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...

The uncertainty of U.S. core inflation, measured by the stochastic volatility of forecast errors, has soared to a level not seen in nearly five decades since the COVID-19 pandemic hit the global economy. Prices, consumption, and production increase after a positive shock to core inflation...

This paper investigates if the impact of uncertainty shocks on the U.K. economy has changed over time. To this end, we propose an extended time-varying VAR model that simultaneously allows the estimation of a measure of uncertainty and its time-varying impact on key macroeconomic and financial...

This paper uses a FAVAR model with stochastic volatility to estimate the impact of uncertainty shocks on real income growth in US states. The results suggest that there is a large degree of heterogeneity in the magnitude and the persistence of the response to uncertainty shocks across states....

We propose an extended time-varying parameter Vector Autoregression that allows for an evolving relationship between the variances of the shocks. Using this model, we show that the relationship between the conditional variance of GDP growth and the long-term interest rate has become weaker over...

In this paper we investigate the effects of uncertainty shocks on economic activity using a Dynamic Stochastic General Equilibrium (DSGE) model with heterogenous agents and a stylized banking sector. We show that frictions in credit supply amplify the effects of uncertainty shocks on economic...

In this paper, I study the drop of real GDP volatility which has been observed in the United States during the postwar period. This paper thoroughly estimates how much sectoral shifts contributed to this phenomenon called the Great Moderation. In a short section, Stock and Watson (2003) find...

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...

We use a TVP-VAR model to investigate possible changes in the time series properties of key Norwegian macroeconomic variables since the 1980s. The sample period is characterised by deregulation, globalization, sizable petroleum revenues, a switch from exchange rate to inflation targeting and...

We develop a dynamic factor model with time-varying parameters and stochastic volatility, estimate it with several variables for a large number of countries and decompose the variance of each variable in terms of contributions from uncertainty common to all countries (global uncertainty),...