Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Strukturālās lūzuma AR modelis× | Paplašinātais Dikija-Fullera (ADF) vienības saknes tests× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1989-2003 | 1979–1984 |
| Autors≠ | Perron (1989); Bai & Perron (1998, 2003) | Said & Dickey (1984); building on Dickey & Fuller (1979) |
| Tips≠ | Time-series model with structural change | Hypothesis test (unit root) |
| Pirmavots≠ | Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1-22. DOI ↗ | Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607. DOI ↗ |
| Citi nosaukumi | AR model with structural change, breakpoint AR model, piecewise autoregressive model, AR model with regime shifts | ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | 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. | The Augmented Dickey-Fuller test is the standard procedure for determining whether a univariate time series contains a unit root — that is, whether the series is non-stationary. It extends the original Dickey-Fuller test by including lagged difference terms that absorb serial correlation in the residuals, making the test valid for a wide range of time-series processes encountered in economics and finance. |
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