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Uncertainty and Monetary Policy during Extreme Events

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  • Giovanni Pellegrino
  • Efrem Castelnuovo
  • Giovanni Caggiano

Abstract

How damaging are uncertainty shocks during extreme events such as the great recession and the Covid-19 outbreak? Can monetary policy limit output losses in such situations? We use a nonlinear VAR framework to document the large response of real activity to a financial uncertainty shock during the great recession. We replicate this evidence with an estimated DSGE framework featuring a concept of uncertainty comparable to that in our VAR. We employ the DSGE model to quantify the impact on real activity of an uncertainty shock under different Taylor rules estimated with normal times vs. great recession data (the latter associated with a stronger response to output). We find that the uncertainty shock-induced output loss experienced during the 2007-09 recession could have been twice as large if policymakers had not responded aggressively to the abrupt drop in output in 2008Q3. Finally, we use our estimated DSGE framework to simulate different paths of uncertainty associated to different hypothesis on the evolution of the coronavirus pandemic. We find that: i) Covid-19-induced uncertainty could lead to an output loss twice as large as that of the great recession; ii) aggressive monetary policy moves could reduce such loss by about 50%.

Suggested Citation

  • Giovanni Pellegrino & Efrem Castelnuovo & Giovanni Caggiano, 2020. "Uncertainty and Monetary Policy during Extreme Events," CESifo Working Paper Series 8561, CESifo.
  • Handle: RePEc:ces:ceswps:_8561
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    1. Uncertainty and Monetary Policy during Extreme Events
      by Christian Zimmermann in NEP-DGE blog on 2020-10-23 03:19:34

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    Cited by:

    1. Caggiano, Giovanni & Castelnuovo, Efrem & Delrio, Silvia & Kima, Richard, 2021. "Financial uncertainty and real activity: The good, the bad, and the ugly," European Economic Review, Elsevier, vol. 136(C).
    2. Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2021. "Uncertainty shocks and the great recession: Nonlinearities matter," Economics Letters, Elsevier, vol. 198(C).
    3. Lahcen Bounader & Guido Traficante, 2022. "Robustly optimal monetary policy in a behavioral environment," Working Papers 2022.01, International Network for Economic Research - INFER.
    4. Josué Diwambuena & Jean-Paul K. Tsasa, 2021. "The Real Effects of Uncertainty Shocks: New Evidence from Linear and Nonlinear SVAR Models," BEMPS - Bozen Economics & Management Paper Series BEMPS87, Faculty of Economics and Management at the Free University of Bozen.
    5. Stefan Schiman & Atanas Pekanov, 2020. "Uncertainty in the Euro Area During the First Wave of the COVID-19 Pandemic," WIFO Studies, WIFO, number 66708, June.
    6. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2020. "Measuring Uncertainty and Its Effects in the COVID-19 Era," Working Papers 20-32R, Federal Reserve Bank of Cleveland, revised 05 Jan 2022.

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    More about this item

    Keywords

    house price prediction; machine learning; genetic algorithm; spatial aggregation;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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