Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/220194 
Erscheinungsjahr: 
2015
Schriftenreihe/Nr.: 
Discussion Paper No. 105
Verlag: 
Institute for Applied Economic Research (ipea), Brasília
Zusammenfassung: 
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.
Schlagwörter: 
Bayesian
Dynamic
Hyperparameters
Impulse response
Markov chain Monte Carlo
Metropolis-Hastings algorithm
Vector autoregressive models
Dokumentart: 
Working Paper

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