This paper uses a nonlinear vector autoregression and a non-recursive identification strategy to show that an equal-sized uncertainty shock generates a larger contraction in real activity when growth is low (as in recessions) than when growth is high (as in expansions). An estimated New...

We employ real-time data available to the US monetary policy makers to estimate a Taylor rule augmented with a measure of financial uncertainty over the period 1969-2008. We find evidence in favor of a systematic response to financial uncertainty over and above that to expected inflation, output...

This survey features three parts. The first one covers the recent literature on domestic (i.e., country-specific) uncertainty and offers ten main takeaways. The second part reviews contributions on the fast-growing strand of the literature focusing on the macroeconomic effects of uncertainty...

We estimate a nonlinear VAR model to study the real effects of monetary policy shocks in regimes characterized by high vs. low macroeconomic uncertainty. We find unexpected monetary policy moves to exert a substantially milder impact in presence of high uncertainty. We then exploit the set of...

We estimate a novel measure of global financial uncertainty (GFU) with a dynamic factor framework that jointly models global, regional, and country-specific factors. We quantify the impact of GFU shocks on global output with a VAR analysis that achieves set-identification via a combination of...

We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a large dataset of disaggregated industrial production series for the US economy. Our results...