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A Quantitative Model of Banking Industry Dynamics

Author

Listed:
  • Dean Corbae

    (University of Texas)

  • Pablo D'Erasmo

    (University of Maryland)

Abstract

business cycles, and borrower default frequencies. The model is parameterized to match a set of key aggregate and cross-sectional statistics for the U.S. banking industry. As in the data, the model generates countercyclical interest rates on loans, bank failure rates, borrower default frequencies, and charge-off rates as well as a procyclical loan supply and entry rates. The model can be used to study bank competition and the benefits/costs of policies to subsidize/mitigate bank entry/exit.

Suggested Citation

  • Dean Corbae & Pablo D'Erasmo, 2010. "A Quantitative Model of Banking Industry Dynamics," 2010 Meeting Papers 268, Society for Economic Dynamics.
    • Handle: RePEc:red:sed010:268
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    References listed on IDEAS

    as
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    Cited by:

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    2. Niepmann, Friederike, 2023. "Banking across borders with heterogeneous banks," Journal of International Economics, Elsevier, vol. 142(C).
    3. Eduardo Dávila & Ansgar Walther, 2021. "Corrective Regulation with Imperfect Instruments," NBER Working Papers 29160, National Bureau of Economic Research, Inc.
    4. Roger Aliaga‐Díaz & María Pía Olivero, 2011. "The Cyclicality Of Price‐Cost Margins In Banking: An Empirical Analysis Of Its Determinants," Economic Inquiry, Western Economic Association International, vol. 49(1), pages 26-46, January.
    5. Cornelia Kerl & Friederike Niepmann, 2014. "What determines the composition of international bank flows?," Staff Reports 681, Federal Reserve Bank of New York.
    6. Dávila, Eduardo & Walther, Ansgar, 2020. "Does size matter? Bailouts with large and small banks," Journal of Financial Economics, Elsevier, vol. 136(1), pages 1-22.
    7. Alexandru GRIBINCEA & Georgeta GHERGHINA, 2013. "Necessity To Diminish The Giant Banks," ECONOMY AND SOCIOLOGY: Theoretical and Scientifical Journal, Socionet;Complexul Editorial "INCE", issue 3, pages 71-75.

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