Bayesian Inference in Cointegrated VAR Models: With Applications to the Demand for Euro Area M3

Abstract

The paper considers a Bayesian approach to the cointegrated VAR model with a uniform prior on the cointegration space. Building on earlier work by Villani (2005b), where the posterior probability of the cointegration rank can be calculated conditional on the lag order, the current paper also makes it possible to compute the joint posterior probability of these two parameters as well as the marginal posterior probabilities under the assumption of a known upper bound for the lag order. When the marginal likelihood identity is used for calculating these probabilities, a point estimator of the cointegration space and the weights is required. Analytical expressions are therefore derived of the mode of the joint posterior of these parameter matrices. The procedure is applied to a money demand system for the euro area and the results are compared to those obtained from a maximum likelihood analysis.

Keywords: Bayesian inference, cointegration, lag order, money demand, vector autoregression

JEL Classification: C11, C15, C32, E41