IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v78y2008i3p296-300.html
   My bibliography  Save this article

A note on the Vogelsang test for additive outliers

Author

Listed:
  • Haldrup, Niels
  • Sansó, Andreu

Abstract

The role of additive outliers in integrated time series has attracted some attention recently and research shows that outlier detection should be an integral part of unit root testing procedures. Recently, Vogelsang [1999. Two simple procedures for testing for a unit root when there are additive outliers. J. Time Ser. Anal. 20, 237-52] suggested an iterative procedure for the detection of multiple additive outliers in integrated time series. However, the procedure appears to suffer from serious size distortions towards the finding of too many outliers as has been shown by Perron and Rodriguez [2003. Searching for additive outliers in nonstationary time series. J. Time Ser. Anal. 24, 193-220] In this note we prove the inconsistency of the test in each step of the iterative procedure and hence alternative routes need to be taken to detect outliers in nonstationary time series.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:3:p:296-300
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(07)00241-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Charles, Amélie & Darné, Olivier, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 167-180.
    2. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    3. Haldrup Niels & Montañes Antonio & Sansó Andreu, 2011. "Detection of Additive Outliers in Seasonal Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(2), pages 1-20, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haldrup Niels & Montañes Antonio & Sansó Andreu, 2011. "Detection of Additive Outliers in Seasonal Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(2), pages 1-20, April.
    2. 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.
    3. Christian M. Hafner & Arie Preminger, 2016. "The effect of additive outliers on a fractional unit root test," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 401-420, October.
    4. 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.
    5. Maican, Florin G. & Sweeney, Richard J., 2013. "Real exchange rate adjustment in European transition countries," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 907-926.
    6. Sam Astill & David I. Harvey & A. M. Robert Taylor, 2013. "A bootstrap test for additive outliers in non-stationary time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 454-465, July.
    7. Giulio Cifarelli & Giovanna Paladino, 2009. "The Buffer Stock Model Redux? An Analysis of the Dynamics of Foreign Reserve Accumulation," Open Economies Review, Springer, vol. 20(4), pages 525-543, September.
    8. Olivier Darné & Amélie Charles, 2011. "Large shocks in U.S. macroeconomic time series: 1860-1988," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(1), pages 79-100, January.
    9. Gabriel Rodriguez & Dionisio Ramirez, 2014. "A Note on the Size of the ADF Test with Additive Outliers and Fractional Errors. A Reappraisal about the (Non)Stationarity of the Latin-American Inflation Series," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 37(73), pages 113-132.
    10. YAMAMOTO, Yohei & 山本, 庸平, 2015. "Asymptotic Inference for Common Factor Models in the Presence of Jumps," Discussion Papers 2015-05, Graduate School of Economics, Hitotsubashi University.
    11. Charles, Amélie & Darné, Olivier, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 167-180.
    12. Gabriel Rodriguez, 2013. "A Comparative Note About Estimation of the Fractional Parameter under Additive Outliers," Documentos de Trabajo / Working Papers 2013-356, Departamento de Economía - Pontificia Universidad Católica del Perú.
    13. Gabriel Rodriguez & Dionisio Ramirez, 2013. "A comparison between Tau-d and the procedure TRAMO-SEATS is also included," Documentos de Trabajo / Working Papers 2013-355, Departamento de Economía - Pontificia Universidad Católica del Perú.
    14. Alanya-Beltran, Willy, 2022. "Unit roots in lower-bounded series with outliers," Economic Modelling, Elsevier, vol. 115(C).
    15. Darne, Olivier & Diebolt, Claude, 2004. "Unit roots and infrequent large shocks: new international evidence on output," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1449-1465, October.
    16. Artur Silva Lopes, 2006. "Deterministic seasonality in Dickey–Fuller tests: should we care?," Empirical Economics, Springer, vol. 31(1), pages 165-182, March.
    17. Chen, Jie, 2006. "Re-evaluating the association between housing wealth and aggregate consumption: New evidence from Sweden," Journal of Housing Economics, Elsevier, vol. 15(4), pages 321-348, December.
    18. Olivier Darné & Jean‐François Hoarau, 2007. "Further Evidence On Mean Reversion In The Australian Exchange Rate," Bulletin of Economic Research, Wiley Blackwell, vol. 59(4), pages 383-395, October.
    19. Thierno Balde & Gabriel Rodriguez, 2005. "Finite sample effects of additive outliers on the Granger-causality test with an application to money growth and inflation in Peru," Applied Economics Letters, Taylor & Francis Journals, vol. 12(13), pages 841-844.
    20. Aparicio, Felipe M. & García, Ana, 2003. "Range unit root tests," DES - Working Papers. Statistics and Econometrics. WS ws031126, Universidad Carlos III de Madrid. Departamento de Estadística.

    More about this item

    Keywords

    Additive outliers Outlier detection Integrated processes;

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:78:y:2008:i:3:p:296-300. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.