Comparer des méthodes

	Causalité de Granger bayésienne	Test de Causalité de Granger sur Données de Panel
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1969 (frequentist); 1984 (Bayesian treatment)	1988–2012
Auteur d'origine	Clive W. J. Granger (frequentist basis, 1969); Bayesian extension by Geweke (1984) and subsequent literature	Holtz-Eakin, Newey & Rosen (1988); Dumitrescu & Hurlin (2012)
Type	Bayesian causal inference test	Causality test
Source fondatrice	Geweke, J. (1984). Inference and causality in economic time series models. Handbook of Econometrics, 2, 1101-1144. Elsevier.	Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460.
Alias	Bayesian Granger test, Bayesian predictive causality, BGC, Bayesian causality in mean	panel causality test, Dumitrescu-Hurlin test, heterogeneous panel causality, panel Granger test
Apparentées	6	5
Résumé	Bayesian Granger causality tests whether past values of one time series carry predictive information about another, framing the hypothesis through Bayesian inference rather than frequentist p-values. It combines a vector autoregressive (VAR) structure with prior distributions over coefficients and evaluates causal claims via posterior probabilities or Bayes factors, providing a probabilistic and nuanced alternative to the classical Granger test.	The Panel Granger Causality test examines whether past values of one variable help predict another variable across multiple cross-sectional units observed over time. It extends the classical Granger causality framework to panel data, accounting for cross-sectional heterogeneity and enabling more powerful inference by pooling information across units.