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Uncertainty Shocks in a Model of Effective Demand: Comment

Author

Listed:
  • Oliver de Groot
  • Alexander W. Richter
  • Nathaniel A. Throckmorton

Abstract

Basu and Bundick, 2017 showed an intertemporal preference volatility shock has meaningful effects on real activity in a New Keynesian model with Epstein and Zin, 1991 preferences. We show that when the distributional weights on current and future utility in the Epstein–Zin time aggregator do not sum to 1, there is an asymptote in the responses to such a shock with unit intertemporal elasticity of substitution. In the Basu–Bundick model, the intertemporal elasticity of substitution is set near unity and the preference shock only hits current utility, so the sum of the weights differs from 1. We show that when we restrict the weights to sum to 1, the asymptote disappears and preference volatility shocks no longer have large effects. We examine several different calibrations and preferences as potential resolutions with varying degrees of success.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:emetrp:v:86:y:2018:i:4:p:1513-1526
    DOI: 10.3982/ECTA15405
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    References listed on IDEAS

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    1. Fernández-Villaverde, Jesús & Gordon, Grey & Guerrón-Quintana, Pablo & Rubio-Ramírez, Juan F., 2015. "Nonlinear adventures at the zero lower bound," Journal of Economic Dynamics and Control, Elsevier, vol. 57(C), pages 182-204.
    2. Susanto Basu & Brent Bundick, 2017. "Uncertainty Shocks in a Model of Effective Demand," Econometrica, Econometric Society, vol. 85, pages 937-958, May.
    3. Alexander W. Richter & Nathaniel Throckmorton, 2017. "A New Way to Quantify the Effect of Uncertainty," Working Papers 1705, Federal Reserve Bank of Dallas, revised 23 Feb 2018.
    4. Epstein, Larry G & Zin, Stanley E, 1991. "Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: An Empirical Analysis," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 263-286, April.
    5. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, August.
    6. Haroon Mumtaz & Francesco Zanetti, 2013. "The Impact of the Volatility of Monetary Policy Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(4), pages 535-558, June.
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    Cited by:

    1. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2020. "Economic Policy Uncertainty Spillovers in Booms and Busts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(1), pages 125-155, February.
    2. Alexander W. Richter & Nathaniel Throckmorton, 2017. "A New Way to Quantify the Effect of Uncertainty," Working Papers 1705, Federal Reserve Bank of Dallas, revised 23 Feb 2018.
    3. Bonciani, Dario & Oh, Joonseok Jason, 2019. "The long-run effects of uncertainty shocks," Bank of England working papers 802, Bank of England.
    4. Oliver de Groot & Alexander W. Richter & Nathaniel A. Throckmorton, 2018. "Valuation Risk Revalued," CDMA Working Paper Series 201803, Centre for Dynamic Macroeconomic Analysis.
    5. Grzegorz Długoszek, 2018. "Macroeconomic Effects of Financial Uncertainty," 2018 Meeting Papers 1128, Society for Economic Dynamics.
    6. Ying Tung Chan, 2019. "The Environmental Impacts and Optimal Environmental Policies of Macroeconomic Uncertainty Shocks: A Dynamic Model Approach," Sustainability, MDPI, Open Access Journal, vol. 11(18), pages 1-26, September.

    More about this item

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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