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Are Sovereign Ratings Informative? Comments on Cavallo, Powell and Rigobon

Are Sovereign Ratings Informative? Comments on Cavallo, Powell and Rigobon. Jeromin Zettelmeyer Research Department IMF * *Personal views. Need not reflect the views of the IMF. Main reactions. Excellent paper Methodologically very careful

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Are Sovereign Ratings Informative? Comments on Cavallo, Powell and Rigobon

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  1. Are Sovereign Ratings Informative? Comments on Cavallo, Powell and Rigobon Jeromin Zettelmeyer Research Department IMF * *Personal views. Need not reflect the views of the IMF.

  2. Main reactions • Excellent paper • Methodologically very careful • Significantly goes beyond the literature, in what is already a crowded field • This presentation: • Why this is an important paper • What I don’t find completely convincing • Why, in the end, I am nonetheless convinced.

  3. Context • Question: do credit ratings contain information about country fundamentals, even though credit rating agencies do not have particularly privileged information about these fundamentals? • Usual approach: do credit ratings influence spreads over and above the impact of fundamentals? • Answer: Yes (Eichengreen and Mody, 1998; Dell’Ariccia, Schnabel, Zettelmeyer, 2006; Powell and Martinez, 2007) • Case closed? No! • Significant effects of credit ratings may just reflect the poverty of spreads models. Market may have much more information about fundamentals than is captured on the RHS of the models

  4. Contribution of this paper • Raises the bar: do credit ratings influence spreads over and above the information that is already aggregated in market variables? • Answer: Again, Yes (suggested both by specification test and “horse race”) • Ifwe believe the answer, this is a much stronger result than the one that is usually found in the spreads literature • Should we believe the answer?

  5. Specification test: methodological issues • Approach: Hausmann specification test based on a regression of future spreads/stock prices/exchange rates on current spreads, using credit ratings as instruments • Rejection of the Null of no misspecification interpreted as evidence for the “informativeness” of ratings. • Two potential problems with this approach: • Perhaps rejection of no misspecification Null indicates just that: misspecification! → bias towards “finding informativeness” • Lack of power to reject Null → bias against “finding informativeness” • To the author’s credit, they emphasize first problem but not second

  6. Potential problem of specification test • Authors show that specification test is a test of informativeness if: • Either: No misspecification in the OLS regression under the Null hypothesis that spreads are a perfect signal of fundamental; • OLS and IV both consistent under the Null • Or: Misspecification in the OLS regression even under the Null hypothesis, but “error in variable” (EIV) in ratings uncorrelated with error in the OLS regression • OLS and IV have identical biases under the Null. • But in more general settings, test breaks down (could reject Null even if spreads are a “sufficient statistic”) • in particular, if “error in variable” in the rating is correlated with the error in the OLS regression

  7. Should we buy the authors’ interpretation of the specification test? • Authors’ argument: • If there is misspecification because EIV in the rating is correlated with the error in the OLS regression, then EIV should be bigger the bigger the window around ratings change • bigger windows should lead to more rejections. • in fact, we don’t see this. So we are fine. • Potential problem: • Widening the window has not one but two effects: • makes potential misspecification problem worse (as authors say) • but also: weakens the power of the test (because instrument becomes noisier, and hence weaker). • If second effect dominates, might see decrease in rejections even with misspecification

  8. Even though specification test is not watertight, the findings are convincing • Specification test allows multiple interepretations: • spreads are not a sufficient statistic, i.e. ratings are informative • model is misspecified. • or both! • However, “horserace”, and discussion of anticipation, show not only that ratings seem to have an effect (this could be spurious) but that they have an effect exactly as one might think. • rating changes affect market variables in the “right” direction; • size of the effect depends on the degree to which they are anticipated.

  9. Conclusion • Even though no single test or regression in this paper is entirely immune from the methodology police, the individual pieces fit together so well that they make a convincing case. • By far the strongest case made so far (and, I suspect, that could ever be made) that ratings are informative over and above information already contained in market variables. • Clearly, if ratings matter in a plain vanilla market such as sovereign debt, they should matter much more in markets where information costs are higher

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