Fernández-Villaverde, Jesús
[Verfasser:in]
;
Guerrón-Quintana, Pablo A.
[Sonstige Person, Familie und Körperschaft]National Bureau of Economic Research
Erschienen:
Cambridge, Mass: National Bureau of Economic Research, 2020
Erschienen in:NBER working paper series ; no. w27715
Umfang:
1 Online-Ressource; illustrations (black and white)
Sprache:
Englisch
DOI:
10.3386/w27715
Identifikator:
Reproduktionsnotiz:
Hardcopy version available to institutional subscribers
Entstehung:
Anmerkungen:
System requirements: Adobe [Acrobat] Reader required for PDF files
Mode of access: World Wide Web
Beschreibung:
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