Turning to empirical literature, Demirguc-Kunt and Detragiache (1998) study the determinants of the probability of a banking crisis around the world in 1980—1994 using a multivariate Logit model. They find that bank crises are more likely in countries with low GDP growth, high real interest rates, high inflation rates, and explicit deposit insurance system. Countries that are more susceptible to balance of payments crises also have a higher probability of experiencing banking crises.
Moreover, Demirguc-Kunt and Detragiache (2002) specifically investigate the relation between the explicit deposit insurance and stability in banking sector across countries. They confirm and strengthen the findings of Demirguc-Kunt and Detragiache (1998) that…show more content… They find that banks with lower capitalization, higher ratios of loans to assets, poor quality loan portfolios and lower earnings have higher risk of failure. Banks located in states where branching is permitted are less likely to fail. This may indicate that an ability to create a branch network, and an associated ability to diversify, reduces banks’ susceptibility to failure. Further, the more efficiently a bank operates, the less likely the bank is to…show more content… Their study makes advance predictions of the performance of 24 Taiwan banks based on uncertain financial data (reported in ranges) and also presents the prediction of efficiency scores (again in ranges). They find that the model-predicted efficiency scores are similar to the actual (calculated from the data) efficiency scores. They also show that the poor performances of the two banks taken over by the Financial Restructuring Fund of Taiwan could actually have been predicted in advance using their method.
Tsionas and Papadakis (2009) provide a statistical framework that can be used with stochastic DEA. In order to make inference on the efficiency scores, they use a Bayesian approach to the problem set up around simulation techniques. They also test the new methods on the efficiency of Greek banks, and find that the majority of the Greek banks operate close to market best-practices.
Cielen et al (2004) compare the performance of a DEA model, Minimized Sum of Deviations (MSD), and a rule induction (C5.0) model in bankruptcy prediction. MSD is a combination of linear programming (LP) and DA. Using data from the National Bank of Belgium, they find that MSD, DEA and C5.0 obtain the correct classification rates of failure for 78.9%, 86.4% and 85.5% of banks, respectively. They conclude that DEA outperformed the C5.0 and MSD models in terms of