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| Грънджър причинно-следствена връзка със структурни прекъсвания× | Векторна авторегресия (VAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1995-2010 | 1980 |
| Създател≠ | Granger (1969) causality framework extended by Toda & Yamamoto (1995) and Balcilar et al. (2010) | Christopher A. Sims |
| Тип≠ | Hypothesis test / time-series model | Multivariate time-series model |
| Основополагащ източник≠ | Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Други названия | break-robust Granger causality, Granger causality under regime change, time-varying Granger causality, structural change Granger test | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Свързани≠ | 3 | 5 |
| Резюме≠ | Structural break Granger causality extends the classic Granger causality framework to accommodate regime shifts and parameter instability in time series. By detecting break points and testing causality within sub-samples or via rolling/recursive windows, it reveals whether a predictive relationship between variables switches on, switches off, or changes direction over time. | 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. |
| ScholarGateНабор от данни ↗ |
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