Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test bayésien de racine unitaire de Phillips-Perron× | Test de racine unitaire de Phillips-Perron× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1988 / early 1990s | 1988 |
| Auteur d'origine≠ | Phillips & Perron (classical test, 1988); Bayesian framework: Sims & Uhlig (1991) | Peter C. B. Phillips and Pierre Perron |
| 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. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Alias | Bayesian PP test, Bayesian Phillips-Perron test, Bayesian nonparametric unit root test, Bayes PP unit root | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root 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 Phillips-Perron (PP) test is a nonparametric unit root test for time series that corrects for serial correlation and heteroscedasticity in the error term without adding lagged differences. Introduced by Phillips and Perron (1988), it applies a kernel-based long-run variance estimator to adjust the Dickey-Fuller statistic, making it robust to a wide class of weakly dependent error processes. |
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