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Model Stability and the Subprime Mortgage Crisis

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  • Xudong An

    ()

  • Yongheng Deng

    ()

  • Eric Rosenblatt

    ()

  • Vincent Yao

    ()

Abstract

We study the potential model instability problem with respect to mortgage default risk and examine to what extent it helps explain the default shock during the recent crisis. We find that econometric default risk models based on historical data can be unstable over time. Due to temporal shifts in the parameters, default prediction of the 2006 vintage subprime loans based on hazard and Logit models estimated with 2003 vintage loan data can generate over 40% fewer defaults than the actual number, assuming perfect forecast of house price change. We also find that the combined impact of parameter instability and bad forecast of HPI enlarges the under-prediction of default rate but the marginal impact of parameter instability is larger than that of bad HPI forecast. Our findings have important implications regarding model limitations and risk, model improvements, economic capital, and regulatory reform. Copyright Springer Science+Business Media, LLC 2012

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Bibliographic Info

Article provided by Springer in its journal The Journal of Real Estate Finance and Economics.

Volume (Year): 45 (2012)
Issue (Month): 3 (October)
Pages: 545-568

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Handle: RePEc:kap:jrefec:v:45:y:2012:i:3:p:545-568

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Web page: http://www.springerlink.com/link.asp?id=102945

Related research

Keywords: Subprime mortgage; Default risk; Model stability; Hazard model; Logit model;

References

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Cited by:
  1. Yongheng Deng, 2012. "Discussant remarks on Chihiro Shimizu, Kiyohiko G Nishimura and Tsutomu Watanabe’s paper House prices from magazines, realtors,and the Land Registry," BIS Papers chapters, in: Bank for International Settlements (ed.), Property markets and financial stability, volume 64, pages 39-41 Bank for International Settlements.
  2. W. Scott Frame & Lawrence J. White, 2014. "Technological Change, Financial Innovation, and Diffusion in Banking," Working Papers 14-02, New York University, Leonard N. Stern School of Business, Department of Economics.

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