Speaker: Daniel F. Waggoner.
Title: Forecasting with Structural Bayesian Economic Models.
Affiliation: Federal Reserve Bank of Atlanta.
Date: Friday, 21 February 2003.
Place and Time: Room 499 - Dirac Science Library, 3:00 pm.
Refreshments: Dirac Library 4th floor lounge, 4:00 pm.

Abstract. In order to conduct monetary policy a central bank must have forecasts of the path of the economy. Complicating these forecasting models is the need to be able to perform counterfactual "what if" experiments. Because of this, the models used by a central bank need to structural, as opposed to reduced form in nature. We will consider how structural, Bayesian vector autoregression models can be used to explore the effects of different short run monetary policies. We will also point out some of the difficulties in formulating and implementing this class of models.