Comparer des méthodes

	Modèle structurel de séries temporelles (Modèle structurel de base)	Modèle à changement de régime markovien (MS-AR / MS-VAR)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1990	1989
Auteur d'origine	Andrew C. Harvey	Hamilton (1989); Kim & Nelson (1999)
Type	State-space (unobserved components) time series model	Regime-switching time series model
Source fondatrice	Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 978-0521405737	Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384.
Alias	BSM, basic structural model, unobserved components model, Yapısal Zaman Serisi Modeli (BSM)	regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR
Apparentées	4	5
Résumé	The Structural Time Series Model, in its Basic Structural Model (BSM) form, is Andrew Harvey's state-space approach that decomposes a series into separate stochastic trend, seasonal, cyclical, and irregular components. Developed in Harvey's 1990 treatment, it is prized for interpretability and component decomposition where ARIMA only delivers a black-box fit.	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.