방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 푸리에 그래인저 인과관계 검정× | 구조적 분절 그랜저 인과관계× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2016 | 1995-2010 |
| 창시자≠ | Enders and Jones | Granger (1969) causality framework extended by Toda & Yamamoto (1995) and Balcilar et al. (2010) |
| 유형≠ | Causality test | Hypothesis test / time-series model |
| 원전≠ | Enders, W., & Jones, P. (2016). Grain prices, oil prices, and multiple smooth breaks in a VAR. Studies in Nonlinear Dynamics and Econometrics, 20(4), 399–419. DOI ↗ | Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗ |
| 별칭 | Fourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality | break-robust Granger causality, Granger causality under regime change, time-varying Granger causality, structural change Granger test |
| 관련≠ | 6 | 3 |
| 요약≠ | The Fourier Granger causality test extends the classic Granger causality framework by embedding low-frequency Fourier terms in the VAR equation, allowing the causal relationship to shift gradually over time without requiring the researcher to pre-specify the number or location of structural breaks. | 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. |
| ScholarGate데이터셋 ↗ |
|
|