Linear process bootstrap unit root test
Copyright policy )Linear process bootstrap unit root test
One of the most widely applied unit root test, Phillips-Perron test, enjoys in general highpowers, but suffers from size distortions when moving average noise exists. As a remedy, thispaper proposes a nonparametric bootstrap unit root test that specifically targets moving aver-age noise. Via a bootstrap functional central limit theorem, the consistency of this bootstrapapproach is established under general assumptions which allows a large family of non-linear timeseries. In simulation, this bootstrap test alleviates the size distortions of the Phillips-Perrontest while preserving its high powers.
- University of California, San Diego United States
- University of California, San Francisco United States
- University of California, San Diego United States
- University of Toronto Canada
integrated time series, FOS: Computer and information sciences, functional central limit theorem, size distortion, Methodology (stat.ME), Time series, auto-correlation, regression, etc. in statistics (GARCH), resampling, Nonparametric statistical resampling methods, Nonparametric hypothesis testing, Statistics - Methodology
integrated time series, FOS: Computer and information sciences, functional central limit theorem, size distortion, Methodology (stat.ME), Time series, auto-correlation, regression, etc. in statistics (GARCH), resampling, Nonparametric statistical resampling methods, Nonparametric hypothesis testing, Statistics - Methodology
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