Hazard versus Probit in Predicting U.S. Bank Failures: A Regulatory Perspective over Two Crises
40 Pages Posted: 24 Aug 2009 Last revised: 25 Aug 2018
Date Written: December 31, 2017
We compare the out-of-sample accuracy of two methodologies—the time-varying hazard model of Shumway (2001) and the static probit model used by Cole and Gunther (1998)—in forecasting U.S. bank failures from both academic and regulatory perspectives. When we limit both models to financial data available at the time of prediction, we find that the probit model slightly outperforms the hazard model, indicating that the superior performance of hazard models documented in previous empirical research is attributable to use of more timely financial data rather than to incorporation of time-varying covariates. We also find that a parsimonious specification fit to data over 1985-1993 performs well in forecasting bank failures during 2009-2010—evidence that the characteristics of “distressed banks” have experienced little change over the past two decades despite substantial changes in structure and regulation of the U.S. banking industry. Our findings support supervision focusing on banks’ traditional CAMELS risk ratios.
Keywords: bank failure, bank regulation, failure prediction, hazard model, probit model, financial crisis
JEL Classification: G17, G21, G28
Suggested Citation: Suggested Citation