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Testing for Additive Outliers in Seasonally Integrated Time Series

Author

Listed:
  • Niels Haldrup
  • Antonio Montañés
  • Andreu Sansó

    (Department of Economics, University of Aarhus, Denmark)

Abstract
The detection of additive outliers in integrated variables has attracted some attention recently, see e.g. Shin et al. (1996), Vogelsang (1999) and Perron and Rodriguez (2003). This paper serves several purposes. We prove the inconsistency of the test proposed by Vogelsang, we extend the tests proposed by Shin et al. and Perron and Rodriguez to the seasonal case, and we consider alternative ways of computing their tests. We also study the e?ects of periodically varying variances on the previous tests and demonstrate that these can be seriously size distorted. Subsequently, some new tests that allow for periodic heteroskedasticity are proposed.

Suggested Citation

  • Niels Haldrup & Antonio Montañés & Andreu Sansó, 2004. "Testing for Additive Outliers in Seasonally Integrated Time Series," Economics Working Papers 2004-14, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:aarhec:2004-14
    as

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    File URL: https://repec.econ.au.dk/repec/afn/wp/04/wp04_14.pdf
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    References listed on IDEAS

    as
    1. Peter C.B. Phillips & Pierre Perron, 1986. "Testing for a Unit Root in Time Series Regression," Cowles Foundation Discussion Papers 795R, Cowles Foundation for Research in Economics, Yale University, revised Sep 1987.
    2. Pierre Perron & Gabriel Rodríguez, 2003. "Searching For Additive Outliers In Nonstationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 193-220, March.
    3. Franses, Philip Hans & Paap, Richard, 2004. "Periodic Time Series Models," OUP Catalogue, Oxford University Press, number 9780199242030.
    4. Burridge, Peter & Taylor, A. M. Robert, 2001. "On regression-based tests for seasonal unit roots in the presence of periodic heteroscedasticity," Journal of Econometrics, Elsevier, vol. 104(1), pages 91-117, August.
    5. Franses, Philip Hans, 1996. "Periodicity and Stochastic Trends in Economic Time Series," OUP Catalogue, Oxford University Press, number 9780198774549.
    6. Timothy J. Vogelsang, 1999. "Two Simple Procedures for Testing for a Unit Root When There are Additive Outliers," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(2), pages 237-252, March.
    7. Haldrup, Niels Prof. & Montanes, Antonio & Sansó, Andreu, 2000. "Measurement Errors and Outliers in Seasonal Unit Root Testing," University of California at San Diego, Economics Working Paper Series qt0gw7q9hk, Department of Economics, UC San Diego.
    8. Shin, Dong Wan & Sarkar, Sahadeb & Lee, Jong Hyup, 1996. "Unit root tests for time series with outliers," Statistics & Probability Letters, Elsevier, vol. 30(3), pages 189-197, October.
    9. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    10. Haldrup, Niels & Montanes, Antonio & Sanso, Andreu, 2005. "Measurement errors and outliers in seasonal unit root testing," Journal of Econometrics, Elsevier, vol. 127(1), pages 103-128, July.
    11. Franses, Philip Hans & Haldrup, Niels, 1994. "The Effects of Additive Outliers on Tests for Unit Roots and Cointegration," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 471-478, October.
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    Cited by:

    1. Haldrup, Niels & Sansó, Andreu, 2008. "A note on the Vogelsang test for additive outliers," Statistics & Probability Letters, Elsevier, vol. 78(3), pages 296-300, February.

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    More about this item

    Keywords

    Additive outliers; outlier detection; integrated processes; periodic heteroscedasticity; seasonality.;
    All these keywords.

    JEL classification:

    • 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; Diffusion Processes

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