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Performance of unit root tests in unbalanced panels: experimental evidence

  • Verena Werkmann

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    This paper is about the validity of established panel unit root tests applied to panels in which the individual time series are of different lengths, a case often encountered in practice. Most of the tests considered work well under various types of cross-correlation which is true for both, their application in balanced as well as in unbalanced panels. A Monte Carlo study reveals that in unbalanced panels, procedures involving the computation of individual $$p$$ -values for each cross-section unit (or the combination thereof) are mostly superior to those relying on a pooled Dickey–Fuller regression framework. As the former are able to consider each unit separately, they do not require cutting back the “longer” time series so as to obtain the smallest “balanced” quadrangle which in turn means that no potentially valuable information is lost. Copyright Springer-Verlag Berlin Heidelberg 2013

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    File URL: http://hdl.handle.net/10.1007/s10182-012-0203-8
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    Article provided by Springer in its journal AStA Advances in Statistical Analysis.

    Volume (Year): 97 (2013)
    Issue (Month): 3 (July)
    Pages: 271-285

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    Handle: RePEc:spr:alstar:v:97:y:2013:i:3:p:271-285
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    1. MOON, H.R. & PERRON, Benoit, 2010. "Beyond Panel Unit Root Tests : Using Multiple Testing to Determine the Non-Stationarity Properties of Individual Series in a Panel," Cahiers de recherche 10-2010, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    2. Pasaran, M.H. & Im, K.S. & Shin, Y., 1995. "Testing for Unit Roots in Heterogeneous Panels," Cambridge Working Papers in Economics 9526, Faculty of Economics, University of Cambridge.
    3. Hyungsik Roger MOON & Benoit PERRON, 2002. "Testing For A Unit Root In Panels With Dynamic Factors," Cahiers de recherche 18-2002, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    4. Samarjit Das & Joerg Breitung, 2004. "Panel Unit Root Tests under Cross- sectional Dependence," Econometric Society 2004 North American Summer Meetings 55, Econometric Society.
    5. 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.
    6. Maddala, G S & Wu, Shaowen, 1999. " A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 631-52, Special I.
    7. James G. MacKinnon, 1995. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Working Papers 918, Queen's University, Department of Economics.
    8. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    9. Christoph Hanck, 2013. "An Intersection Test for Panel Unit Roots," Econometric Reviews, Taylor & Francis Journals, vol. 32(2), pages 183-203, February.
    10. Jushan Bai & Serena Ng, 2001. "A PANIC Attack on Unit Roots and Cointegration," Boston College Working Papers in Economics 519, Boston College Department of Economics.
    11. Peter C. B. Phillips & Donggyu Sul, 2003. "Dynamic panel estimation and homogeneity testing under cross section dependence *," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 217-259, 06.
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