A model for U.S. macroeconomic time series that has been used for forecasting for several years is described in some detail. The model is a multivariate Bayesian autoregression, with allowance for conditional heteroskedasticity, stochastic time-variation in parameters, and non-normality of...

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...

Inference for multiple-equation Markov-chain models raises a number of difficulties that are unlikely to appear in smaller models. Our framework allows for many regimes in the transition matrix, without letting the number of free parameters grow as the square as the number of regimes, but also...

This article reviews Monetary Policy Rules, edited by John Taylor. The book evaluates the Taylor rule, a policy rule that specifies changes in the central bank's interest rate according to what is happening to two variables, real output and inflation. Questions are raised about (a) how well the...

Probabilistic reasoning is essential to discourse in economics. This is true in any discipline in which, as in economics, data collection is constrained and beliefs about the phenomena being studied are crucial to decisions that cannot be delayed. Some economists have recently turned away from...