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Panel Data Unit Roots Tests: The Role of Serial Correlation and the Time Dimension

Author

Listed:
  • Stefan De Wachter

    (University of Oxford)

  • Richard D.F. Harris

    (University of Exeter)

  • Elias Tzavalis

    (Queen Mary, University of London)

Abstract

We investigate the influence of residual serial correlation and of the time dimension on statistical inference for a unit root in dynamic longitudinal data, known as panel data in econometrics. To this end, we introduce two test statistics based on method of moments estimators. The first is based on the generalised method of moments estimators, while the second is based on the instrumental variables estimator. Analytical results for the IV based test in a simplified setting show that (i) large time dimension panel unit root tests will suffer from serious size distortions in finite samples, even for samples that would normally be considered large in practice, and (ii) negative serial correlation in the error terms of the panel reduces the power of the unit root tests, possibly up to a point where the test becomes biased. However, near the unit root the test is shown to have power against a wide range of alternatives. These findings are confirmed in a more general set-up through a series of Monte Carlo experiments.

Suggested Citation

  • Stefan De Wachter & Richard D.F. Harris & Elias Tzavalis, 2005. "Panel Data Unit Roots Tests: The Role of Serial Correlation and the Time Dimension," Working Papers 550, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:550
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    File URL: https://www.qmul.ac.uk/sef/media/econ/research/workingpapers/2005/items/wp550.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Dynamic longitudinal (panel) data; Generalized method of moments; Instrumental variables; Unit roots; Moving average errors;
    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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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