This paper investigates the long-run recovery experience of U.S. banks that received capital infusions under the Capital Purchase Program (CPP), a part of the Troubled Asset Relief Program (TARP). Based on a dynamic recovery model, our results show that recovering CPP banks tended to be in...

This paper develops a novel measure of systemic risk that combines mapping technology and regression methods. Self-organizing maps (SOM) and lasso logistic regressions are employed to estimate default probabilities for individual U.S. commercial banks from 2001 to 2017. Subsequently, these...

The credit hypothesis maintains that nonmonetary factors worsen declines in output during severe economic contractions, which has been a prominent rationale for stringent bank regulation. We apply recent advances in time series analysis to re-examine the role of U.S. bank failures in the Great...

This paper utilizes neural network mapping technology to assess the dynamic nature of systemic risk over time in the banking industry. We combine the nonparametric method of trait recognition with self-organizing maps (SOMs) to generate yearly pictures of the 16 largest U.S. banks' financial...