Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/220194 
Year of Publication: 
2015
Series/Report no.: 
Discussion Paper No. 105
Publisher: 
Institute for Applied Economic Research (ipea), Brasília
Abstract: 
This paper is concerned with the study of Bayesian inference procedures to commonly used time series models. In particular, the dynamic or state-space models, the time-varying vector autoregressive model and the structural vector autoregressive model are considered in detail. Inference procedures are based on a hybrid integration scheme where state parameters are analytically integrated and hyperparameters are integrated by Markov chain Monte Carlo methods. Credibility regions for forecasts and impulse responses are then derived. The procedures are illustrated in real data sets.
Subjects: 
Bayesian
Dynamic
Hyperparameters
Impulse response
Markov chain Monte Carlo
Metropolis-Hastings algorithm
Vector autoregressive models
Document Type: 
Working Paper

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