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The Origins and Effects of Macroeconomic Uncertainty

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  • Francesco Bianchi

    (Duke University)

  • Howard Kung

    (London Business School)

  • Mikhail Tirskikh

    (London Business School)

Abstract

We construct and estimate a dynamic stochastic general equilibrium model that features demand- and supply-side uncertainty. Using term structure and macroeconomic data, we find sizable effects of uncertainty on risk premia and business cycle fluctuations. Both demand-side and supply-side uncertainty imply large contractions in real activity and an increase in term premia, but supply-side uncertainty has larger effects on inflation and investment. We introduce a novel analytical decomposition to illustrate how multiple distinct risk propagation channels account for these differences. Supply and demand uncertainty are strongly correlated in the beginning of our sample, but decouple in the aftermath of the Great Recession.

Suggested Citation

  • Francesco Bianchi & Howard Kung & Mikhail Tirskikh, 2019. "The Origins and Effects of Macroeconomic Uncertainty," 2019 Meeting Papers 245, Society for Economic Dynamics.
  • Handle: RePEc:red:sed019:245
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    3. Benjamin Born & Johannes Pfeifer, 2021. "Uncertainty‐driven business cycles: Assessing the markup channel," Quantitative Economics, Econometric Society, vol. 12(2), pages 587-623, May.
    4. Bonciani, Dario & Oh, Joonseok Jason, 2019. "The long-run effects of uncertainty shocks," Bank of England working papers 802, Bank of England.
    5. Darracq Pariès, Matthieu & Papadopoulou, Niki X., 2020. "On the credit and exchange rate channels of central bank asset purchases in a monetary union," Economic Modelling, Elsevier, vol. 91(C), pages 502-533.
    6. Oliver de Groot & Alexander W. Richter & Nathaniel A. Throckmorton, 2022. "Valuation risk revalued," Quantitative Economics, Econometric Society, vol. 13(2), pages 723-759, May.
    7. Boyan Jovanovic & Sai Ma, 2022. "Uncertainty and Growth Disasters," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 44, pages 33-64, April.
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    9. Szczygielski, Jan Jakub & Charteris, Ailie & Bwanya, Princess Rutendo & Brzeszczyński, Janusz, 2022. "The impact and role of COVID-19 uncertainty: A global industry analysis," International Review of Financial Analysis, Elsevier, vol. 80(C).
    10. Ambrocio, Gene, 2020. "Inflationary household uncertainty shocks," Research Discussion Papers 5/2020, Bank of Finland.
    11. Li, Erica X.N. & Zha, Tao & Zhang, Ji & Zhou, Hao, 2022. "Does fiscal policy matter for stock-bond return correlation?," Journal of Monetary Economics, Elsevier, vol. 128(C), pages 20-34.
    12. Alex Hsu & Erica X. N. Li & Francisco Palomino, 2021. "Real and Nominal Equilibrium Yield Curves," Management Science, INFORMS, vol. 67(2), pages 1138-1158, February.
    13. Xu, Qinhua & Fu, Buben & Wang, Bin, 2022. "The effects of oil price uncertainty on China’s economy," Energy Economics, Elsevier, vol. 107(C).
    14. Gareth Lui-Evans & Shalini Mitra, 2019. "Informality and Bank Stability," Working Papers 201903, University of Liverpool, Department of Economics.
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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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