Long-term Examination of Bank Crashes Using Panel Logistic Regression: Turkish Banks Failure Case

Abstract

Crises in the financial sector over the last two decades have shown the importance of early warning systems, especially for bank failures. This study aims to develop an early warning system for Turkish commercial bank failures using panel data from 2002 to 2012. The data was analyzed using pooled logistic regression versus random panel logistic regression. The dependent variable was the bank failure, defined as the return-on assets ratio. Factor analysis was used to construct independent variables of financial ratios. The meaningful factors were found as: Interest income and expenditures, Equity, Other income and expenditures, Balance sheet, Deposit, Due, Asset quality. When the focus is sensitivity, the best prediction performance was obtained using random-effect logistic regression.