We use aggregate banking data to uncover a new fact: U.S. banks counter- cyclically vary the proportion of defaulted loans that they charge-off. The variance of this \charge-offs to defaults" ratio is roughly 15 times larger than that of GDP. Canonical financial accelerator models cannot explain this variance. We show that introducing stochastic default costs into the model helps to resolve the discrepancy with the data. Estimating the augmented model on typical macroeconomic data using Bayesian techniques reveals that the estimated default cost shocks not only help account for the variance of the banking data but also help account for a significant fraction of the U.S. business cycle between 1984 and 2015.

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Department of Economics
Carleton Economics Working Papers (CEWP)
Department of Economics

Gunn, C, Johri, Alok, & Letendre, Marc-André. (2019). Charge-offs, Defaults and U.S. Business Cycles (No. CEP 19-04). Carleton Economics Working Papers (CEWP). Department of Economics.