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Bank failures are critical events that have far-reaching implications for the financial system and various stakeholders. This study aims to focus on analyzing the phenomenon of small bank failures in the USA.

This study adopts the coarsened exact matching (CEM) technique to enhance the reliability of the analysis. By matching similar observed characteristics, the CEM approach helps to address potential selectivity bias and facilitates a more accurate estimation of the treatment effect. This study uses a data set covering the period from 2000 through 2019 and includes 523 failed bank observations and 43,605 nonfailed bank observations.

The results reveal several key findings. Small banks, especially those with lower yields on earning assets, those with lower charge-offs on loans and leases, those with higher core capital ratios and those with higher Fed Funds rates are found to be more susceptible to failure.

Some results align with initial predictions, whereas others present contrasting outcomes.

This study underscores the significance of understanding the factors contributing to bank failure and emphasizes the importance of studying small bank failures in particular.

This study uses the CEM method. CEM is a comprehensive approach that combines matching, sample trimming and reweighting techniques. When applying CEM, researchers carefully select a set of core variables to achieve balance between the treated and control groups. The CEM process involves discretizing each continuous variable into distinct bins or categories, a process known as “coarsening.” It then requires an exact match among these binned variables between the treated and control units, which constitutes the matching step in CEM.