We propose a methodology to gauge the uncertainty in output gap nowcasts across a large number of commonly deployed vector autoregressions in US inflation and various measures of the output gap. Our approach constructs ensemble nowcast densities using a linear opinion pool. This yields...

We examine the effectiveness of recursive-weight and equal-weight combination strategies for forecasting using many time-varying models of the relationship between inflation and the output gap. The forecast densities for inflation reflect the uncertainty across models using many statistical...

A popular macroeconomic forecasting strategy takes combinations across many models to hedge against model instabilities of unknown timing; see (among others) Stock andWatson (2004) and Clark and McCracken (2009). In this paper, we examine the effectiveness of recursive-weight and equal-weight...

We propose a methodology for producing density forecasts for the output gap in real time using a large number of vector autoregessions in inflation and output gap measures. Density combination utilizes a linear mixture of experts framework to produce potentially non-Gaussian ensemble densities...