Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Markovin tilaa vaihtava malli (MS-AR / MS-VAR)× | Kynnys- ja sileän siirtymän VAR (TVAR / STVAR)× | Vektorien autoregressiomalli (VAR-malli)× | |
|---|---|---|---|
| Tieteenala | Ekonometria | Ekonometria | Ekonometria |
| Menetelmäperhe | Regression model | Regression model | Regression model |
| Syntyvuosi≠ | 1989 | 1998 | 2005 |
| Kehittäjä≠ | Hamilton (1989); Kim & Nelson (1999) | Tsay (multivariate threshold modelling) | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Tyyppi≠ | Regime-switching time series model | Nonlinear multivariate time-series model | Multivariate time-series model |
| Alkuperäislähde≠ | 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 ↗ | Tsay, R. S. (1998). Testing and Modeling Multivariate Threshold Models. Journal of the American Statistical Association, 93(443), 1188-1202. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| Rinnakkaisnimet≠ | regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR | TVAR, STVAR, regime-switching VAR, threshold VAR | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Liittyvät≠ | 5 | 5 | 4 |
| Tiivistelmä≠ | 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. | 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. | 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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