In the existing literature, conditional forecasts in the vector autoregressive (VAR) framework have not been commonly presented with probability distributions or error bands. This paper develops Bayesian methods for computing such distributions or bands. It broadens the class of conditional...

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...

Causal analysis in multiple equation models often revolves around the evaluation of the effects of an exogenous shift in a structural equation. When taking into account the uncertainty implied by the shape of the likelihood, we argue that how normalization is implemented matters for inferential...

Strategic interjurisdictional behavior and the interaction over time of the mean and dispersion of average tax rates across states are analyzed in a vector autoregression model. Variance decompositions reveal that fiscal competition explains roughly one-third of the time variation of state and...

In the applications of identified VAR models, finite-sample properties are not obvious to obtain when identifying restrictions are imposed on some lagged relationships. As a result, researchers have either left lagged relationships unrestricted even though some restrictions clearly make economic...

The half-life of deviations from purchasing power parity (PPP) plays a central role in the ongoing debate about the ability of macroeconomic models to account for the time series behavior of the real exchange rate. The main contribution of this paper is a general framework in which alternative...