This paper considers the problem of forecasting in large macroeconomic panels using Bayesian model averaging. Practical … apply these methods to the problem of forecasting GDP and inflation using quarterly U.S. data on 162 time series. Our … analysis indicates that models containing factors do outperform autoregressive models in forecasting both GDP and inflation …

This paper compares the forecasting performance of different models which have been proposed for forecasting in the … macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast … majority of cases. We find no single forecasting model consistently works best in the presence of structural breaks. In many …

In this paper, we develop methods for estimation and forecasting in large time-varying parameter vector autoregressive … dimension can change over time. For instance, we can have a large TVP-VAR as the forecasting model at some points in time, but a … use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting …