ScholarGate
Assistent
Regression modelEconometrics / time series

Fourier Toda-Yamamoto Granger Kausalitetstest

Fourier Toda-Yamamoto (FTY) kausalitetstesten udvider den klassiske Toda-Yamamoto-procedure ved at indlejre Fourier trigonometriske led i den augmenterede VAR for at fange glatte, gradvise strukturelle brud i den deterministiske komponent. Den bevarer den centrale fordel ved Toda-Yamamoto-tilgangen – Granger-kausalitet kan testes uden forudgående test for integration eller kointegrationsorden – samtidig med at den dramatisk forbedrer størrelse og styrke, når brud opstår.

Anvend med EconMindSnartVideoSnartDownload slides

Læs hele metoden

Kun for medlemmer

Log ind med en gratis konto for at læse dette afsnit.

Log ind

Method map

The neighbourhood of related methods — select a node to explore.

Kilder

  1. Yilanci, V., & Ozgur, O. (2019). Testing the Fourier Toda-Yamamoto causality test with an application to energy demand. Energy Economics, 84, 104498. link
  2. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI: 10.1016/0304-4076(94)01616-8

Sådan citerer du denne side

ScholarGate. (2026, June 3). Fourier Toda-Yamamoto Granger Causality Test. ScholarGate. https://scholargate.app/da/econometrics/fourier-toda-yamamoto-causality

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGateFourier Toda-Yamamoto Causality (Fourier Toda-Yamamoto Granger Causality Test). Hentet 2026-06-15 fra https://scholargate.app/da/econometrics/fourier-toda-yamamoto-causality · Datasæt: https://doi.org/10.5281/zenodo.20539026