A Composite Likelihood Approach for Dynamic Structural Models

We describe how to use the composite likelihood to ameliorate estimation, computational, and inferential problems in dynamic stochastic general equilibrium models. We present a number of situations where the methodology has the potential to resolve well-known problems. In each case we consider, we provide an example to illustrate how the approach works and its properties in practice

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Year of publication:	2019
Authors:	Canova, Fabio
Other Persons:	Matthes, Christian (contributor)
Publisher:	[2019]: [S.l.] : SSRN
Subject:	Modellierung \| Scientific modelling \| Schätztheorie \| Estimation theory \| Bayes-Statistik \| Bayesian inference \| DSGE-Modell \| DSGE model

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Extent:	1 Online-Ressource (41 p)
Series:	FRB Richmond Working Paper ; No. 18-12
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments 2018-07-23 erstellt
Classification:	C10 - Econometric and Statistical Methods: General. General ; E27 - Forecasting and Simulation ; E32 - Business Fluctuations; Cycles
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012898448