On the efficiency of US community banks around the COVID-19 outbreak

This paper examines how the COVID-19 pandemic affected the efficiency of 569 publicly traded community banks in the United States. Using a slacks-based measure (SBM) DEA modelling framework, we analyse quarterly data around the pandemic outbreak to estimate overall technical efficiency, pure technical efficiency, and scale efficiency scores. We use four assessment perspectives: general, loan-volume focused, loan-income focused, and income-focused models. Additionally, we incorporate credit risk adjustment in loan and income-focused models. Our findings indicate that U.S. community banks enhanced their efficiency during and after COVID-19, surpassing pre-pandemic levels. Managerial efficiency drove this improvement. Adjusting for default risk weakened efficiency improvements, revealing a more accurate picture of efficiency changes during and after the pandemic.