Troubled Banks: Why Don’t They All Fail?
Robert Oshinsky
Federal Deposit Insurance Corporation
550 17th Street, NW
Washington, DC 20429
Phone: (202) 898-3813
roshinsky@fdic.gov
Virginia Olin∗
Federal Deposit Insurance Corporation
550 17th Street, NW
Washington, DC 20429
Phone: (202) 898-8711
volin@fdic.gov
March 2005
Working Paper 2005-03
∗ Robert Oshinsky and Virginia Olin are Senior Financial Economists, Division of Insurance and Research, FDIC.
The authors thank John O’Keefe for his overall guidance; Andrew Davenport for his counsel; and Jesse Weiher,
Brian Lamm, James Marino, and the anonymous readers of the FDIC for their careful review of the draft and their
valuable comments and suggestions. The authors also thank Robert DeYoung of the Federal Reserve Bank of
Chicago for his suggestions. Of course, all mistakes are the responsibility of the authors. The views expressed here
are those of the authors and not necessarily those of the Federal Deposit Insurance Corporation.
Robert Oshinsky
Federal Deposit Insurance Corporation
550 17th Street, NW
Washington, DC 20429
Phone: (202) 898-3813
roshinsky@fdic.gov
Virginia Olin∗
Federal Deposit Insurance Corporation
550 17th Street, NW
Washington, DC 20429
Phone: (202) 898-8711
volin@fdic.gov
March 2005
Working Paper 2005-03
∗ Robert Oshinsky and Virginia Olin are Senior Financial Economists, Division of Insurance and Research, FDIC.
The authors thank John O’Keefe for his overall guidance; Andrew Davenport for his counsel; and Jesse Weiher,
Brian Lamm, James Marino, and the anonymous readers of the FDIC for their careful review of the draft and their
valuable comments and suggestions. The authors also thank Robert DeYoung of the Federal Reserve Bank of
Chicago for his suggestions. Of course, all mistakes are the responsibility of the authors. The views expressed here
are those of the authors and not necessarily those of the Federal Deposit Insurance Corporation.
1
Abstract
In this paper we examine troubled banks—those that receive a poor safety-and-soundness
rating when examined—in order to predict future bank state. Besides failure, we see three
alternative outcomes for these banks: recovery, acquisition, or continuation as a problem. The
determinants of bank failure have been much researched, as has failure prediction. Most of this
research uses a binary approach, dividing banks into two groups (those that fail and those that do
not) or predicting one of two states (failure or nonfailure). Because our sample contains only
troubled banks, we can go beyond a two-state approach.
First we use univariate trend analysis to determine whether financial variables differ
within this group of banks depending on the banks’ future states. This analysis suggests that
meaningful relationships exist between these future states and prior-period financial conditions.
We then use financial ratios as explanatory variables in a unified model of bank states, with the
goal of improving predictions of future bank condition.
We gauge the model’s effectiveness by testing the out-of-sample forecasting accuracy.
Our results show that our model compares favorably with the standard binary failure-prediction
model, yet has the added feature of predicting recovery, merge r, or continuation as a problem
bank.
Abstract
In this paper we examine troubled banks—those that receive a poor safety-and-soundness
rating when examined—in order to predict future bank state. Besides failure, we see three
alternative outcomes for these banks: recovery, acquisition, or continuation as a problem. The
determinants of bank failure have been much researched, as has failure prediction. Most of this
research uses a binary approach, dividing banks into two groups (those that fail and those that do
not) or predicting one of two states (failure or nonfailure). Because our sample contains only
troubled banks, we can go beyond a two-state approach.
First we use univariate trend analysis to determine whether financial variables differ
within this group of banks depending on the banks’ future states. This analysis suggests that
meaningful relationships exist between these future states and prior-period financial conditions.
We then use financial ratios as explanatory variables in a unified model of bank states, with the
goal of improving predictions of future bank condition.
We gauge the model’s effectiveness by testing the out-of-sample forecasting accuracy.
Our results show that our model compares favorably with the standard binary failure-prediction
model, yet has the added feature of predicting recovery, merge r, or continuation as a problem
bank.