A Markov model of bank failure estimated using an information-theoretic approach
By: by Dennis Glennon and Amos Golan.
Contributors: Golan, Amos.; United States. Office of the Comptroller of the Currency.
Series: Economic and policy analysis working paper ;; 2003-1; Economic and policy analysis working paper (2000 : Online) ;; 2003-1.
Publisher: Office of the Comptroller of the Currency
Published: 2003
Place of publication: Washington, DC
Language: eng
Format: Electronic resource
Subjects: Bank failures.
Description: "In this paper, we develop an early-warning bank failure model designed specifically to capture the dynamic process underlying the transition from financially sound to closure. We model the transition process as a stationary Markov model and estimate the transition probabilities using a Generalized Maximum Entropy (GME) estimation technique. The GME estimation method is a member of the class of information-theoretic methods, is semi-parametric, and is better suited for estimating models in which the data are limited (e.g., few events, and data availability problems), highly collinear, and measured with error--conditions that often exist with micro-level banking data. In addition, this method allows us to incorporate prior information and impose fewer distributional assumptions relative to conventional maximum likelihood (or full information maximum likelihood) methods. We report estimates of the transition probabilities for nine transition states for the population of nationally chartered banks incorporating the effect of bank-specific and macroeconomic variables from 1984 through 1999"--Office of the Comptroller of the Currency web site.
Notes: Includes bibliographical references.
Title from PDF file as viewed on 1/7/2005.
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Mode of access: World Wide Web.