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| Faktor-augmenteret vektorautoregressionsmodel (FAVAR)× | Markov regime-switching model (MS-AR / MS-VAR)× | Almindelig mindste kvadraters metode (OLS) regression× | Tærskel- og jævn-overgangs VAR (TVAR / STVAR)× | Vektor Autoregression (VAR) Model× | |
|---|---|---|---|---|---|
| Fagområde | Økonometri | Økonometri | Økonometri | Økonometri | Økonometri |
| Familie | Regression model | Regression model | Regression model | Regression model | Regression model |
| Oprindelsesår≠ | 2005 | 1989 | 2019 | 1998 | 2005 |
| Ophavsperson≠ | Bernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexes | Hamilton (1989); Kim & Nelson (1999) | Wooldridge (textbook treatment); classical least squares | Tsay (multivariate threshold modelling) | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Type≠ | Multivariate time-series model | Regime-switching time series model | Linear regression | Nonlinear multivariate time-series model | Multivariate time-series model |
| Oprindelig kilde≠ | 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: 978-1337558860 | 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 ↗ |
| Aliasser≠ | factor-augmented VAR, FAVAR model, Faktör Artırımlı VAR (FAVAR) | regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | TVAR, STVAR, regime-switching VAR, threshold VAR | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Relaterede≠ | 4 | 5 | 5 | 5 | 4 |
| Resumé≠ | 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. | 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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