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| Modèle autorégressif (AR)× | Autoregressive Vectoriel (VAR)× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1970s (popularised 1976) | 1980 |
| Auteur d'origine≠ | George E. P. Box and Gwilym M. Jenkins | Christopher A. Sims |
| Type≠ | Time series model | Multivariate time-series model |
| Source fondatrice≠ | Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043 | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Alias | AR model, AR(p) model, autoregression, AR process | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | An autoregressive model of order p — AR(p) — expresses the current value of a time series as a linear function of its own p most recent past values plus a white-noise error. It is the building block of the Box-Jenkins family of time-series models and is widely used for forecasting stationary economic and financial series. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
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