Model Stability and the Subprime Mortgage Crisis

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.