Measuring Systemic Risk in the U.S. Banking System

June 2020 | Kolari, James W.

Due to the 2008-09 global financial crisis, bank regulators implemented supervisory systems to monitor systemic risk that can severely damage the economy.  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 over time. These probabilities are aggregated into a size-weighted measure of systemic risk dubbed SYSTEM. Empirical results show that, due primarily to large banks, volatility in systemic risk increased in 2005 followed by a very large spike from late 2006 to 2008 related to the financial crisis. Tests reveal that SYSTEM: (1) provided early warning signals of the impending 2008−2009 crisis; and (2) indicated relatively lower systemic risk after 2012. Based on these and other results, we conclude that micro- and macro-prudential measures of bank condition are useful in assessing and predicting systemic risk.



  • James W. Kolari
  • Felix Lopez-Iturriaga
  • Ivan Pastor Sanz


Economic Modelling