ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Векторная авторегрессия с добавлением факторов (FAVAR)×Пороговая и плавнопереходная векторная авторегрессия (TVAR / STVAR)×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления20051998
Автор методаBernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexesTsay (multivariate threshold modelling)
ТипMultivariate time-series modelNonlinear multivariate time-series model
Основополагающий источникBernanke, 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 ↗Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202. DOI ↗
Другие названияfactor-augmented VAR, FAVAR model, Faktör Artırımlı VAR (FAVAR)TVAR, STVAR, regime-switching VAR, threshold VAR
Связанные45
СводкаFAVAR 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.Threshold VAR and Smooth-Transition VAR are nonlinear multivariate time-series models in which the coefficients of a vector autoregression switch between regimes according to a threshold variable. Building on Tsay's 1998 treatment of multivariate threshold models, they capture different dynamic structures across phases such as the business cycle, financial crises, or policy differences.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: FAVAR · Threshold and Smooth-Transition VAR. Получено 2026-06-17 из https://scholargate.app/ru/compare