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Teste de Causalidade de Granger×Teste de Limites ARDL (Teste de Limites de Pesaran)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem19692001
Autor originalClive W. J. GrangerPesaran, Shin & Smith
TipoTime-series predictive causality testCointegration test / Autoregressive distributed lag model
Fonte seminalGranger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289–326. DOI ↗
Outros nomesGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik TestiPesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)
Relacionados54
ResumoThe 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.The ARDL bounds test is an autoregressive distributed lag method that tests for a cointegrating (long-run level) relationship between time series, introduced by Pesaran, Shin and Smith in 2001. Unlike the Johansen procedure, it remains valid whether the variables are I(0), I(1) or a mix of the two, and it is more reliable than Johansen in small samples of roughly 30 to 80 observations.
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ScholarGateComparar métodos: Granger Causality · ARDL Bounds Test. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare