ScholarGate
Assistente

Comparar métodos

Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Teste de Causalidade de Toda-Yamamoto para Dados em Painel×Granger Causality Test×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem1995 (panel extension from 2006)1969
Autor originalToda & Yamamoto (1995); extended to panel settings by Konya (2006) and othersClive W. J. Granger
TipoCausality test (non-causality hypothesis)Causality test (F-test on VAR)
Fonte seminalToda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗
Outros nomesPanel TY causality test, Toda-Yamamoto panel causality, panel modified Wald causality test, panel MWALD causalityGranger test, GC test, predictive causality test, Granger non-causality test
Relacionados55
ResumoThe Panel Toda-Yamamoto (PTY) causality test extends the Toda-Yamamoto modified Wald approach to panel data, allowing researchers to test Granger non-causality across multiple cross-sectional units without requiring pre-testing for cointegration or imposing a common causality direction on all units.The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis.
ScholarGateConjunto de dados
  1. v1
  2. 2 Fontes
  3. PUBLISHED
  1. v1
  2. 2 Fontes
  3. PUBLISHED

Ir para a pesquisa Baixar slides

ScholarGateComparar métodos: Panel Toda-Yamamoto Causality · Granger Causality Test. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare