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Panel Unit Roots Tests for Cross-Sectionally Correlated Panels: A Monte Carlo Comparison

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  • Luciano Gutierrez

Abstract

This paper deals with the finite sample performance of a set of unit root tests for cross correlated panels. As is well known, univariate tests are not powerful to reject the null of a unit root for the usual economic variables while panel tests, by exploiting the large number of cross-section units, provide a device to increase the power of unit root tests. We investigate the finite sample properties of recently proposed panel unit root tests for cross-sectionally correlated panels. Specifically, the size and power of Choi’s (2002), Bai and Ng’s (2003), Moon and Perron’s (2003), and Phillips and Sul’s (2003) tests are analyzed by a Monte Carlo simulation study. In synthesis, Moon and Perron’s (2003) tests show good size and power for different values of T and N and model specifications. Focusing on Bai and Ng’s (2003) procedure, the simulation study highlights first that the suggested ADF test for the nonstationary analysis of the common factor lack of power, and secondly the simulation shows that the pooled Dickey-Fuller-GLS test provides higher power than the pooled ADF test for the analysis of nonstationary properties of the idiosyncratic components. Choi’s (2002) tests are strongly oversized when the common factor influences the cross-section units heterogeneously. Finally, all the tests lack power when a deterministic trend is included in the data generating process.

Suggested Citation

  • Luciano Gutierrez, 2003. "Panel Unit Roots Tests for Cross-Sectionally Correlated Panels: A Monte Carlo Comparison," Econometrics 0310004, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0310004
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    References listed on IDEAS

    as
    1. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    2. Moon, Hyungsik Roger & Perron, Benoit & Phillips, Peter C.B., 2007. "Incidental trends and the power of panel unit root tests," Journal of Econometrics, Elsevier, vol. 141(2), pages 416-459, December.
    3. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
    4. Backus, David K & Kehoe, Patrick J, 1992. "International Evidence of the Historical Properties of Business Cycles," American Economic Review, American Economic Association, vol. 82(4), pages 864-888, September.
    5. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    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 631-652, Special I.
    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. G. S. Maddala & Shaowen Wu, 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(S1), pages 631-652, November.
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    More about this item

    Keywords

    Panel unit root test; Cross section dependence; Monte Carlo Simulation;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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