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Working Paper
Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions
A rapidly growing body of research has examined tail risks in macroeconomic outcomes. Most of this work has focused on the risks of significant declines in GDP, and it has relied on quantile regression methods to estimate tail risks. Although much of this work discusses asymmetries in conditional predictive distributions, the analysis often focuses on evidence of downside risk varying more than upside risk. We note that this pattern in risk estimates over time could obtain with conditional distributions that are symmetric but subject to simultaneous shifts in conditional means (down) and ...
Working Paper
Evaluating Macroeconomic Outcomes Under Asymmetries: Expectations Matter
Asymmetries play an important role in many macroeconomic models. We show that assumptions on household and firm expectations play a key role in determining the effects of these asymmetries on macroeconomic outcomes. If households and firms have perfect foresight and hence do not account for the possibility of future shocks, then the implied longer-run averages and distributions for unemployment and inflation can differ significantly from their rational expectations counterparts. We first derive this result analytically under either an asymmetric monetary policy rule or a nonlinear Phillips ...
Working Paper
Evaluating Macroeconomic Outcomes Under Asymmetries: Expectations Matter
Asymmetries play an important role in many macroeconomic models. We show that assumptions on household and firm expectations play a key role in determining the effects of these asymmetries on macroeconomic outcomes. If households and firms have perfect foresight and hence do not account for the possibility of future shocks, then the implied longer-run averages and distributions for unemployment and inflation can differ significantly from their rational expectations counterparts. We first derive this result analytically under either an asymmetric monetary policy rule or a nonlinear Phillips ...
Working Paper
Capturing Macroeconomic Tail Risks with Bayesian Vector Autoregressions
A rapidly growing body of research has examined tail risks in macroeconomic outcomes. Most of this work has focused on the risks of significant declines in GDP, and has relied on quantile regression methods to estimate tail risks. In this paper we examine the ability of Bayesian VARs with stochastic volatility to capture tail risks in macroeconomic forecast distributions and outcomes. We consider both a conventional stochastic volatility specification and a specification featuring a common volatility factor that is a function of past financial conditions. Even though the conditional ...