In this article, Christopher A. Sims argues the answer to his title is yes. Sims explains that any decisionmaking model must incorporate some identifying assumptions to enable it to forecast the effects of alternative decisions. He argues that although all identifying assumptions in econometric...

We describe an algorithm for calculating second order approximations to the solutions to nonlinear stochastic rational expectation models. The paper also explains methods for using such an approximate solution to generate forecasts, simulated time paths for the model, and evaluations of expected...

The inference for hidden Markov chain models in which the structure is a multiple-equation macroeconomic model raises a number of difficulties that are not as likely to appear in smaller models. One is likely to want to allow for many states in the Markov chain without allowing the number of...

In his paper "To Criticize the Critics" (1991), Peter Phillips discusses Bayesian methodology for time series models. The main point that Uhlig and I set out to make, however, was that careful consideration of the implications of the likelihood principle suggests that much of the recent work...

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...

Most macroeconomic models treat the central bank and the trea-sury as a unified entity. The balance sheet of the central bank is therefore implicitly treated as an accounting fiction. While this is often realistic, the central bank balance sheet has implications for central bank independence....

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...