ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

フーリエ・戸田・山本型グレンジャー因果性検定×Granger因果性検定×
分野計量経済学計量経済学
系統Regression modelRegression model
提唱年20191969
提唱者Yilanci, Ozgur (building on Toda and Yamamoto 1995; Becker, Enders, and Hurn 2004)Clive W. J. Granger
種類Granger causality testTime-series predictive causality test
原典Yilanci, V., & Ozgur, O. (2019). Testing the Fourier Toda-Yamamoto causality test with an application to energy demand. Energy Economics, 84, 104498. link ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗
別名FTY causality, Fourier TY causality, Toda-Yamamoto causality with Fourier approximation, FTY Granger causalityGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
関連35
概要The Fourier Toda-Yamamoto (FTY) causality test extends the classical Toda-Yamamoto procedure by embedding Fourier trigonometric terms in the augmented VAR to capture smooth, gradual structural breaks in the deterministic component. It retains the key advantage of the Toda-Yamamoto approach — Granger causality can be tested without pre-testing for integration or cointegration order — while dramatically improving size and power when breaks occur.The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 1 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Fourier Toda-Yamamoto Causality · Granger Causality. 2026-06-19に以下より取得 https://scholargate.app/ja/compare