This paper develops and applies tools to assess multivariate
aspects of Bayesian Dynamic Stochastic General Equilibrium (DSGE)
model forecasts and their ability to predict comovements among key
macroeconomic variables. We construct posterior predictive checks
to evaluate conditional and unconditional density forecasts, in
addition to checks for root-mean-squared errors and event
probabilities associated with these forecasts. The checks are
implemented on a three-equation DSGE model as well as the Smets and
Wouters (2007) model using real-time data. We find that the
additional features incorporated into the Smets-Wouters model do
not lead to a uniform improvement in the quality of density
forecasts and prediction of comovements of output, inflation, and
interest rates.
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