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Charge-offs, Defaults and U.S. Business Cycles

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Abstract

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 discrepancywith 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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  • Christopher M. Gunn & Alok Johri & Marc-André Letendre, 2019. "Charge-offs, Defaults and U.S. Business Cycles," Carleton Economic Papers 19-04, Carleton University, Department of Economics.
    • Handle: RePEc:car:carecp:19-04
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    More about this item

    Keywords

    Charge-offs and defaults; default cost shocks; financial acceleratormodels; business cycles;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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