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MCMC method for Markov mixture simultaneous-equation models: a note

This paper extends the methods developed by Hamilton (1989) and Chib (1996) to identified multiple-equation models. It details how to obtain Bayesian estimation and inference for a class of models with different degrees of time variation and discusses both analytical and computational difficulties.
Year of publication:
2004
Authors: Sims, Christopher A. ; Zha, Tao
Publisher: Atlanta, GA : Federal Reserve Bank of Atlanta
Subject: Volatilität | Bayes-Statistik | Markovscher Prozess | Theorie | Simultanes Gleichungssystem
Series:
Working Paper ; 2004-15
Type of publication: Book / Working Paper
Type of publication (narrower categories): Working Paper
Language: English
Other identifiers:
479119813 [GVK]
hdl:10419/100926 [Handle]
RePEc:fip:fedawp:2004-15 [RePEc]
Source:
Persistent link: https://ebvufind01.dmz1.zbw.eu/10010397597
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