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| 贝叶斯增广迪基-富勒单位根检验× | Phillips-Perron单位根检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1991–1992 | 1988 |
| 提出者≠ | Sims & Uhlig (1991); Koop, Osiewalski & Steel (1992) | Peter C. B. Phillips and Pierre Perron |
| 类型≠ | Bayesian hypothesis test | Hypothesis test (unit root) |
| 开创性文献≠ | Sims, C. A., & Uhlig, H. (1991). Understanding unit rooters: A helicopter tour. Econometrica, 59(6), 1591–1599. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| 别名 | Bayesian ADF test, Bayesian unit root test, Bayesian Dickey-Fuller, BADF | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| 相关≠ | 6 | 5 |
| 摘要≠ | The Bayesian Augmented Dickey-Fuller (BADF) unit root test re-frames the classical ADF test within a Bayesian framework. Rather than computing a frequentist p-value, it quantifies evidence for or against a unit root by comparing posterior probabilities or Bayes factors under the null (unit root) and alternative (stationarity) hypotheses, incorporating prior beliefs about the autoregressive parameter. | 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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