Decomposing Risk in Dynamic Stochastic General Equilibrium
Hong Lan () and
No SFB649DP2013-022, SFB 649 Discussion Papers from Humboldt University, Collaborative Research Center 649
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.
Keywords: Recursive preferences; stochastic volatility; asset pricing; DSGE; moment calculation (search for similar items in EconPapers)
JEL-codes: C63 E32 G12 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5) Track citations by RSS feed
Downloads: (external link)
Working Paper: Decomposing Risk in Dynamic Stochastic General Equilibrium (2014)
Software Item: Dynare add-on for "Decomposing Risk in Dynamic Stochastic General Equilibrium" (2013)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:hum:wpaper:sfb649dp2013-022
Access Statistics for this paper
More papers in SFB 649 Discussion Papers from Humboldt University, Collaborative Research Center 649 Contact information at EDIRC.
Bibliographic data for series maintained by RDC-Team ().