Evidence on Conflicts of Interest 1 Matthias Efing University of Geneva and SFI Harald Hau University of Geneva and SFI httpwwwharaldhaucom 2 Did CRAs grant rating favors to issuers in which they had a large business interest ID: 486577
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Structured Debt Ratings: Evidence on Conflicts of Interest
1
Matthias Efing
University of Geneva and SFI
Harald HauUniversity of Geneva and SFIhttp://www.haraldhau.comSlide2
2Did CRAs grant rating favors to issuers in which they had a large business interest?US Justice Department expected to file lawsuit against S&PSpectacular
rating failures during the 2007–08 crisis
2007/2008 crisis triggered by simultaneous downgrades of thousands of structured debt securities (Benmelech & Dlugosz, 2009)
ABX index of AAA-rated MBS dropped by 70% between Jan 2007 and Dec 2008 (Brunnermeier, 2009).Harmful economic implications of rating bias:Undeserved competitive advantages for privileged issuers
Distorted capital allocation Impedes rating-contingent regulation
Research QuestionSlide3
3LiteratureTheoretical literature:
Strong bargaining power of issuers due to “issuer pays model”(
Pagano and Volpin, 2010; White, 2010)Rated firm can “shop for better ratings” (e.g. Skreta & Veldkamp, 2009; Faure-Grimaud et al., 2009)
CRAs might respond to lobbying for rating favors to attract / maintain rating business (Bolton et al., 2012; Mathis et al., 2009) Rating contingent regulation creates incentives to sell regulatory relief in the form of rating favors (Efing, 2012; Harris et al., 2013)Empirical literature:Rating favors in corporate bank ratings (Hau et al. 2013)Investors require higher yields for MBS sold by large issuers
(He et al., 2012)Decline of rating standards during credit boom (Ashcraft et al., 2010)Subjective rating adjustments, rating performance and competitive pressure (Griffin & Tang, 2012; Griffin et al., 2013)Slide4
4
Collateral
Pool
AAA
AAA
AAB
Equity
Complexity of Deal Structures
Credit risk allocated to deal tranches according to seniority
Cash flow cascade further refined
(triggers regulating amortization pro rata vs. in order of seniority; varying tranche access to liquidity reserves or debt insurance; etc.)
Risk allocation to deal tranches intractable for large samples with different asset/collateral types
Deal complexity poses challenge to empirical research on
tranche-level
Slide5
5Advantages of Deal-Level AnalysisIgnore complex intra-deal allocation of credit riskMeasures of collateral quality and credit enhancement mostly available at deal level:
90plus delinquency rate measured 9 months after deal closure to control for collateral quality
Credit enhancement in the form of overcollaterali-zation, debt guarantees, and liquidity
reservesChallenge of deal-level analysis:Need to summarize tranche ratings to deal-levelSlide6
6Methodology – Rating Implied Spreads
Slide7
7Methodology – Deal Level Aggregation of RIS
Slide8
8Methodology – Determinants of deal ratings
Slide9
9
Data – Structured Debt by Deal TypeSlide10
10
Data
– Structured Debt by Origin of CollateralSlide11
11
Data –
Boom-Bust Pattern of Structured DebtSlide12
12
Estimation of
RIS
(Rating-Implied Spreads)
Data from DCM Analytics and Bloomberg (US and EMEA)
10,625 floating-rate notes
(
ABS & MBS) issued at par with Euribor/Libor as base rate
Dummies for unrated tranches
Fixed effects and time-interact. for collateral origin, asset type, currency and issuance half-year
Controls for liquidity, maturity and term structure at issuance
Rating Dummies (
RIS
) alone explain
48% of variation in launch
spreads (column 1)Slide13
13Aggregation of RIS to Deal Rating-Implied Spread
Correlation
: 0.55Slide14
14HypothesisH1: Conflicts of Interest and Ratings Inflation
Issuers who generate more rating business (high ASSB) (i) receive better ratings and (ii) benefit from lower rating-implied spreadsSlide15
15H1: Evidence from Subordination LevelsSlide16
16
H1: Evidence from Deal Rating Implied Spreads
European sample
726 ABS/MBS deals
1,501 deal-CRA pairs
6,638 tranche ratings
Robust std. errors clustered by deal as well as by issuer
Two std. dev. of
Log ASSB
(2
∙
1.47)
=>
DRIS
reduction of 9 basis points for avg. deal with
DRIS
=
12 basis points.Slide17
17HypothesisH2: Rating Favors by Deal Quality and Asset Type
Rating favors are concentrated in those deals for which they are most profitable to issuers and CRAs.Deals of low quality benefit from larger rating favors.
(more profitable than rating favors on already high ratings)More complex ABS
benefit from larger rating favors.(rating precision more expensive; external quality verification more difficult)Slide18
18H2: Quantile RegressionsSlide19
19H2: Quantile Regressions
MBS (ABS) account for
57% (43%) of observations with DRIS
beyond Q90.Slide20
20
H2: Rating Favors by Asset Type
…Slide21
21HypothesisH3: Conflicts of Interest over the Credit Cycle
Rating favors are more pronounced during credit booms.
(lower default probabilities & reputational costs;
best analysts work for banks rather than for CRAs)Slide22
… 22
H3: Conflicts of Interest over the Credit CycleSlide23
23HypothesisH4: Ratings Shopping over the Credit Cycle
During credit booms risk aversion and
perceived asymmetric information are low. Issuers suppress bad ratings so that deals rated by only one CRA have on average better ratings.
In normal times issuers publish multiple ratings to mitigate adverse selection. Only very risky deals with on average worse ratings are rated by just one CRA.Slide24
… 24
H4: Ratings Shopping over the Credit CycleSlide25
… 25
Robustness: CRA fixed effects & interactionsSlide26
26Robustness: Alternative DRIS Models
Ca.
1.5%
of
avg.
deal unsecuritized
Base line regress.:
Weight unsec. part of deal with dummy for
Unrated Junior
Columns (1-2):
Weight unsec. deal part with avg.
RIS
Columns (3-4):
Weight unsec. deal part with
RIS(Junk)Slide27
27
Robustness: Rating Favors Priced Into Yield Spreads
Yield spreads might contain a premium for the risk that rating of security is inflated.
Estimate new spread model and control for (log) securitization business shared between CRAs and security issuers.
(coefficient not significant)
Re-computed
all RIS and DRIS and rerun regression for Hypothesis 1.Slide28
28
Robustness: Regression based on AAA subordination
E.g. Ashcraft et al. (2010), He et al. (2011) use level of AAA subordination to summarize tranche ratings to deal level.Slide29
29Main findings and policy implicationsStatistically and economically large rating favors
Deals receive better credit ratings if CRA has a large business interest
in the deal issuer. Reallocation of resources from disadvantaged to large issuers. Competitive
distortions likely to cause bank concentration and a too big to fail status.Rating favors more pronounced for credit risk lemons
Rating favors twice as large for the 10% of deals with highest rating-implied credit risk. Incentive distortion to supply more and more low quality products to the market causing a quality degradation during the structured debt boom 2004-06.