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date: 30 November 2020

Abstract and Keywords

Dynamic Stochastic General Equilibrium (DSGE) models have become popular in macroeconomics, but the combination of nonlinear microeconomic behavior of the agents and model-consistent expectations raise intricate computational issues; this chapter reviews solution methods and estimation of DSGE models. Perfect foresight deterministic models can easily be solved with a great degree of accuracy. In practice, medium-sized stochastic models can only be solved by local approximation or the perturbation approach. The Bayesian approach to estimation is privileged. It provides a convenient way to communicate both the prior information available to the econo-metrician and new information revealed by the data. This chapter focuses on methods frequently used in applied work rather than aiming at being exhaustive.

Keywords: DSGE models, rational expectation, perturbation method, generalized Schur decomposition, Bayesian estimation, Kalman filter

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