This paper compares alternative models of time-varying macroeconomic volatility on the basis of the accuracy of point … vector autoregressive models that incorporate some form of time-varying volatility, precisely stochastic volatility (both … with constant and time-varying autoregressive coefficients), stochastic volatility following a stationary AR process …

This paper compares alternative models of time-varying macroeconomic volatility on the basis of the accuracy of point … vector autoregressive models that incorporate some form of time-varying volatility, precisely stochastic volatility (both … with constant and time-varying autoregressive coefficients), stochastic volatility following a stationary AR process …

VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine … transitory and persistent changes in volatility. The resulting density forecasts are much less sensitive to outliers in the data … the pandemic period, as well as for earlier subsamples of relatively high volatility. In historical forecasting, outlier …

stable, driven by stochastic volatility (SV), or follow a novel nonparametric specification. Estimation is carried out using …

. However, recent sharp changes in macroeconomic volatility such as the Great Moderation and the more recent sharp rise in … volatility associated with greater variation in energy prices and the deep global recession pose significant challenges to …, inflation, and the federal funds rate from VAR models with stochastic volatility. The model of interest extends the steady state …

forecast errors, we derive a multiple-horizon specification of stochastic volatility. Compared to constant-variance approaches …, our stochastic-volatility model improves the accuracy of uncertainty measures for survey forecasts …