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Forecasting bank failures: Timeliness versus number of failures

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Authors

Li, Guo
Sanning, Lee W
Shaffer, Sherrill

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Journal ISSN

Volume Title

Publisher

Routledge, Taylor & Francis Group

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.

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Citation

Source

Applied Economics Letters

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Restricted until

2037-12-31
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