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...

Data from a heterogeneous-agents economy with incomplete asset markets and indivisible labor supply are simulated under various fiscal policy regimes and an approximating representative-agent model is estimated. Preference and technology parameter estimates of the representative-agent model are...

This paper assesses biases in policy predictions due to the lack of invariance of "structural'' parameters in representative-agent models. We simulate data under various fiscal policy regimes from a heterogeneous-agents economy with incomplete asset markets and indivisible labor supply....

This paper assesses biases in policy predictions due to the lack of invariance of ``structural'' parameters in representative-agent models. We simulate data under various fiscal policy regimes from a heterogeneous-agents economy with incomplete asset markets and indivisible labor supply....

Data from a heterogeneous-agents economy with incomplete asset markets and indivisible labor supply are simulated under various scal policy regimes and an approximating representative-agent model is estimated. Preference and technology parameter estimates of the representative-agent model are...

We develop a new class of nonlinear time-series models to identify nonlinearities in the data and to evaluate nonlinear DSGE models. U.S. output growth and the federal funds rate display nonlinear conditional mean dynamics, while inflation and nominal wage growth feature conditional...

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 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 chapter provides an overview of solution and estimation techniques for dynamic stochastic general equilibrium (DSGE) models. We cover the foundations of numerical approximation techniques as well as statistical inference and survey the latest developments in the field

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...