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Identifying stationary series in panels: A Monte Carlo evaluation of sequential panel selection methods

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  • Costantini, Mauro
  • Lupi, Claudio

Abstract

Sequential panel selection methods (spsms — procedures that sequentially use conventional panel unit root tests to identify I(0) time series in panels) are increasingly used in the empirical literature. We check the reliability of spsms by using Monte Carlo simulations based on generating directly the individual asymptotic p values to be combined into the panel unit root tests, in this way isolating the classification abilities of the procedures from the small sample properties of the underlying univariate unit root tests. The simulations consider both independent and cross-dependent individual test statistics. Results suggest that spsms may offer advantages over time series tests only under special conditions.

Suggested Citation

  • Costantini, Mauro & Lupi, Claudio, 2016. "Identifying stationary series in panels: A Monte Carlo evaluation of sequential panel selection methods," Economics Letters, Elsevier, vol. 138(C), pages 9-14.
    • Handle: RePEc:eee:ecolet:v:138:y:2016:i:c:p:9-14
    DOI: 10.1016/j.econlet.2015.11.011
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    References listed on IDEAS

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    1. Matei Demetrescu & Uwe Hassler & Adina‐Ioana Tarcolea, 2006. "Combining Significance of Correlated Statistics with Application to Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(5), pages 647-663, October.
    2. Moon, H.R. & Perron, B., 2012. "Beyond panel unit root tests: Using multiple testing to determine the nonstationarity properties of individual series in a panel," Journal of Econometrics, Elsevier, vol. 169(1), pages 29-33.
    3. Christoph Hanck, 2013. "An Intersection Test for Panel Unit Roots," Econometric Reviews, Taylor & Francis Journals, vol. 32(2), pages 183-203, February.
    4. Chortareas, Georgios & Kapetanios, George, 2009. "Getting PPP right: Identifying mean-reverting real exchange rates in panels," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 390-404, February.
    5. Ng, Serena, 2008. "A Simple Test for Nonstationarity in Mixed Panels," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 113-127, January.
    6. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    7. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    8. Hanck, Christoph, 2008. "The Error-in-Rejection Probability of meta-analytic panel tests," Economics Letters, Elsevier, vol. 101(1), pages 27-30, October.
    9. Christoph Hanck, 2009. "For which countries did PPP hold? A multiple testing approach," Empirical Economics, Springer, vol. 37(1), pages 93-103, September.
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    Cited by:

    1. Casarin, Roberto & Costola, Michele, 2019. "Structural changes in large economic datasets: A nonparametric homogeneity test," Economics Letters, Elsevier, vol. 176(C), pages 55-59.

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    More about this item

    Keywords

    Panel unit root; Monte Carlo; p value distribution; ROC curve;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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