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Ratings Shopping and Asset Complexity: A Theory of Ratings Inflation


Vasiliki Skreta


NYU Stern School of Business; Leonard N. Stern School of Business - Department of Economics

Laura Veldkamp


New York University - Stern School of Business; National Bureau of Economic Research (NBER)

February 2009

NBER Working Paper No. w14761

Abstract:     
Many identify inflated credit ratings as one contributor to the recent financial market turmoil. We develop an equilibrium model of the market for ratings and use it to examine possible origins of and cures for ratings inflation. In the model, asset issuers can shop for ratings -- observe multiple ratings and disclose only the most favorable -- before auctioning their assets. When assets are simple, agencies' ratings are similar and the incentive to ratings shop is low. When assets are sufficiently complex, ratings differ enough that an incentive to shop emerges. Thus, an increase in the complexity of recently-issued securities could create a systematic bias in disclosed ratings, despite the fact that each ratings agency produces an unbiased estimate of the asset's true quality. Increasing competition among agencies would only worsen this problem. Switching to an investor-initiated ratings system alleviates the bias, but could collapse the market for information.

Number of Pages in PDF File: 31

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Date posted: February 26, 2009  

Suggested Citation

Skreta, Vasiliki and Veldkamp, Laura, Ratings Shopping and Asset Complexity: A Theory of Ratings Inflation (February 2009). NBER Working Paper No. w14761. Available at SSRN: http://ssrn.com/abstract=1349593

Contact Information

Vasiliki Skreta (Contact Author)
NYU Stern School of Business ( email )
44 West 4th Street
New York, NY NY 10012
United States
Leonard N. Stern School of Business - Department of Economics
269 Mercer Street
New York, NY 10003
United States
Laura Veldkamp
New York University - Stern School of Business ( email )
44 West 4th St. - Suite 7-180
New York, NY 100012
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
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