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

Thomas A. Lubik · Christian Matthes Y

84 citations0/0 files storedEconomic quarterly - Federal Reserve Bank of Richmond

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Monetary Policy and Economic Impact Forecasting Techniques and Applications Statistical and numerical algorithms

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.

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1980Macroeconomics and Reality 2005Time Varying Structural Vector Autoregressions and Monetary Policy 1998Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models 1998Monetary Policy Shocks: What Have We Learned and to What End?2006Were There Regime Switches in U.S. Monetary Policy?2002Has the Business Cycle Changed and Why?2004Testing for Indeterminacy: An Application to U.S. Monetary Policy 2010Bayesian Multivariate Time Series Methods for Empirical Macroeconomics

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