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Risk news shocks and the business cycle

Author

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  • Pinter, Gabor

    () (Bank of England)

  • Theodoridis, Konstantinos

    () (Bank of England)

  • Yates, Tony

    () (University of Bristol and Centre for Macroeconomics)

Abstract

We identify a ‘risk news' shock in a vector autoregression (VAR), modifying Barsky and Sims’s procedure, while incorporating sign restrictions to simultaneously identify monetary policy, technology and demand shocks. The VAR-identifed risk news shock is estimated to account for around 2%-12% of business cycle fluctuations depending on which risk proxy we use; regardless, contemporaneous risk and risk news shocks together account for about 20%. This is substantially lower than the 60% reported in Christiano, Motto, and Rostagno’s full-information exercise. We fit a DSGE model with financial frictions to these impulse responses and find that, in order to match the fall in consumption recorded by the VAR, we have to allow for 75% of consumers to be living hand-to-mouth.

Suggested Citation

  • Pinter, Gabor & Theodoridis, Konstantinos & Yates, Tony, 2013. "Risk news shocks and the business cycle," Bank of England working papers 483, Bank of England.
  • Handle: RePEc:boe:boeewp:0483
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Francesco Furlanetto & Francesco Ravazzolo & Samad Sarferaz, 2014. "Identification of financial factors in economic fluctuations," Working Paper 2014/09, Norges Bank.
    2. Kamber, Güneş & Theodoridis, Konstantinos & Thoenissen, Christoph, 2017. "News-driven business cycles in small open economies," Journal of International Economics, Elsevier, vol. 105(C), pages 77-89.
    3. repec:wly:econjl:v:128:y:2018:i:611:p:1730-1757 is not listed on IDEAS
    4. Andrej Sokol & Ambrogio Cesa-Bianchi, 2017. "The International Credit Channel of U.S. Monetary Policy and Financial Shocks," 2017 Meeting Papers 724, Society for Economic Dynamics.
    5. Gabor Pinter, 2016. "The Macroeconomic Shock with the Highest Price of Risk," Discussion Papers 1623, Centre for Macroeconomics (CFM), revised Apr 2017.
    6. Piergiorgio Alessandri & Haroon Mumtaz, 2014. "Financial Regimes and Uncertainty Shocks," Working Papers 729, Queen Mary University of London, School of Economics and Finance.
    7. Gabriela Castro & José R. Maria & Paulo Júlio & Ricardo Mourinho Félix, 2015. "Financial Fragmentation Shocks," Working Papers w201508, Banco de Portugal, Economics and Research Department.
    8. Michael Plante & Alexander W. Richter & Nathaniel A. Throckmorton, 2018. "The Zero Lower Bound and Endogenous Uncertainty," Economic Journal, Royal Economic Society, vol. 128(611), pages 1730-1757, June.

    More about this item

    Keywords

    News shock; business cycles; risk; financial frictions; vector autoregression;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - 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
    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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