Bayesian Analysis of Econometric Time Series Models Using Hybrid Integration Rules

Ajax Moreira and Dani Gamerman

No 105, Discussion Papers from Instituto de Pesquisa Econômica Aplicada - IPEA

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. Este artigo utiliza procedimentos de inferência bayesiana para estimar modelos econométricos freqüentemente usados. Em particular, os modelos dinâmicos ou de espaço de estado são considerados detalhadamente. Procedimentos de inferência baseiam-se em esquemas de integração híbridos, em que as variáveis de estado são integradas analiticamente, e os hiperparâmetros são integrados utilizando o método de cadeias de Markov de Monte Carlo. As regiões de credibilidade da previsão e das funções de resposta a impulso são também avaliadas. Os procedimentos são ilustrados com dados reais da economia brasileira.

Pages: 38 pages
Date: 2015-01
New Economics Papers: this item is included in nep-ecm and nep-ets
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