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Vetores Autorregressivos Aumentados por Fatores (FAVAR)×Modelo de Markov com Troca de Regimes (MS-AR / MS-VAR)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem20051989
Autor originalBernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexesHamilton (1989); Kim & Nelson (1999)
TipoMultivariate time-series modelRegime-switching time series model
Fonte seminalBernanke, B. S., Boivin, J. & Eliasz, P. (2005). Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach. The Quarterly Journal of Economics, 120(1), 387-422. DOI ↗Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. DOI ↗
Outros nomesfactor-augmented VAR, FAVAR model, Faktör Artırımlı VAR (FAVAR)regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR
Relacionados45
ResumoFAVAR is a multivariate time-series model that first compresses information from a very large set of variables into a few common factors, then includes those factors alongside the observed variables in a vector autoregression. It was introduced by Bernanke, Boivin and Eliasz in 2005 to study monetary policy using hundreds of macroeconomic indicators at once.The Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions.
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ScholarGateComparar métodos: FAVAR · Markov-Switching Model. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare