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Measurement Errors and Outliers in Seasonal Unit Root Testing

  • Niels Haldrup
  • Antonio Montanés
  • Andreu Sanso

    ()

    (Department of Economics, University of Aarhus, Denmark)

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.

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Paper provided by Department of Economics and Business Economics, Aarhus University in its series Economics Working Papers with number 2000-8.

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Handle: RePEc:aah:aarhec:2000-8
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  8. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-62, April.
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  16. J. Breitung & P. H. Franses, 1996. "On Phillips-Perron Type Tests for Seasonal Unit Roots," SFB 373 Discussion Papers 1996,27, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  17. 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.
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