The predictive likelihood is of particular relevance in a Bayesian setting when the purpose is to rank models in a … observable variables in linear Gaussian state-space models with Bayesian methods, and proposes to utilize a missing observations …

We extend the literature on economic forecasting by constructing a mixed-frequency time-varying parameter vector … indicators sampled at different frequencies. We conduct a real-time forecast exercise to predict US key macroeconomic variables …' performance during the Great Recession and find that the combination of stochastic volatility, time-varying parameters, and mixed …

standard Bayesian VARs with Minnesota priors, VARs with democratic priors and standard time-varying parameter VARs for the euro …We develop a vector autoregressive model with time variation in the mean and the variance. The unobserved time … the researcher to use a large cross-sectional dimension in a feasible amount of computational time. The slowly changing …

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive … by evaluating a mixed-frequency time-varying parameter VAR with stochastic volatility (MF-TVP-SV-VAR). Overall, the MFTVP …