Time-varying parameter vector autoregressions (TVP-VARs) have become a popular tool to study the dynamics of macroeconomic time series. In this article, we discuss the specification and estimation of this class of models with a focus on implementability. We provide a step-by-step guide for...

In high-dimensional vector autoregressive (VAR) models, it is natural to have large number of predictors relative to the number of observations, and a lack of efficiency in estimation and forecasting. In this context, model selection is a difficult issue and standard procedures may often be...

This paper advances the application of Bayesian graphical structural vector autoregressive (BGSVAR) models to address the problem of impulse response estimation in VAR-based systems. The BGSVAR is designed as a robust empirical framework for impulse response estimation using information from the...

In impulse response analysis estimation uncertainty is typically displayed by constructing bands around estimated impulse response functions. These bands may be based on frequentist or Bayesian methods. If they are based on the joint distribution in the Bayesian framework or the joint asymptotic...