Forecasting bank failures: Timeliness versus number of failures

Guo Li, Lee W Sanning, Sherrill Shaffer

    Research output: Contribution to journalArticle

    Abstract

    Motivated by the observation that very few banks fail in normal years, we explore the impact of that pattern on the precision of a standard statistical failure model and discuss implications for regulation and risk management. Out-of-sample forecasting is found to be worse for a model fitted to recent data with few failures than for a model fitted to much older data with more failures.
    Original languageEnglish
    Pages (from-to)1549-1552
    JournalApplied Economics Letters
    Volume18
    Issue number16
    DOIs
    Publication statusPublished - 2011

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