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http://ssrn.com/abstract=1296982
 
 

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The Failure of Models that Predict Failure: Distance, Incentives and Defaults


Uday Rajan


University of Michigan - Stephen M. Ross School of Business

Amit Seru


University of Chicago - Booth School of Business and NBER

Vikrant Vig


London Business School

August 1, 2010

Chicago GSB Research Paper No. 08-19
EFA 2009 Bergen Meetings Paper
Ross School of Business Paper No. 1122

Abstract:     
Statistical default models, widely used to assess default risk, are subject to a Lucas critique. We demonstrate this phenomenon using data on securitized subprime mortgages issued in the period 1997--2006. As the level of securitization increases, lenders have an incentive to originate loans that rate high based on characteristics that are reported to investors, even if other unreported variables imply a lower borrower quality. Consistent with this behavior, we find that over time lenders set interest rates only on the basis of variables that are reported to investors, ignoring other credit-relevant information. The change in lender behavior alters the data generating process by transforming the mapping from observables to loan defaults. To illustrate this effect, we show that a statistical default model estimated in a low securitization period breaks down in a high securitization period in a systematic manner: it underpredicts defaults among borrowers for whom soft information is more valuable. Regulations that rely on such models to assess default risk may therefore be undermined by the actions of market participants.

Number of Pages in PDF File: 46

Keywords: Securitization, screening, incentives, subprime, defaults, mortgages, disintermediation, models, lucas critique, soft information, hard information, failure, predictability

JEL Classification: G21

working papers series


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Date posted: November 10, 2008 ; Last revised: August 15, 2010

Suggested Citation

Rajan, Uday and Seru, Amit and Vig, Vikrant, The Failure of Models that Predict Failure: Distance, Incentives and Defaults (August 1, 2010). Chicago GSB Research Paper No. 08-19; EFA 2009 Bergen Meetings Paper; Ross School of Business Paper No. 1122. Available at SSRN: http://ssrn.com/abstract=1296982 or http://dx.doi.org/10.2139/ssrn.1296982

Contact Information

Uday Rajan
University of Michigan - Stephen M. Ross School of Business ( email )
Ross School of Business
701 Tappan Street, Room D4203
Ann Arbor, MI 48109
United States
734-647-4027 (Phone)
Amit Seru (Contact Author)
University of Chicago - Booth School of Business and NBER ( email )
5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

Chicago Booth School of Business Logo

Vikrant Vig
London Business School ( email )
Sussex Place
Regent's Park
London, London NW1 4SA
United Kingdom
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