摘要：Over the past decade or so,
researchers at academic institutions
and central banks have been active
in specifying and estimating
dynamic stochastic general equilibrium (DSGE)
models that can be used to analyze monetary
policy.1 Although the first-generation models
were relatively small and stylized, more recent
models typically embed a much more elaborate
dynamic structure aimed at capturing key aspects
of the aggregate data.2 Indeed, several central
banks now use DSGE models in the forecasting
process and in formulating and communicating
policy strategies.3 In following that approach,
however, it is crucial to investigate the sensitivity
of the optimal policy prescriptions of a given
model¡ªthat is, comparing the policy implications
of alternative specifications of the behavioral
mechanisms or exogenous shocks¡ªand to
identify policy strategies that provide robust performance
under model uncertainty.
