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Model Stability and the Subprime Mortgage Crisis

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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.

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Notes

  1. Major mortgage investors had to substantially write down their mortgage assets and rating agencies had to adjust their ratings of mortgage-related securities to reflect revised expectations of default losses. Many mortgage lenders went into bankruptcy due to unexpected losses.

  2. “CDO Boom Masks Subprime Losses, Abetted by S&P, Moody’s, Fitch,” Bloomberg News, May 31, 2007.

  3. “The Financial Crisis and the Role of Federal Regulators,” the House Committee on Oversight and Government Reform hearing on October 23, 2008.

  4. There is also a literature that tries to understand the implied (ex ante) default risk through mortgage prices (see, Kau et al. 1994; Capozza et al. 1998 and many others).

  5. See, for example, von Furstenberg and Green (1974), Follain and Struyk (1977), Vandell (1978); Jackson and Kaserman (1980); Foster and Van Order (1984, 1985), Clauretie (1987), and Quigley and Van Order (1991).

  6. For example, lenders made important changes in response to pressure on revealed redlining practice and Fannie Mae revised standards on ARMs based on academic studies (Vandell 1993).

  7. Other examples include Williams et al. (1974) and Webb (1982).

  8. Ciochetti et al. (2003), Chen and Deng (2003), and An et al. (2009) apply the model to CMBS loan default.

  9. See Morton (1975), Episcopos et al. (1998), and Feldman and Gross (2005), respectively.

  10. Notice that the loan duration time T is different from the natural time t, which allows identification of the model.

  11. Alternatively, Demyanyk and Van Hemert 2009 and Elul 2009 use house price appreciation.

  12. The regression results are available upon request.

  13. A large fraction of the subprime mortgage loans are ARMs, e.g. about 38 percent of the LP sample are 2/28 ARMs.

  14. 10-year Treasury rate for FRM 30 and 7-year Treasury rate for FRM 15.

  15. Those predictions together with scenario analysis and sensitivity analysis are then used to assist mortgage underwriting, pricing and risk management.

  16. We set the insignificant parameters to zero because they are statistically indifferent from zero.

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Acknowledgements

The authors are grateful to John Clapp, David Geltner, Richard Green, Michael Lea, David Ling, Tony Sanders, and Brent Smith for helpful discussions and suggestions. We also thank participants in the Maastricht-MIT-NUS 2009 Real Estate Finance and Investment Symposium, the 2010 Weimer School of Advanced Studies in Real Estate and Land Economics, the Finance Seminar at San Diego State University for helpful comments.

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Authors and Affiliations

  1. Department of Finance, College of Business Administration, San Diego State University, 5500 Campanile Dr., San Diego, CA, 92182-8236, USA

    Xudong An

  2. Institute of Real Estate Studies, National University of Singapore, 21 Heng Mui Keng Terrace, #04-02, Singapore, 119613, Singapore

    Yongheng Deng

  3. Fannie Mae, 3900 Wisconsin Avenue, Washington, DC, 20016, USA

    Eric Rosenblatt & Vincent W. Yao

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  1. Xudong An
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  2. Yongheng Deng
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Correspondence to Yongheng Deng.

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An, X., Deng, Y., Rosenblatt, E. et al. Model Stability and the Subprime Mortgage Crisis. J Real Estate Finan Econ 45, 545–568 (2012). https://doi.org/10.1007/s11146-010-9283-y

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