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Measurement Errors and Outliers in Seasonal Unit Root Testing

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  • Niels Haldrup
  • Antonio Montanés
  • Andreu Sanso

    () (Department of Economics, University of Aarhus, Denmark)

Abstract

Frequently, seasonal and non-seasonal data (especially macro time series) are observed with noise. For instance, the time series can have irregular abrupt changes and interruptions following as a result of additive or temporary change outliers caused by external circumstances which are irrelevant for the series of interest. Equally, the time series can have measurement errors. In this paper we analyse the above types of data irregularities on the behaviour of seasonal unit root tests. It occurs that in most cases outliers and measurement errors can seriously affect inference towards the rejection of seasonal unit roots. It is shown how the distortion of the tests will depend upon the frequency, magnitude, and persistence of the outliers as well as on the signal to noise ratio associated with measurement errors. Some solutions to the implied inference problems are suggested.

Suggested Citation

  • Niels Haldrup & Antonio Montanés & Andreu Sanso, "undated". "Measurement Errors and Outliers in Seasonal Unit Root Testing," Economics Working Papers 2000-8, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:aarhec:2000-8
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    Cited by:

    1. 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.
    2. Gabriel Pons, 2006. "Testing Monthly Seasonal Unit Roots With Monthly and Quarterly Information," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(2), pages 191-209, March.
    3. Kim, Chang Sik & Lee, Sungro, 2011. "Spurious regressions driven by excessive volatility," Economics Letters, Elsevier, vol. 113(3), pages 292-297.
    4. 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.
    5. 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.
    6. Pami Dua & Lokendra Kumawat, 2005. "Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series," Working papers 136, Centre for Development Economics, Delhi School of Economics.
    7. Pavel Cizek & Wolfgang Härdle, 2006. "Robust Econometrics," SFB 649 Discussion Papers SFB649DP2006-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    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.

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    More about this item

    Keywords

    Seasonal unit roots; HEGY tests; additive outliers; measurement errors; Brownian motion;
    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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