299 citations · 844 across the 14 of their papers we have counts for
3 papers · 1 filter
Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?
Martin Feldkircher, Luis Gruber, Florian Huber +1
We assess the relationship between model size and complexity in the time-varying parameter VAR framework via thorough predictive exercises for the Euro Area, the United Kingdom and…
Ancillarity-Sufficiency Interweaving Strategy (ASIS) for Boosting MCMC Estimation of Stochastic Volatility Models
Gregor Kastner, Sylvia Frühwirth-Schnatter
Bayesian inference for stochastic volatility models using MCMC methods highly depends on actual parameter values in terms of sampling efficiency. While draws from the posterior uti…
Sparse Bayesian vector autoregressions in huge dimensions
Gregor Kastner, Florian Huber
We develop a Bayesian vector autoregressive (VAR) model with multivariate stochastic volatility that is capable of handling vast dimensional information sets. Three features are in…