This paper considers the problem of forecasting in large macroeconomic panels using Bayesian model averaging. Practical methods for implementing Bayesian model averaging with factor models are described. These methods involve algorithms that simulate from the space defined by all possible...

This paper examines the predictive content of coincident variables for monitoring U.S. recessions in the presence of instabilities. We propose several specifications of a probit model for classifying phases of the business cycle. We find strong evidence in favor of the ones that allow for the...

This chapter surveys the recent literature on output forecasting, and examines the real-time forecasting ability of several models for U.S. output growth. In particular, it evaluates the accuracy of short-term forecasts of linear and nonlinear structural and reduced-form models, and judgmental...