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。

戸田・山本の因果性検定×ベクトル誤差修正モデル(VECM)×
分野計量経済学計量経済学
系統Regression modelRegression model
提唱年19951987
提唱者Toda, H. Y. and Yamamoto, T.Robert F. Engle and Clive W. J. Granger
種類Causality testMultivariate time-series model
原典Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
別名Toda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALDVECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
関連55
概要The Toda-Yamamoto (TY) causality test is a modified Wald procedure for testing Granger causality in vector autoregressions (VARs) estimated in levels, even when variables are nonstationary or cointegrated. By intentionally over-fitting the VAR with extra lags equal to the maximum integration order, it restores the standard chi-squared asymptotic distribution of the Wald statistic without requiring prior unit-root or cointegration pretesting.The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Toda-Yamamoto causality test · Vector Error Correction Model. 2026-06-17に以下より取得 https://scholargate.app/ja/compare