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| Модел на авторегресия със структурни промени× | Авторегресивен модел (AR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1989-2003 | 1970s (popularised 1976) |
| Създател≠ | Perron (1989); Bai & Perron (1998, 2003) | George E. P. Box and Gwilym M. Jenkins |
| Тип≠ | Time-series model with structural change | Time series model |
| Основополагащ източник≠ | 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 |
| Други названия | AR model with structural change, breakpoint AR model, piecewise autoregressive model, AR model with regime shifts | AR model, AR(p) model, autoregression, AR process |
| Свързани | 6 | 6 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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