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Faktor-augmentierte Vektor-Autoregression (FAVAR)×Vektorautoregressionsmodell (VAR)×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr20052005
UrheberBernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexesLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TypMultivariate time-series modelMultivariate time-series model
Wegweisende QuelleBernanke, 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 ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Aliasnamenfactor-augmented VAR, FAVAR model, Faktör Artırımlı VAR (FAVAR)vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Verwandt44
ZusammenfassungFAVAR 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.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
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ScholarGateMethoden vergleichen: FAVAR · VAR Model. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare