We show how to correctly extend known methods for generating error bands in reduced form VAR's to overidentified models. We argue that the conventional pointwise bands common in the literature should be supplemented with measures of shape uncertainty, and we show how to generate such measures....

A multivariate model, identifying monetary policy and allowing for simultaneity and regime switching in coefficients and variances, is confronted with U.S. data since 1959. The best fit is with a model that allows time variation in structural disturbance variances only. Among models that also...

If multivariate dynamic models are to be used to guide decision-making, it is important that it be possible to provide probability assessments of their results. Bayesian VAR models in the existing literature have not commonly (in fact, not at all as far as we know) been presented with error...

We examine the theory and behavior in practice of Bayesian and bootstrap methods for generating error bands on impulse responses in dynamic linear models. The Bayesian intervals have a firmer theoretical foundation in small samples, are easier to compute, and are about as good in small samples...

This paper extends the methods developed by Hamilton (1989) and Chib (1996) to identified multiple-equation models. It details how to obtain Bayesian estimation and inference for a class of models with different degrees of time variation and discusses both analytical and computational difficulties.