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Autoregresja wektorowa bayesowska (BVAR)×Wektorowa autokorelacja z uwzględnieniem czynników (FAVAR)×Model Markowa z przełączaniem reżimów (MS-AR / MS-VAR)×Regresja metodą najmniejszych kwadratów (OLS)×Progowy i gładko-przejściowy VAR (TVAR / STVAR)×
DziedzinaEkonometriaEkonometriaEkonometriaEkonometriaEkonometria
RodzinaRegression modelRegression modelRegression modelRegression modelRegression model
Rok powstania19862005198920191998
TwórcaLitterman (1986); Bańbura, Giannone & Reichlin (2010)Bernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexesHamilton (1989); Kim & Nelson (1999)Wooldridge (textbook treatment); classical least squaresTsay (multivariate threshold modelling)
TypBayesian multivariate time-series modelMultivariate time-series modelRegime-switching time series modelLinear regressionNonlinear multivariate time-series model
Źródło pierwotneLitterman, R. B. (1986). Forecasting with Bayesian Vector Autoregressions—Five Years of Experience. Journal of Business & Economic Statistics, 4(1), 25-38. DOI ↗Bernanke, 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 ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202. DOI ↗
Inne nazwyBVAR, Bayesian vector autoregression, Minnesota prior VAR, Bayesian VAR (BVAR)factor-augmented VAR, FAVAR model, Faktör Artırımlı VAR (FAVAR)regime-switching model, Markov-switching autoregression, MS-AR, MS-VARordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuTVAR, STVAR, regime-switching VAR, threshold VAR
Pokrewne54555
PodsumowanieBayesian VAR adds Minnesota or other prior distributions to a vector autoregressive model to control over-parameterisation. Introduced by Litterman (1986) and extended to high dimensions by Bańbura, Giannone and Reichlin (2010), it outperforms classical VAR on short series and high-dimensional macroeconomic forecasts.FAVAR 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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).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.
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ScholarGatePorównaj metody: Bayesian VAR · FAVAR · Markov-Switching Model · OLS Regression · Threshold and Smooth-Transition VAR. Pobrano 2026-06-18 z https://scholargate.app/pl/compare