Estimating DSGE Models: Recent Advances and Future Challenges / Jesús Fernández-Villaverde, Pablo A. Guerrón-Quintana.

Format:

Book

Author/Creator:

Fernández-Villaverde, Jesús.

Contributor:

National Bureau of Economic Research.

Guerrón-Quintana, Pablo A.

Series:

Working Paper Series (National Bureau of Economic Research) no. w27715.

NBER working paper series no. w27715

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2020.

Summary:

We review the current state of the estimation of DSGE models. After introducing a general framework for dealing with DSGE models, the state-space representation, we discuss how to evaluate moments or the likelihood function implied by such a structure. We discuss, in varying degrees of detail, recent advances in the field, such as the tempered particle filter, approximated Bayesian computation, the Hamiltonian Monte Carlo, variational inference, and machine learning, methods that show much promise, but that have not been fully explored yet by the DSGE community. We conclude by outlining three future challenges for this line of research.

Notes:

Print version record

August 2020.