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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. Andrea Lanteri, 2018. "The Market for Used Capital: Endogenous Irreversibility and Reallocation over the Business Cycle," American Economic Review, American Economic Association, vol. 108(9), pages 2383-2419, September.
    2. Lawrence J. Christiano & Martin S. Eichenbaum & Mathias Trabandt, 2016. "Unemployment and Business Cycles," Econometrica, Econometric Society, vol. 84(4), pages 1523-1569, July.
    3. Glenn D. Rudebusch & Eric T. Swanson, 2012. "The Bond Premium in a DSGE Model with Long-Run Real and Nominal Risks," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(1), pages 105-143, January.
    4. Hall, Alastair R. & Inoue, Atsushi & Nason, James M. & Rossi, Barbara, 2012. "Information criteria for impulse response function matching estimation of DSGE models," Journal of Econometrics, Elsevier, vol. 170(2), pages 499-518.
    5. Oliver de Groot & Alexander W. Richter & Nathaniel A. Throckmorton, 2018. "Uncertainty Shocks in a Model of Effective Demand: Comment," Econometrica, Econometric Society, vol. 86(4), pages 1513-1526, July.
    6. Guerron-Quintana, Pablo & Inoue, Atsushi & Kilian, Lutz, 2017. "Impulse response matching estimators for DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 144-155.
    7. Renée Fry & Adrian Pagan, 2011. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 938-960, December.
    8. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    9. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
    10. Fabio Canova, 2009. "What Explains The Great Moderation in the U.S.? A Structural Analysis," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 697-721, June.
    11. Francisco RUGE-MURCIA, 2014. "Indirect Inference Estimation of Nonlinear Dynamic General Equilibrium Models : With an Application to Asset Pricing under Skewness Risk," Cahiers de recherche 15-2014, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    12. Dario Caldara & Jesus Fernandez-Villaverde & Juan Rubio-Ramirez & Wen Yao, 2012. "Computing DSGE Models with Recursive Preferences and Stochastic Volatility," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 15(2), pages 188-206, April.
    13. Leduc, Sylvain & Liu, Zheng, 2016. "Uncertainty shocks are aggregate demand shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 20-35.
    14. Michele Piffer & Maximilian Podstawski, 2018. "Identifying Uncertainty Shocks Using the Price of Gold," Economic Journal, Royal Economic Society, vol. 128(616), pages 3266-3284, December.
    15. Atsushi Inoue & Barbara Rossi, 2011. "Identifying the Sources of Instabilities in Macroeconomic Fluctuations," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1186-1204, November.
    16. Brent Bundick & Andrew Lee Smith, 2016. "The dynamic effects of forward guidance shocks," Research Working Paper RWP 16-2, Federal Reserve Bank of Kansas City.
    17. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2008. "How Structural Are Structural Parameters?," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 83-137, National Bureau of Economic Research, Inc.
    18. Eric T. Swanson, 2012. "Risk Aversion and the Labor Margin in Dynamic Equilibrium Models," American Economic Review, American Economic Association, vol. 102(4), pages 1663-1691, June.
    19. Jermann, Urban J., 1998. "Asset pricing in production economies," Journal of Monetary Economics, Elsevier, vol. 41(2), pages 257-275, April.
    20. Julio J. Rotemberg, 1982. "Monopolistic Price Adjustment and Aggregate Output," Review of Economic Studies, Oxford University Press, vol. 49(4), pages 517-531.
    21. Hannah Schildberg-Hörisch, 2018. "Are Risk Preferences Stable?," Journal of Economic Perspectives, American Economic Association, vol. 32(2), pages 135-154, Spring.
    22. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
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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. 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.

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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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