This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating DSGE model posterior distributions. We show how the tempering schedule can be chosen adaptively, explore the benefits of an SMC variant we call generalized tempering for "online" estimation, and...

This comment points out mismeasurement of three of the variables in the DSGE model in Del Negro, Giannoni, and Schorfheide (2015). These errors began with the model in Smets and Wouters (2007), and they also exist in other models that use the Smets-Wouters model as a benchmark. The...

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output...