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Fourier Granger Causaliteitstest×Structurele Breuk Granger Causality×
VakgebiedEconometrieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan20161995-2010
GrondleggerEnders and JonesGranger (1969) causality framework extended by Toda & Yamamoto (1995) and Balcilar et al. (2010)
TypeCausality testHypothesis test / time-series model
Oorspronkelijke bronEnders, 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 ↗
AliassenFourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causalitybreak-robust Granger causality, Granger causality under regime change, time-varying Granger causality, structural change Granger test
Verwant63
SamenvattingThe 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.
ScholarGateGegevensset
  1. v1
  2. 2 Bronnen
  3. PUBLISHED
  1. v1
  2. 2 Bronnen
  3. PUBLISHED

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ScholarGateMethoden vergelijken: Fourier Granger Causality · Structural Break Granger Causality. Geraadpleegd op 2026-06-18 via https://scholargate.app/nl/compare