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Financial Dampening

Author

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  • Mu-Jeung Yang

    (University of Washington, Seattle)

  • Johannes Wieland

    (University of California, San Diego)

Abstract

We propose a novel mechanism, 'financial dampening,' whereby financial sector deleveraging attenuates the effectiveness of monetary policy. In our model of financial intermediation, where banks have leverage targets and asymmetric portfolio adjustment costs, deleveraging banks will have a lower pass-through from reductions in policy rates to credit supply. We find consistent evidence for financial dampening in micro-data on U.S. regulated financial intermediaries. We instrument deleveraging at local banks using average deleveraging at spatially-separate banks of the same bank holding company to isolate local deleveraging independent of local demand conditions. We find that in response to a 1% monetary policy shock, a bank at the 25th percentile of the deleveraging distribution increases its loan growth by 3.70% more than a bank at the 75th percentile according to our baseline specification. Thus, our mechanism provides a rationale for why recoveries from financial crisis may be slow.

Suggested Citation

  • Mu-Jeung Yang & Johannes Wieland, 2015. "Financial Dampening," 2015 Meeting Papers 1022, Society for Economic Dynamics.
  • Handle: RePEc:red:sed015:1022
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    6. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
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    9. Michael Weber & Ali Ozdagli, 2016. "Monetary Policy Through Production Networks: Evidence from the Stock Market," 2016 Meeting Papers 148, Society for Economic Dynamics.
    10. Juvenal, Luciana & Petrella, Ivan, 2024. "Unveiling the dance of commodity prices and the global financial cycle," Journal of International Economics, Elsevier, vol. 150(C).
    11. Bu, Chunya & Rogers, John & Wu, Wenbin, 2021. "A unified measure of Fed monetary policy shocks," Journal of Monetary Economics, Elsevier, vol. 118(C), pages 331-349.
    12. Dominik Bertsche & Robin Braun, 2022. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 328-341, January.
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    More about this item

    JEL classification:

    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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