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The effect of additive outliers on a fractional unit root test

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  • Hafner, Christian
  • Premiger, Arie

Abstract

It is well known that additive outliers that occur with a small probability have a bias effect on the asymptotic distribution of classical unit root statistics. This paper shows that such outliers do not affect the asymptotic distribution in the case where the error term is fractionally integrated of order d, where $$0
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Suggested Citation

  • Hafner, Christian & Premiger, Arie, 2016. "The effect of additive outliers on a fractional unit root test," LIDAM Reprints ISBA 2016027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  • Handle: RePEc:aiz:louvar:2016027
    Note: In : A St A - Advances in Statistical Analysis, vol. 100, no. 4, p. 401-420 (2016)
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    References listed on IDEAS

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    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. Eduardo Rossi & Paolo Santucci de Magistris, 2014. "Estimation of Long Memory in Integrated Variance," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 785-814, October.
    3. Neil Shephard & Kevin Sheppard, 2010. "Realising the future: forecasting with high-frequency-based volatility (HEAVY) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 197-231.
    4. David F. Hendry & Carlos Santos, 2005. "Regression Models with Data‐based Indicator Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(5), pages 571-595, October.
    5. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    6. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    7. 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.
    8. Haldrup, Niels & Nielsen, Morten Orregaard, 2007. "Estimation of fractional integration in the presence of data noise," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3100-3114, March.
    9. 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.
    10. Jussi Tolvi, 2003. "Long memory and outliers in stock market returns," Applied Financial Economics, Taylor & Francis Journals, vol. 13(7), pages 495-502.
    11. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
    12. Hansen, Peter R. & Lunde, Asger, 2014. "Estimating The Persistence And The Autocorrelation Function Of A Time Series That Is Measured With Error," Econometric Theory, Cambridge University Press, vol. 30(1), pages 60-93, February.
    13. Perron, Pierre & Vogelsang, Timothy J, 1992. "Testing for a Unit Root in a Time Series with a Changing Mean: Corrections and Extensions," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 467-470, October.
    14. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    15. Katsumi Shimotsu, 2006. "Simple (but Effective) Tests Of Long Memory Versus Structural Breaks," Working Paper 1101, Economics Department, Queen's University.
    16. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    17. 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.
    18. Chung, Ching-Fan & Baillie, Richard T, 1993. "Small Sample Bias in Conditional Sum-of-Squares Estimators of Fractionally Integrated ARMA Models," Empirical Economics, Springer, vol. 18(4), pages 791-806.
    19. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    20. Sowell, Fallaw, 1990. "The Fractional Unit Root Distribution," Econometrica, Econometric Society, vol. 58(2), pages 495-505, March.
    21. Diego Lubian, 1999. "Long‐Memory Errors in Time Series Regressions with a Unit Root," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(5), pages 565-577, September.
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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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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