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| Strukturelles Bruch-AR-Modell× | Autoregressives Modell (AR)× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1989-2003 | 1970s (popularised 1976) |
| Urheber≠ | Perron (1989); Bai & Perron (1998, 2003) | George E. P. Box and Gwilym M. Jenkins |
| Typ≠ | Time-series model with structural change | Time series model |
| Wegweisende Quelle≠ | Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1-22. DOI ↗ | Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043 |
| Aliasnamen | AR model with structural change, breakpoint AR model, piecewise autoregressive model, AR model with regime shifts | AR model, AR(p) model, autoregression, AR process |
| Verwandt | 6 | 6 |
| Zusammenfassung≠ | The structural break AR model extends the standard autoregressive framework by allowing the intercept and autoregressive coefficients to shift at one or more unknown break dates. Each regime between consecutive break points is governed by its own AR parameters, capturing abrupt changes in the dynamics of a time series caused by crises, policy shifts, or other shocks. | 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. |
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