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We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples consisting of an artificial state-space...

In Bayesian analysis of dynamic stochastic general equilibrium (DSGE) models, prior distributions for some of the taste-and-technology parameters can be obtained from microeconometric or presample evidence, but it is difficult to elicit priors for the parameters that govern the law of motion of...

This paper discusses prior elicitation for the parameters of dynamic stochastic general equilibrium (DSGE) models and provides a method for constructing prior distributions for a subset of these parameters from beliefs about the moments of the endogenous variables. The empirical application...

Policy analysis with potentially misspecified dynamic stochastic general equilibrium (DSGE) models faces two challenges: estimation of parameters that are relevant for policy trade-offs and treatment of estimated deviations from the cross-equation restrictions. This paper develops and explores...

It has been argued that existing DSGE models cannot properly account for the evolution of key macroeconomic variables during and following the recent great recession, and that models in which inflation depends on economic slack cannot explain the recent muted behavior of inflation, given the...

We develop a nonlinear state-space model to capture the joint dynamics of consumption, dividend growth, and asset returns. Building on Bansal and Yaron (2004), the core of our model consists of an endowment economy that is, in part, driven by a common predictable component for consumption and...