Seraching for Additive Outliers in Nonstationary Time Series
AbstractRecently, Vogelsang (1999) proposed a method to detect outliers which explicitly imposes the null hypothesis of a unit root. It works in an iterative fashion to select multiple outliers in a given series. We show, via simulations, that under the null hypothesis of no outliers, it has the right size in finite samples to detect a single outlier but when applied in an iterative fashion to select multiple outliers, it exhibits severe size distortions towards finding an excessive number of outliers. We show that this iterative method is incorrect and derice the appropriate limiting distribution of the test at each step of the search.
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Bibliographic InfoPaper provided by University of Ottawa, Department of Economics in its series Working Papers with number 0005e.
Length: 30 pages
Date of creation: 2000
Date of revision:
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ECONOMETRICS ; ECONOMIC MODELS;
Other versions of this item:
- Pierre Perron & Gabriel RodrÌguez, 2003. "Searching For Additive Outliers In Nonstationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 193-220, 03.
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
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