This paper improves a standard Structural Panel Bayesian Vector Autoregression model in order to jointly deal with issues of endogeneity, because of omitted factors and unobserved heterogeneity, and volatility, because of policy regime shifts and structural changes. Bayesian methods are used to...

This paper provides an overview of a time-varying Structural Panel Bayesian Vector Autoregression model that deals with model misspecification and unobserved heterogeneity problems in applied macroeconomic analyses when studying time-varying relationships and dynamic interdependencies among...

The paper develops empirical implementations of the standard time-varying Panel Bayesian VAR model to deal with confounding and latent effects. Bayesian computations and mixed hierarchical distributions are used to generate posteriors of conditional impulse responses and conditional forecasts....

This paper improves the existing literature on the shrinkage of high dimensional model and parameter spaces through Bayesian priors and Markov Chains algorithms. A hierarchical semiparametric Bayes approach is developed to overtake limits and misspecificity involved in compressed regression...