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非線形Toda-Yamamoto因果性検定×共和分検定(ヨハンセン/エングル・グレンジャー法)×
分野計量経済学計量経済学
系統Regression modelRegression model
提唱年1995 (base); nonlinear extensions 2000s–2010s1988
提唱者Toda & Yamamoto (1995) for the linear base; nonlinear extension developed by subsequent researchers applying rank transformations or neural-network-augmented VAREngle & Granger (1987); Johansen (1988)
種類Causality testTime-series cointegration test
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 ↗Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. DOI ↗
別名nonlinear TY causality, rank-based Toda-Yamamoto test, modified Wald nonlinear causality, NTY causality testJohansen cointegration test, Engle-Granger cointegration test, long-run equilibrium test, Eşbütünleşme Testi (Johansen/Engle-Granger)
関連55
概要The Nonlinear Toda-Yamamoto causality test extends the classic Toda-Yamamoto (1995) modified Wald procedure to detect causal linkages that are hidden in the means of series but manifest through nonlinear dynamics such as asymmetries, threshold effects, or volatility transmission. It fits an augmented VAR on rank-transformed or otherwise nonlinearly mapped series and applies a chi-squared Wald test on the extra-lag coefficients.The cointegration test examines whether non-stationary time series that each contain a unit root share a stable long-run equilibrium relationship. The single-equation residual approach was introduced by Engle and Granger (1987) and the system-based rank approach by Johansen (1988).
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ScholarGate手法を比較: Nonlinear Toda-Yamamoto Causality · Cointegration Test. 2026-06-18に以下より取得 https://scholargate.app/ja/compare