The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution...

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the...

The interaction of macroeconomic variables may change as the nominal shortterm interest rates approaches zero. In this paper, we propose an empirical model capturing these changing dynamics with a time-varying parameter vector autoregressive process. State-dependent parameters are determined by...

We combine the factor augmented VAR framework with recently developed estimation and identification procedures for sparse dynamic factor models. Working with a sparse hierarchical prior distribution allows us to discriminate between zero and non-zero factor loadings. The non-zero loadings...

Two Bayesian sampling schemes are outlined to estimate a K-state Markov switching model with time-varying transition probabilities. Data augmentation for the multinomial logit model of the transition probabilities is alternatively based on a random utility and a difference in random utility...