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Forecasting Bank Failure : A Non-Parametric Frontier Estimation Approach


  • Richard S. BARR

    (Southern Methodist University)

  • Lawrence M. SEIFORD

    (University of Massachusetts)

  • Thomas F. SIEMS

    (Federal Reserve Bank of Dallas)


The dramatic rise in bank failures over the last decade has led to a search for leading indicators so that costly bailouts might be avoided. While the quality of a bank's management is generally acknowledged to be a key contributor to institutional collapse, it is usually excluded from early-warning models for lack of a metric. This paper describes a new approach for quantifying a bank's managerial efficiency, using a data- envelopment-analysis model that combines multiple inputs and outputs to compute a scalar measure of efficiency. This new metric captures an elusive, yet crucial, element of institutional success: management quality. New failure-prediction models for detecting a bank's troubled status which incorporate this explanatory variable have proven to be robust and accurate, as verified by in-depth empirical evaluations, cost sensitivity analyses, and comparisons with other published approaches

Suggested Citation

  • Richard S. BARR & Lawrence M. SEIFORD & Thomas F. SIEMS, 1994. "Forecasting Bank Failure : A Non-Parametric Frontier Estimation Approach," Discussion Papers (REL - Recherches Economiques de Louvain) 1994041, Universit√© catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  • Handle: RePEc:ctl:louvre:1994041

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    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • D69 - Microeconomics - - Welfare Economics - - - Other
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure


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