Banking Crises, Early Warning Models, and Efficiency

Pavlos Almanidis () and Robin Sickles
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Pavlos Almanidis: Ernst & Young LLP

Chapter Chapter 14 in Advances in Efficiency and Productivity, 2016, pp 331-364 from Springer

Abstract: Abstract This paper proposes a general model that combines the Mixture Hazard Model with the Stochastic Frontier Model for the purposes of investigating the main determinants of the failures and performances of a panel of U.S. commercial banks during the financial crisis that began in 2007. The combined model provides measures of the probability and time to failure conditional on a bank’s performance and vice versa. Both continuous-time and discrete-time specifications of the model are considered in the paper. The estimation is carried out via the expectation-maximization algorithm due to incomplete information regarding the identity of at-risk banks. In- and out-of-sample predictive accuracy of the proposed models is investigated in order to assess their potential to serve as early warning tools.

Keywords: Financial distress; Panel data; Bank failures; Semiparametric mixture hazard model; Discrete-time mixture hazard model; Bank efficiency; C33; C41; C51; D24; G01; G21 (search for similar items in EconPapers)
Date: 2016
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Working Paper: Banking Crises, Early Warning Models, and Efficiency (2015)
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DOI: 10.1007/978-3-319-48461-7_14

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