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Decomposing risk in dynamic stochastic general equilibrium

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  • Lan, Hong
  • Meyer-Gohde, Alexander

Abstract

We analyze the theoretical moments of a nonlinear approximation to a model of business cycles and asset pricing with stochastic volatility and recursive preferences. We find that heteroskedastic volatility operationalizes a time-varying risk adjustment channel that induces variability in conditional asset pricing measures and assigns a substantial portion of the variance of macroeconomic variables to variations in precautionary behavior, both while leaving its ability to match key macroeconomic and asset pricing facts untouched. Our method decomposes moments into contributions from realized shocks and differing orders of approximation and from shifts in the distribution of future shocks, enabling us to identify the common channel through which stochastic volatility in isolation operates and through which conditional asset pricing measures vary.

Suggested Citation

  • Lan, Hong & Meyer-Gohde, Alexander, 2013. "Decomposing risk in dynamic stochastic general equilibrium," SFB 649 Discussion Papers 2013-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2013-022
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    Cited by:

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    2. Mutschler, Willi, 2018. "Higher-order statistics for DSGE models," Econometrics and Statistics, Elsevier, vol. 6(C), pages 44-56.
    3. Meyer-Gohde, Alexander, 2019. "Generalized entropy and model uncertainty," Journal of Economic Theory, Elsevier, vol. 183(C), pages 312-343.
    4. Meyer-Gohde, Alexander, 2015. "Risk-Sensitive Linear Approximations," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113057, Verein für Socialpolitik / German Economic Association.
    5. Benjamin Born & Johannes Pfeifer, 2014. "Risk Matters: A Comment," CESifo Working Paper Series 4793, CESifo.
    6. Bonciani, Dario & Roye, Björn van, 2016. "Uncertainty shocks, banking frictions and economic activity," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 200-219.
    7. Benjamin Born & Johannes Pfeifer, 2014. "Risk Matters: The Real Effects of Volatility Shocks: Comment," American Economic Review, American Economic Association, vol. 104(12), pages 4231-4239, December.
    8. Poeschel, Friedrich, 2012. "Assortative matching through signals," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62061, Verein für Socialpolitik / German Economic Association.
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    More about this item

    Keywords

    recursive preferences; stochastic volatility; asset pricing; DSGE; moment calculation;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • 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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