Time-Varying Parameter Vector Autoregressions: Specification, Estimation, and an Application

Abstract

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 researchers interested in utilizing this methodology in their own research. Specifically, we discuss how to use Bayesian Gibbs-sampling techniques to easily conduct inference.