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Unit root tests in the presence of innovational outliers

Author

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  • Lanne, Markku
  • Lütkepohl, Helmut
  • Saikkonen, Pentti

Abstract

Unit root tests are considered for time series with innovational outliers. The function representing the outliers can have a very general nonlinear form and additional deterministic mean and trend terms are allowed for. Prior to the tests the deterministic parts and other nuisance parameters of the data generation process are estimated in a first step. Then the series are adjusted for these terms and unit raot tests of the Dickey-Fuller type are applied to the adjusted series. The properties of previously suggested tests of this sort are analyzed and modifications are proposed which take into account estimation errors in the nuisance parameters. An important result is that estimation under the null hypothesis is preferable to estimation under local alternatives. This contrasts with results obtained by other authors for time series without outliers. A comparison with additive outlier models is also performed.

Suggested Citation

  • Lanne, Markku & Lütkepohl, Helmut & Saikkonen, Pentti, 2001. "Unit root tests in the presence of innovational outliers," SFB 373 Discussion Papers 2001,82, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    • Handle: RePEc:zbw:sfb373:200182
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    Cited by:

    1. Jungmittag Andre & Grupp Hariolf, 2006. "Wechselwirkungen zwischen Innovations- und Wachstumsprozessen in Deutschland 1951-1999 im Vergleich zu 1850-1913 / Dynamic Relationships Between Innovation Activities and Per Capita Income in Germany ," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(2), pages 180-207, April.

    More about this item

    Keywords

    Univariate time series; unit root; structural shift; autoregression;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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