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| Kiểm định Đồng Tích Engle-Granger Mạnh mẽ× | Kiểm định Đồng tích hợp Engle-Granger có Đứt gãy Cấu trúc× | |
|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1987 (base); robust variants 2000s–2020s | 1996 |
| Người khởi xướng≠ | Engle & Granger (1987); robust extensions by subsequent authors including Hao & Shaffer and others | Gregory & Hansen (1996), extending Engle & Granger (1987) |
| Loại≠ | Cointegration test | Cointegration test with structural break |
| Công trình gốc≠ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ | Gregory, A. W., & Hansen, B. E. (1996). Residual-based tests for cointegration in models with regime shifts. Journal of Econometrics, 70(1), 99-126. link ↗ |
| Tên gọi khác | robust EG cointegration, outlier-robust cointegration test, robust two-step cointegration, robust EG test | Gregory-Hansen cointegration test, cointegration with structural break, EG cointegration with regime shift, residual-based cointegration with break |
| Liên quan≠ | 5 | 2 |
| Tóm tắt≠ | The Robust Engle-Granger cointegration test adapts the classic two-step Engle-Granger procedure to withstand outliers, heavy-tailed error distributions, and additive noise that can severely distort standard residual-based cointegration inference. By substituting robust regression and robust unit-root testing for classical OLS and ADF steps, it yields reliable conclusions about long-run equilibrium relationships even when the data contain anomalous observations. | The structural break Engle-Granger cointegration test, most commonly implemented via the Gregory-Hansen (1996) procedure, extends the classical Engle-Granger two-step test to allow for a single unknown structural break in the long-run cointegrating relationship. It tests whether two or more integrated series share a common stochastic trend even when that relationship may have shifted at some point in the sample. |
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