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On Unit Root Tests and the Initial Observation

Author

Listed:
  • Steve Leybourne

    (Nottingham)

  • David Harvey

    (Nottingham)

Abstract

We consider the power of unit root tests for different deviations of the initial observation from the deterministic component of the series. Following recent work highlighting the relative power performance of extant tests, we propose a new procedure based on a data-dependent weighted average of the standard Dickey-Fuller and Elliott-Rothenberg- Stock tests, with the weight determined by an estimate of the initial observation’s deviation from the deterministics. Simulation of the new test’s power reveals very good performance across different magnitudes of the initial condition. The procedure’s value is further highlighted by application to US producer price inflation.

Suggested Citation

  • Steve Leybourne & David Harvey, 2003. "On Unit Root Tests and the Initial Observation," Econometrics 0311006, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0311006
    Note: Type of Document - ; pages: 15
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0311/0311006.pdf
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    References listed on IDEAS

    as
    1. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    2. Elliott, Graham, 1999. "Efficient Tests for a Unit Root When the Initial Observation Is Drawn from Its Unconditional Distribution," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(3), pages 767-783, August.
    3. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
    4. Ulrich K. M¸ller & Graham Elliott, 2003. "Tests for Unit Roots and the Initial Condition," Econometrica, Econometric Society, vol. 71(4), pages 1269-1286, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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