) and for states (Johnson and Kriz 2002). We find that although Fitch has a
growing presence in the municipal sector, they continue to rate far fewer issues than
Moody’s and S&P.6 The focus of this study is on issues rated by both Moody’s and S&P
because we wish to analyze the relative impact of each of these agencies on yields. While
6
For example, in 2002 (1995), of the uninsured issues rated by only one agency, Fitch rated only 2% (1%) of
issues, and of the issues rated by at least one agency, Moody’s rated 71% (75%), S&P rated 60% (57%), and
Fitch 18% (7%).
J Finan Serv Res (2008) 33:57–76
65
we include control variables for Fitch ratings in the regression analysis that follows, for the
sake of brevity we omit Fitch’s market share and conservatism from the tables.7
Table 2 displays the market share of Moody’s and S&P in the local government bond
market for each year from 1986 to 2002. Table 2 shows the number and volume of new
issues rated solely by each agency and by both agencies, the market share of each agency,
and the difference in the market shares. Market share is defined as the number of uninsured
new issues rated by each agency divided by the total number of all uninsured new issues.
We measure market share with the percentage of all uninsured bonds which received a
single rating because the effect of dual rated bonds is the same for both agencies. Moody’s
market share peaked in 1987 at 52% and stayed between 47 and 49% from 1988 to 1992.
Since 1992, Moody’s market share has declined, with a large market share drop between
1993 and 1997 (from 46 to 39%). Moody’s market share since 1997 has remained relatively
constant. S&P’s market share rose gradually from 14 to 20% from 1986 to 1990, then fell to
17% by 1992. Rapid gains in S&P’s market share occurred beginning in 1993 and
continuing until 1997, with market share growing from 17 to 29%. Market share since 1997
has stabilized, fluctuating between 28 and 30%.
We measure rating agency dominance by the difference in market share, calculated as
the Moody’s market share minus the S&P market share. Moody’s dominance fell from 32%
in 1992 to 10% in 1997, with a 4 percentage point decline in 1993, 3% in 1994, 7% in
1995, and 3% in both 1996 and 1997.
We measure rating agency divergence as the percentage of ratings that receive a different
rating. Table 2 shows that divergence peaked in 1988 at 55% and was 51% in 1993.
Divergence dropped slightly in 1994 to 48%, significantly in 1995 to 41%, was stable at
about 38% from 1996 to 1999 and then slid to 32% in 2002.
Over the time period that ratings were converging between the two agencies, Moody’s
continued to charge higher fees. If issuers and investors believe that the two ratings will be
the same, issuers have little incentive for paying a premium to Moody’s. Ratings
convergence is one factor which may have lead to an erosion of Moody’s market share.
Other possible factors include changes in the two agencies’ marketing strategies, changes in
the agencies’ relative conservatism, or damage to an agency’s reputation.
While we are unable to obtain information on the historical marketing strategies
employed by either agency, there were events during this time period which could have
negatively affected Moody’s municipal ratings reputation. In 1993, Jefferson County
Colorado School District sued Moody’s over an unsolicited rating published just as its
bonds were coming to market. The low unsolicited rating was estimated to have cost the
district $770,000 in interest costs on a $110 million issue. The widely-publicized lawsuit
was dismissed on first amendment grounds, but prompted a Justice Department
investigation (Kuiper 1998). In 1995, the Justice Department initiated an investigation into
allegations that Moody’s used the threat of low unsolicited ratings to coerce issuers to
purchase Moody’s regular ratings.8 While the investigation was closed in 1999 without
7
A more extensive analysis of the market share of Fitch and the impact of Fitch ratings on yields is available
from the authors.
8
As reported in Gasparino (1996), Moody’s and S&P have both had long-standing policies to issue
unsolicited ratings of municipal issues of interest to its subscribers (Fitch does some unsolicited ratings of
corporate issues; Duff & Phelps does not release unsolicited ratings).
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Table 2 Market share and conservatism of Moody’s vs. S&P. Single Moody (S&P) is the number of bonds
rated exclusively by Moody’s (S&P). Both Ratings is the number of bonds rated by both agencies. One or
Both Ratings is the number of bonds rated by at least one agency. Single Moody’s (S&P)/Total is the
percentage of bonds rated exclusively by Moody’s (S&P). Difference in Market Share is the difference
between Single Moody’s/Total and Single S&P/Total. % Moody’s is the High Rating the percentage of the
dual ratings disagreements in which the Moody’s rating is the high rating. % of Ratings Different is the
percentage of the dual rated bonds in which the modified ratings disagree
Number of uninsured new issues
Time
Single
Single Both
One or
Moody’s S&P Ratings Both
Ratings
1986
1,426
1987
1,678
1988
1,458
1989
1,588
1990
1,473
1991
2,087
1992
2,496
1993
2,624
1994
1,726
1995
1,457
1996
1,408
1997
1,452
1998
1,842
1999
1,585
2000
1,558
2001
1,838
2002
1,715
1986– 16,556
1994
1995– 12,855
2002
Single
Single
Moody’s/ S&P/
Total
Total
Difference
in Market
Share
Percentage
Moody’s is the
High Rating
% of
Ratings
Different
442
509
505
578
616
836
854
1,044
774
829
948
1,070
1,290
1,161
1,154
1,276
1,243
6,158
1,251
1,048
1,046
1,086
1,034
1,491
1,805
2,036
1,287
1,119
1,201
1,210
1,425
1,220
1,169
1,436
1,416
12,084
3,119
3,235
3,009
3,252
3,123
4,414
5,155
5,704
3,787
3,405
3,557
3,732
4,557
3,966
3,881
4,550
4,374
34,798
0.46
0.52
0.48
0.49
0.47
0.47
0.48
0.46
0.46
0.43
0.40
0.39
0.40
0.40
0.40
0.40
0.39
0.48
0.14
0.16
0.17
0.18
0.20
0.19
0.17
0.18
0.20
0.24
0.27
0.29
0.28
0.29
0.30
0.28
0.28
0.18
0.32
0.36
0.32
0.31
0.27
0.28
0.32
0.28
0.25
0.18
0.13
0.10
0.12
0.11
0.10
0.12
0.11
0.30
0.41
0.48
0.44
0.48
0.48
0.51
0.48
0.52
0.48
0.50
0.48
0.38
0.39
0.41
0.37
0.35
0.32
0.44
0.52
0.50
0.55
0.53
0.53
0.49
0.49
0.51
0.48
0.41
0.38
0.38
0.37
0.38
0.35
0.33
0.32
0.50
8,971
10,196
32,022
0.40
0.28
0.12
0.40
0.36
further action, Moody’s suffered reputational damage and lost several senior analysts
following a management reorganization.9
Another factor related to market share is the relative conservatism in assigning ratings.
We measure the relative conservatism of Moody’s vs. S&P by examining the subsample of
bonds with split ratings. For this subsample, we annually calculate the percentage of splitrated bonds assigned a higher rating by Moody’s. A low percentage indicates that Moody’s
is the more conservative rating agency, and 50% would indicate equal conservatism
between Moody’s and S&P. As shown in Table 2, Moody’s was generally the more
9
Moody’s ultimately paid $195,000 to settle one count of obstruction of justice relating to the destruction of
documents by an employee. In addition, three Moody’s executives resigned as a result of issues related to the
timeliness of their reporting of information related to the government’s charges (Hume et. al. 2001). The
municipal and corporate rating groups were merged in May 1996. The head of the municipal ratings group
resigned, and a senior analyst from outside the municipal ratings group assumed his responsibilities.
According to The Economist (1996), following these organizational changes, several high-level resignations
occurred at Moody’s. This is substantiated by a California Public Finance (1998, January) article
commenting on the loss of senior analysts from Moody’s and noting that the “brain drain” might significantly
weaken Moody’s ability to provide quality service.
J Finan Serv Res (2008) 33:57–76
67
conservative rating agency. An agency choosing to be relatively conservative is likely to
gain investors’ confidence, potentially leading to lower bond interest costs. However,
issuers must balance the potential benefits to using a conservative agency with the potential
costs in the form of a lower rating and fee differences between the agencies. A rating
agency may choose to change their conservatism in response to changing market dynamics.
While no apparent time series trend in conservatism is apparent prior to 1995, there is a
pronounced trend of greater conservatism by Moody’s (or leniency by S&P) since 1995,
including a decrease from 48 to 38% in the percentage of split-rated bonds rated lower by
Moody’s between 1996 and 1997.10 Because the erosion of Moody’s market dominance
preceded the increase in Moody’s conservatism, the evidence is consistent with Moody’s
choosing to increase their conservatism in order to combat their reputational losses or other
factors which lead to the erosion in their market share. Although Moody’s was unable to
regain their former market share, their market share stabilized after 1997.
Figure 1 graphically shows the trends in Moody’s market dominance, relative
conservatism, and ratings divergence. The major trends are as follows. Moody’s market
dominance declined considerably from 1992 through 1997. Moody’s relative conservatism
increased sharply in 1997 and after a slight recovery slowly increased through 2002. Rating
divergence decreased significantly from 1994 to 1996 and drifted lower from 2000 through
2002. These trends do not indicate a single point in time in which Moody’s lost its
dominance. However, they do suggest that Moody’s was significantly less dominant after
1995 than before, and that this loss of dominance took place in the years surrounding 1995.
3 Which Rating Agency has the Most Influence on Yields?
The market share and conservatism analysis indicates that Moody’s has historically had
greater market share and conservatism than S&P, but that Moody’s market share dominance
has diminished since the mid 1990s. However, this analysis is incomplete as it ignores the
impact of rating agency reputation on bond yields. The results from the prior section lead us
to expect that ratings from both agencies have an impact on yields, but that Moody’s ratings
might have a greater impact. If Moody’s ratings do have a greater impact on yields, this
impact may have been reduced since the mid-1990s. To examine these issues, we regress
ratings and a set of control variables on new issue bond yields for our sample period from
1986 to 2002. We restrict the sample to dual-rated bonds to eliminate the self-selection bias
associated with single rated bonds.11
We exclude putable issues, issues with variable interest rates, limited obligation issues,
and issues with other credit enhancing features such as insurance, letters of credit, or state
guarantees. Finally, short-term issues are excluded from the sample because default risk is
not expected to strongly affect yields for these issues. Our sample consists of 12,562 dualrated municipal issues with complete data on all model variables, with a split rating sample
size of 6,104. Missing data reduce the sample to about half the population of issues with
dual ratings.
10
The trends in the average annual Moody’s and S&P’s ratings were very similar across our sample period
(1986-–2002). For example, average ratings rose steadily for both agencies from 1990 to 1996. However, in
1997 S&P’s average rating dropped slightly while Moody’s ratings dropped significantly.
11
Hsueh and Kidwell (1988) investigate whether issuers should purchase a second credit rating. They use a
statistical model which accounts for the self-selection bias that results from issuers’ decisions to purchase a
second credit rating.
68
J Finan Serv Res (2008) 33:57–76
0.6
0.5
0.4
0.3
0.2
0.1
0
1986
1988
1990
1992
Market Dominance
1994
1996
% Moody's High
1998
2000
2002
% Different Ratings
Figure 1 Rating agency dominance and conservatism. Market Dominance is equal to Moody’s market share
minus S&P’s market share where market share is defined as the percentage of all uninsured bonds rated
exclusively by that agency. Percentage Moody’s High is the percentage of dual rating disagreements in which
the Moody’s rating is the high rating. Percentage Different Ratings is the percentage of the dual rated bonds
in which the modified rating is different
The dependent variable is the reoffering yield. Because reoffering yields were often
available for several different maturities, the reoffering yield closest to a 10 year maturity
was chosen. Most of the control variables were suggested by prior research. The level of
interest rates is measured as the Bond Buyer’s index of local government bond yields. It is
important to use local government bond yields because the spreads between local
government yields and corporate (or Treasury) yields varies substantially across time.
Maturity is measured as the number of years to maturity associated with the reoffering yield
chosen.12 Although the municipal yield curve is never downward sloping, it becomes flat
for longer maturities. Therefore, the maturity variable is truncated at 20 years. The natural
log of issue size is the final continuous variable in the model.13
12
Duration cannot be used because it requires complete data on coupon, maturity amounts and dates.
Complete data was generally unavailable.
13
Issue size has tended to go up over the sample period (1986-–2002), and therefore, our size variable may
be capturing time period as well as size. As an alternative specification, we measured size by placing the
issues into size quintiles for each year. Four indicator variables (one group is excluded) are used to measure
the size of the issue relative to other issues in the same year. The regression results are not materially
different when these four indicator variables are used in place of the continuous measure of size.
J Finan Serv Res (2008) 33:57–76
69
Indicator variables are used to control for many factors including negotiated offering,
private placement, state tax preference,14 bank qualified, callable issues, issues subject to
the alternative minimum tax (AMT), certificates,15 limited tax bonds, tax increment bonds,
zero coupon bonds, entity type (state, county, school district, college, and other with city
the excluded group), whether the issuer has been in the market for at least 10 years, issue
purpose (development, education, environment, electric power, general purpose, health
care, housing, public facilities, transportation, with utilities as the excluded group), and
region (New England, Mid-Atlantic, South, Great Lakes, Rocky Mountains, and Far West
with Plains as the excluded group).16
The variables of interest in this study are the ratings variables. While prior studies have
generally used indicator variables for various split rating combinations, these studies have
focused on main rating splits (defined as letter differences in assigned ratings), not modified
rating splits. Analysis of the time series characteristics of the sample revealed that main
rating disagreements have decreased substantially over time, probably because of the
addition of rating modifiers. Main rating splits occurred 21% of the time in 1986, but have
decreased to only 6% of 2002 sample. As a result, the majority of the disagreements are
between modified rating assignments. Capturing modified rating differences is difficult with
an indicator variable empirical design because there are so many combinations of modified
ratings. With nine rating categories per rating agency (Aa1/AA, Aa/AA, Aa3/AA−, A1/A,
A/A, A3/A−, Baa1/BBB, and Baa/BBB), 44 indicator variables would be needed to control
for all of the possible modified rating combinations. The use of a large number of indicator
variables makes reporting and summarizing the results very cumbersome, and leads to small
sample sizes in many of the modified rating combinations.
Our research focus is on whether investors place more weight on the Moody’s or S&P
rating when split ratings occur, and therefore, the use of a single variable that captures the
yield impact of split ratings (SPLIT) independently from the impact of a particular rating
category (RATING) is advantageous. If single variables are used for SPLIT and RATING,
these variables must capture the differences in spreads between rating categories and isolate
the impact of the split rating separately from the impact of a particular rating category. Prior
research has sometimes used ordinal variables to measure ratings (e.g. 20=AAA, 19=AA,
etc.), but this approach ignores the differential effect of each rating increment. In the
municipal market, yield spreads between rating categories increase substantially as ratings
decline (e.g. the spread between Aa and A bonds is smaller than the spread between Baa
and A bonds). We estimate the effect of rating on yields and then use that estimated effect
to create the variables RATING and SPLIT which incorporate both the rating and the
expected effect of rating on yields.
To estimate the effect of ratings on yields, we use a series of indicator variables coded 1
if the rating is in that category (e.g., Aa1) and 0 otherwise with Aaa/AAA as the excluded
group. We restrict the sample to bonds which have identical Moody’s and S&P ratings (N=
6,458) and use the other control variables described above. We regress these variables on
14
The tax preference variable is coded 1 for states which tax interest on out-of-state bonds only, and 0
otherwise.
“Certificates” include certificates of participation, certificates of obligation, certificates of appreciation,
etc. Results were not materially different when separate variables were included for each type of certificate.
15
16
These regional groupings were adopted from Morse and Deely (1983).
70
J Finan Serv Res (2008) 33:57–76
reoffering yields (unreported), and use the estimated coefficients on the rating indicator
variables from this model to create the RATING and SPLIT variables.
The estimated coefficients associated with each rating variable are as follows: Aa1/AA
0.07488; Aa/AA 0.08096; Aa3/AA− 0.16065; A1/A 0.19302; A/A 0.258488; A3/A−
0.37037; Baa1/BBB 0.64013; Baa/BBB 0.7828. Because of the small sample size of the
issues with identical ratings below Baa/BBB, these issues were deleted from the sample.
The RATING variable for each issue in the full sample is set equal to the estimated
coefficient associated with that issue’s Moody’s rating. For example, RATING is coded
0.07488 for Aa1 rated bonds and 0.16065 for Aa3 rated bonds. RATING is a single variable
measuring the effect of the Moody’s rating on reoffering yields. The expected coefficient of
this variable is one because RATING measures the yield premium in basis points over an
Aaa/AAA rated bond. Because the focus of this study is on the relative effect of the S&P
rating compared to the Moody’s rating for split-rated issues, RATING is a control variable
rather than a variable of interest.
To measure the effect of the difference between the Moody’s and S&P rating, the
variable SPLIT is defined as the difference in the coefficients from the above model,
calculated as the estimated coefficient associated with the S&P rating minus the estimated
coefficient associated with the Moody’s rating (with identically rated bonds coded zero).
For example, an issue rated A3/BBB is coded 0.26976 (equal to the 0.64013 premium on
Baa1/BBB bonds minus the 0.37037 premium on A3/A− bonds). Because RATING for this
bond is coded as 0.37037 (the coefficient associated with the Moody’s rating for the bond),
the SPLIT variable reflects the expected yield difference if the market is responding only to
the S&P rating. In the example above, if the market yields follow the S&P rating, we would
expect yields to be 0.26976 higher than the yields associated with the Moody’s rating of A3
on the issue. If the market places value only on the S&P rating, the coefficient on SPLIT
should be one. If the market values the two ratings equally, the coefficient on SPLIT should
be one half. If the market values the Moody’s rating more (less) than the S&P rating, then
we expect the coefficient on SPLIT to be less (more) than one half.17
To examine whether the market’s reliance on Moody’s vs. S&P has changed since 1995,
we also include the variable SPLIT1995 which is coded as SPLIT if the issue is after 1/1/95
and zero otherwise.18 If the market places relatively more reliance on the S&P ratings
compared to the Moody’s rating after 1995, the coefficient on this variable will be greater
than zero. The effect of the S&P rating before 1995 is captured with the coefficient on
SPLIT while the effect of the S&P rating after 1/1/95 is the sum of the coefficients on
SPLIT and SPLIT1995.
To incorporate Fitch ratings in the analysis, five indicator variables19 are included: (1) if
the Fitch rating is higher than both the Moody’s and S&P rating, (2) if the Fitch rating is
lower than both the Moody’s and S&P rating, (3) if the Fitch rating matches the higher
17
We code the variable SPLIT zero for identically rated bonds. Because these issues were used in an earlier
regression model (unreported) to construct the RATING and SPLIT variables, one could argue that
identically rated bonds should be deleted from the sample to avoid overfitting the data. The results are very
similar if these issues are deleted from the sample.
18
While the 1995 cutoff is somewhat arbitrary, it appears reasonable given the timeline of events
surrounding the Justice Department investigation. We experimented with alternative cutoffs of 1994 and
1996 and obtained similar results.
19
We use indicator variables rather than defining a new variable similar to SPLIT because coding
observations lacking a Fitch rating is problematic and comparisons of the Fitch rating to the Moody’s rating
would ignore the comparison of the Fitch rating to the S&P rating.
J Finan Serv Res (2008) 33:57–76
71
Table 3 Descriptive statistics. RATING is the expected effect of the Moody’s rating on bond yields. SPLIT
is the potential incremental effect of the S&P rating on bond yields when the two agencies disagree. RATING
and SPLIT are higher for lower ratings. SPLIT1995 is coded as SPLIT for issues after 1/1/1995, and zero
otherwise. All variables are described in Section 4. The sample includes 12,562 dual rated issues
N=12,562
Variable
Mean
Standard deviation
1st quartile
Median
3rd quartile
5.782
0.177
−0.014
−0.004
6.288
10.599
16.797
1.119
0.162
0.107
0.047
0.930
2.97
1.451
4.850
0.089
−0.007
0.000
5.450
9.684
15.761
5.650
0.125
0.000
0.000
6.160
10.012
16.804
6.700
0.193
0.000
0.000
7.080
10.396
17.834
Continuous variables
Yield of new issues
RATING
SPLIT
SPLIT1995
Interest rates
Years to maturity
Log of issue size
Indicator variables
Variable
Fitch higher
Fitch lower
Fitch same as higher
Fitch same as lower
Fitch same as others
Negotiated
Tax preference
Bank qualified
Callable
Alt. minimum tax
Refunding
Taxable
Revenue
Certificates of participation
Limited tax
Tax increment
Zero coupon bonds
State issuer
County issuer
College issuer
School district issuer
Other issuer
>10 years in the market
Development bonds
Education bonds
Environmental facility
Electric power
General purpose
Health care
Housing
Public facilities
Transportation
New England
Number
90
9
189
33
1,231
5,975
9,276
1,790
10,620
838
5,753
319
5,753
529
290
45
483
1,091
1,707
349
2,094
3,810
10,658
238
2,788
502
314
4,022
832
757
795
811
849
Percent
0.72
0.07
1.50
0.26
9.80
47.56
73.84
14.25
84.54
6.67
45.80
2.54
45.80
4.21
2.31
0.36
3.84
8.68
13.59
2.78
16.67
30.33
84.84
1.89
22.19
4.00
2.50
32.02
6.62
6.03
6.33
6.46
6.76
72
J Finan Serv Res (2008) 33:57–76
Table 3 (continued)
Indicator variables
Mid-Atlantic
South
Great Lakes
Rocky Mountains
Far West
Number
1,690
4,591
2,282
957
1,383
Percent
13.45
36.55
18.17
7.62
11.01
rating on a split-rated issue, (4) if the Fitch rating matches the lower rating on a split-rated
issue, and (5) if the Fitch rating is the same as both the Moody’s and S&P rating.
Table 3 presents the descriptive statistics of the continuous variables and indicator
variables sample. The average (median) of RATING is 0.177 (0.125)20 indicating that the
rating increases yields by an average of 17.7 basis points above the yields on Aaa/AAA
bonds. Because SPLIT is coded zero for identically rated bonds, the average and median of
SPLIT (−0.004 and 0) are quite small. However, the standard deviation of SPLIT is 0.107
indicating a reasonable degree of variation, especially for split-rated bonds. The average
(median) maturity is 10.599 (10.012) and is very close to 10 years because for bonds with
several different maturities, we chose the reoffering yield closest to a 10 year maturity. Only
12% of bonds in the sample have a Fitch rating, and 79% of these issues have the same
Fitch rating as the other ratings. The sample sizes are quite small for the variable indicating
that the Fitch ratings are lower than other ratings (n=9), and for the variable indicating that
the Fitch rating is the same as the lower rating (n=33), therefore caution should be used
when interpreting the results of these variables.
The large majority of the bond issues are callable (84.54%)21 and are from issuers in the
market for more than 10 years (84.84%). Almost half the issues are negotiated (47.56),
refunding bonds (45.8%), or revenue bonds (45.8%). There are few taxable bonds (2.54%),
zero coupon bonds (3.84%), or Certificates of Participation (4.21%), and the results are
robust to excluding these issues. The most common purposes of the bonds were for
education (22.19%) or general purpose (32.02%).
Table 4 presents the results of the regression model where reoffering yield is the
dependent variable. There are 12,562 observations, and the model appears to be well20
Because precisely half the sample was Aa/AA and above, the median of RATING (0.125) is the mid-point
of .08906 (the coding for Aa) and 0 .16065 (the coding for Aa3). In this sample, 8.68% of the issuers were
Aaa, 8.33% were Aa1, 32.99% were Aa, 5.44% were Aa3, 20.54% were A1, 15.91% were A, 1.54% were
A3, 3.7% were Baa1, and 2.87% were Baa.
21
Alternative approaches to examining call provisions are to measure the years to first call or the years to
first call at par. The results of using these variables are essentially the same as the results presented in the
paper. Unlike the call features of corporate bonds, the call features of municipal bonds demonstrate
remarkably little variation. Virtually all callable municipal issues place the call date 5-–10years from issue
date. Because we generally use 10 year reoffering yields, the variation in call features has little effect on
yields. Also, virtually all call premiums are between 0 and 2% of par, so alternative callability measures lack
sufficient variation to possess adequate power. Municipal bonds are not issued at large premiums because the
coupon payments, not the actual interest earned, are exempt from taxation. To prevent investors from
receiving excessive tax benefits, IRS rules prevent significant premiums on tax-exempt bonds. Investors of
tax-exempt bonds issued at a discount receive tax-exemption for only a portion of the interest earned.
Therefore, tax exempt bonds are rarely issued at a significant discount. An exception is zero-coupon bonds
for which the implicit interest is exempt. We control for zero-coupon bonds.
J Finan Serv Res (2008) 33:57–76
73
Table 4 The effect of local government bond ratings on reoffering yields of new issues. The dependent
variable in the regression model is new issue bond yields. All variables are described in Section 4. The
sample includes 12,562 dual rated issues
Variable
Intercept
RATING
SPLIT
SPLIT1995
Fitch higher than other ratings
Fitch lower than other ratings
Fitch same as higher split ratings
Fitch same as lower split ratings
Fitch same as both Moody’s and S&P
Level of interest rates
Average maturity
Log of issue size
Negotiated
Tax preference
Bank qualified
Callable
Alternative minimum tax
Refunding
Taxable
Revenue
Certificates of participation
Limited tax
Tax increment
Zero coupon bonds
State issuer
County issuer
College issuer
School district issuer
Other issuer
>10 years in the market
Development bonds
Education bonds
Environmental facility
Electric power
General purpose
Health care
Housing
Public facilities
Transportation
New England
Mid-Atlantic
South
Great Lakes
Rocky Mountains
Far West
Adjusted R-square=0.9266
Expected sign
+
+
+
+
−
+
−
+
−
+
+
+
+
−
−
+
+
?
+
+
+
+
+
+
?
?
?
?
?
−
?
?
?
?
?
?
?
?
?
?
?
?
?
?
?
Parameter estimate
−2.042
0.991
0.294
0.126
−0.069
−0.146
−0.005
0.004
−0.009
1.036
0.072
0.012
0.047
−0.094
−0.102
0.091
0.019
0.198
1.771
0.052
0.080
0.009
0.186
0.114
−0.023
−0.012
−0.058
0.012
−0.006
−0.024
0.045
0.018
0.017
0.003
0.032
0.224
0.136
0.033
0.046
0.034
0.042
0.023
0.072
0.049
0.030
t-statistic
−39.41
50.84
9.89
1.96
−2.12
−1.45
−0.23
0.08
−0.91
292.47
69.41
4.81
7.01
−14.32
−11.21
11.13
2.71
15.25
99.21
5.90
5.36
0.49
3.94
7.73
−1.98
−1.27
−2.86
1.02
−0.62
−2.99
2.01
1.49
0.99
0.17
3.06
15.88
8.48
2.40
3.37
2.21
3.06
1.95
5.73
3.35
2.12
p-value
0.000
0.000
0.000
0.050
0.034
0.148
0.821
0.934
0.360
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.007
0.000
0.000
0.000
0.000
0.622
0.000
0.000
0.048
0.205
0.004
0.307
0.537
0.003
0.044
0.136
0.323
0.862
0.002
0.000
0.000
0.016
0.001
0.027
0.002
0.051
0.000
0.001
0.034
74
J Finan Serv Res (2008) 33:57–76
specified. The adjusted R-Square is 0.9266. For control variables where the expected sign is
determinant, coefficients tend to be significant with the expected signs. No expectations are
formed about the sign of some control variables. For example, we have no theory to suggest
that county issuers should have larger or smaller yields than cities. Insignificant variables
include four of the five Fitch variables, limited tax, county, school district, other issuer, and
three of the purpose variables.
RATING measures the expected effect of the Moody’s rating on yields. By design, we
expect the coefficient on RATING (0.991) to be very close to one. SPLIT measures the
expected effect on yields of an S&P rating that differs from the Moody’s rating. If the
market places value only on the S&P rating, the coefficient on SPLIT should be one. If
the market values the two ratings equally, the coefficient on SPLIT should be one half. If
the market values the Moody’s rating more (less) than the S&P rating, then we expect the
coefficient on SPLIT to be less (more) than one half. The coefficient on SPLIT is 0.294
which is significantly less than 0.5 (p-value=0.0001). This indicates that prior to 1995, the
market valued the Moody’s rating more than the S&P rating. The coefficient on SPLIT1995
is 0.126 and is significant (p-value=0.050) indicating the market placed greater reliance on
the S&P rating relative to Moody’s after 1/1/95 as compared to before 1/1/95. Although the
combined coefficients of SPLIT and SPLIT1995 (0.420=0.294+0.126) are less than 0.5,
the difference is not statistically significant (p-value=0.172). We are unable to document
that Moody’s continues to be more influential than S&P after 1/1/95.
Only one of the Fitch variables is significant. Issues with identical Moody’s and S&P
ratings, but with a higher Fitch rating have lower yields than bonds without a Fitch rating.
The addition of the Fitch rating to split-rated bonds does not materially impact yields, nor
does the addition of a Fitch rating that is identical to the other two ratings. Although Fitch
ratings have an impact on yields for only a very small percentage of the sample,22 the
impact is favorable when it occurs. Therefore, the acquisition of a Fitch rating would appear
to favor the issuer. However, caution should be used in interpreting the results because of
the small number of issues in which the Fitch rating was lower than the other ratings.
We summarize our main findings as follows. Moody’s rated far more issues than S&P
over the sample period. Moody’s market share dominance diminished substantially from
1993 to 1997, a period also marked by a decline in ratings disagreements. Beginning in
1993, Moody’s received negative publicity related to a lawsuit filed against Moody’s. This
lawsuit was the genesis of a Department of Justice anti-trust investigation that began in
1995. Moody’s appears to have responded to these events by sharply increasing their
relative conservatism in 1997. Moody’s did not recover their previously dominant market
share, but their relative market share stabilized beginning in 1997. Moody’s had a greater
influence on bond yields in the pre-1995 sample period, but Moody’s is not statistically
significantly more influential than S&P in the post-1995 period. Although we suggest that
this loss of market share and influence may have resulted in part from negative publicity,
other possible factors include changes in the agencies’ marketing strategies or turnover of
experienced personnel.
22
There are only 91 issues with identical Moody’s and S&P ratings, but with a higher Fitch rating.
Therefore, Fitch ratings affected yields for only 0 .54% of the full sample (91/16,936). In the regression
model using the recent sample (shown in Table 10), Fitch ratings affect yields for issues with identical
Moody’s and S&P ratings, but with a higher or lower Fitch rating (1.77% of the recent sample).
J Finan Serv Res (2008) 33:57–76
75
4 Conclusions
We examine the impact of split-ratings on yields in the municipal bond market, a market
characterized by less sophisticated investors and less publicly available information than
corporate markets. Using a database containing virtually all primary market municipal
issues from 1986 to 2002, we analyze changes in the relative reputations of Moody’s and
S&P, the two largest raters of municipal bonds. We examine time series changes in market
share and conservatism, and determine which rating agency has the largest influence on
new issue yields.
Our results show that Moody’s rates significantly more issues than S&P, and that
Moody’s ratings tend to be more conservative, particularly for the period since 1995.
Moody’s market share dominance has diminished substantially since 1993, with the
difference between Moody’s and S&P’s market share decreasing from 28% in 1993 to 11%
in 2002. The majority of the drop in market share dominance occurred between 1993 and
1997, a period that corresponds to events surrounding a Justice Department investigation of
Moody’s following accusations by issuers that Moody’s used the threat of unsolicited
ratings to coerce issuers into purchasing Moody’s ratings.
Market share and conservatism trends provide an incomplete picture if Moody’s and
S&P ratings have differential impacts on yields. Issuers will consider a rating agency’s
influence on yields in the rating purchase decision, and will be more likely to purchase
ratings from the more influential agency. As a result, changes in a rating agency’s influence
on yields can alter market share trends. To examine the relative impact of each rating
agency on yields, we regress ratings and a set of control variables on new issue bond yields.
We find that Moody’s ratings have more influence on bond yields than S&P ratings during
the period 1986–1994. However, for the period from 1995 to 2002, Moody’s influence
diminished, and its ratings are no longer significantly more influential than S&P ratings.
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