Detection of Additive Outliers in Seasonal Time Series
AbstractThe detection and location of additive outliers in integrated variables has attracted much attention recently because such outliers tend to affect unit root inference among other things. Most of these procedures have been developed for non-seasonal processes. However, the presence of seasonality in the form of seasonally varying means and variances affect the properties of outlier detection procedures, and hence appropriate adjustments of existing methods are needed for seasonal data. In this paper we suggest modifications of tests proposed by Shin, Sarkar and Lee (1996) and Perron and Rodriguez (2003) to deal with data sampled at a seasonal frequency and we discuss their size and power properties. We also show that the presence of periodic heteroscedasticity will inflate the size of the tests and hence will tend to identify an excessive number of outliers. A modified Perron-Rodriguez test which allows periodically varying variances is suggested, and it is shown to have excellent properties in terms of both power and size.
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Bibliographic InfoArticle provided by De Gruyter in its journal Journal of Time Series Econometrics.
Volume (Year): 3 (2011)
Issue (Month): 2 (April)
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Web page: http://www.degruyter.com
Other versions of this item:
- Niels Haldrup & Antonio Montañés & Andreu Sansó, 2009. "Detection of additive outliers in seasonal time series," CREATES Research Papers 2009-40, School of Economics and Management, University of Aarhus.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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