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Comparison of panel cointegration tests

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  • Örsal, Deniz Dilan Karaman

Abstract

The main aim of this paper is to compare the size and size-adjusted power properties of four residual-based and one maximum-likelihood-based panel cointegration tests with the help of Monte Carlo simulations. In this study the panel-p, the group-p, the panel-t, the group-t statistics of Pedroni (1999) and the standardized LR-bar statistic of Larsson er al. (2001) are considered. The simulation results indicate that the panel-t and standardized LR-bar statistic have the best size and power properties among the five panel cointegration test statistics evaluated. Finally, the Fisher Hypothesis is tested with two different data sets for OECD countries. The results point out the existence of the Fisher relation.

Suggested Citation

  • Örsal, Deniz Dilan Karaman, 2007. "Comparison of panel cointegration tests," SFB 649 Discussion Papers 2007-029, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2007-029
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    2. Janda, Karel & Torkhani, Marouan, 2016. "Causality between energy, carbon, and economic growth: empirical evidence from the European Union," MPRA Paper 75440, University Library of Munich, Germany.
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    5. Mishra, Vinod & Smyth, Russell & Sharma, Susan, 2009. "The energy-GDP nexus: Evidence from a panel of Pacific Island countries," Resource and Energy Economics, Elsevier, vol. 31(3), pages 210-220, August.

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    More about this item

    Keywords

    PanelCointegration tests; Monte Carlo Study; Fisher Hypothesis;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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