A Gibbs Simulator for Restricted VAR Models
Daniel F. Waggoner and Tao Zha
Federal Reserve Bank of Atlanta
Working Paper 2000-3
Many economic applications call for simultaneous equations VAR modeling. We show that the existing importance sampler can be prohibitively inefficient for this type of models. We develop a Gibbs simulator that works for both simultaneous and recursive VAR models with a much broader range of linear restrictions than those in the existing literature. We show that the required computation is of an SUR type, and thus our method can be implemented cheaply even for large systems of multiple equations.
JEL classification: C15, C32, E50
Key words: simultaneous equations, recursive systems, independence, importance sampling, Gibbs sampler, posterior distributions
The authors have benefited from discussions with John Geweke and Chris Sims. The code for computation is available upon request. The views expressed here are the authors' and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors' responsibility.
Please address questions regarding content to Dan Waggoner, Economist, Research Department, Federal Reserve Bank of Atlanta, 104 Marietta Street, N.W., Atlanta, Georgia 30303-2713, 404/498-8278, firstname.lastname@example.org, or Tao Zha, Senior Economist and Policy Adviser, Research Department, Federal Reserve Bank of Atlanta, 104 Marietta Street, N.W., Atlanta, Georgia 30303-2713, 404/498-8353, email@example.com.