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Shadow Banking and the great recession : evidence from an estimated DSGE model

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  • Patrick Fève

    (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Alban Moura

    (Banque Centrale du Luxembourg)

  • Olivier Pierrard

    (Banque Centrale du Luxembourg)

Abstract

We argue that shocks to traditional and shadow banks were important drivers of the U.S. economy during the Great Recession and the Slow Recovery. This result follows from a DSGE model featuring a heterogeneous banking sector estimated from macroeconomic and financial observables. Our model attributes the Great Recession to negative shocks to the aggregate supply of loans. A more novel result is that a shock specific to shadow bank intermediation accounts for much of the Slow Recovery. Therefore, our estimates suggest that accounting for the collapse of shadow banking after the financial crisis is important to explain the subdued path of GDP, investment, and inflation several years into the recovery.

Suggested Citation

  • Patrick Fève & Alban Moura & Olivier Pierrard, 2019. "Shadow Banking and the great recession : evidence from an estimated DSGE model," Working Papers hal-04058856, HAL.
    • Handle: RePEc:hal:wpaper:hal-04058856
    Note: View the original document on HAL open archive server: https://hal.science/hal-04058856
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Fève, Patrick & Moura, Alban & Pierrard, Olivier, 2022. "The fall in shadow banking and the slow U.S. recovery," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    2. Gebauer, Stefan & Mazelis, Falk, 2023. "Macroprudential regulation and leakage to the shadow banking sector," European Economic Review, Elsevier, vol. 154(C).
    3. Hodula, Martin & Libich, Jan, 2023. "Has monetary policy fueled the rise in shadow banking?," Economic Modelling, Elsevier, vol. 123(C).
    4. Philipp Kirchner, 2020. "On shadow banking and fiÂ…nancial frictions in DSGE modeling," MAGKS Papers on Economics 202019, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    5. Lei, Ningze & Huang, Liqiang, 2023. "Corporate financing from shadow banking and bond credit spreads," Finance Research Letters, Elsevier, vol. 58(PB).
    6. Kirchner Philipp, 2020. "On Shadow Banking and Financial Frictions in DSGE Modeling," Review of Economics, De Gruyter, vol. 71(2), pages 101-133, August.

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    More about this item

    Keywords

    Shadow banking; Great Recession; Slow Recovery; Estimated DSGE models;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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