Comparer des méthodes

	Test bayésien de racine unitaire de Phillips-Perron	Test de racine unitaire Augmented Dickey-Fuller (ADF)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1988 / early 1990s	1979–1984
Auteur d'origine	Phillips & Perron (classical test, 1988); Bayesian framework: Sims & Uhlig (1991)	Said & Dickey (1984); building on Dickey & Fuller (1979)
Type	Unit root test (Bayesian)	Hypothesis test (unit root)
Source fondatrice	Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.	Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607.
Alias	Bayesian PP test, Bayesian Phillips-Perron test, Bayesian nonparametric unit root test, Bayes PP unit root	ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test
Apparentées	5	5
Résumé	The Bayesian Phillips-Perron unit root test combines the nonparametric long-run variance correction of the classical Phillips-Perron test with a Bayesian inferential framework. Instead of a p-value, it yields a posterior probability or Bayes factor quantifying evidence for or against a unit root, allowing researchers to incorporate prior economic knowledge and obtain probability statements directly about the persistence of a time series.	The Augmented Dickey-Fuller test is the standard procedure for determining whether a univariate time series contains a unit root — that is, whether the series is non-stationary. It extends the original Dickey-Fuller test by including lagged difference terms that absorb serial correlation in the residuals, making the test valid for a wide range of time-series processes encountered in economics and finance.