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The Refinement of a Common Correlated Effect Estimator in Panel Unit Root Testing: An Extensive Simulation Study

Author

Listed:
  • Tolga Omay

    (Department of Economics, Atılım University, 06830 Ankara, Türkiye)

  • Yılmaz Akdi

    (Department of Statistics, Ankara University, 06100 Ankara, Türkiye)

  • Furkan Emirmahmutoglu

    (Department of Econometrics, Ankara Hacı Bayram Veli University, 06500 Ankara, Türkiye)

  • Meltem Eryılmaz

    (Department of Software Engineering, Ostim Technical University, 06374 Ankara, Türkiye)

Abstract

The Common Correlated Effect (CCE) estimator is widely used in panel data models to address cross-sectional dependence, particularly in nonstationary panels. However, existing estimators have limitations, especially in small-sample settings. This study refines the CCE estimator by introducing new proxy variables and testing them through a comprehensive set of simulations. The proposed method is simple yet effective, aiming to improve the handling of cross-sectional dependence. Simulation results show that the refined estimator eliminates cross-sectional dependence more effectively than the original CCE, with improved power properties under both weak- and strong-dependence scenarios. The refined estimator performs particularly well in small sample sizes. These findings offer a more robust framework for panel unit root testing, enhancing the reliability of CCE estimators and contributing to further developments in addressing cross-sectional dependence in panel data models.

Suggested Citation

  • Tolga Omay & Yılmaz Akdi & Furkan Emirmahmutoglu & Meltem Eryılmaz, 2024. "The Refinement of a Common Correlated Effect Estimator in Panel Unit Root Testing: An Extensive Simulation Study," Mathematics, MDPI, vol. 12(22), pages 1-25, November.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:22:p:3458-:d:1514655
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    References listed on IDEAS

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