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Mean group tests for stationarity in heterogeneous panels

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  • Yongcheol Shin
  • Andy Snell

Abstract

This paper proposes a panel-based mean group test for the null of stationarity against the alternative of unit roots in the presence of both heterogeneity across cross-section units and serial correlation across time periods. Using both sequential and joint asymptotic analyses the proposed test statistic is shown to be distributed as standard normal under the null for large N (number of groups) and large T (number of time periods). Monte Carlo results support the use of joint asymptotic limits (under the further condition that N/T→ 0) as a guide to finite sample performance, but also clearly indicate that the power of our suggested panel-based test is substantially higher than that of the single time-series-based test. Copyright Royal Economic Society 2006

Suggested Citation

  • Yongcheol Shin & Andy Snell, 2006. "Mean group tests for stationarity in heterogeneous panels," Econometrics Journal, Royal Economic Society, vol. 9(1), pages 123-158, March.
    • Handle: RePEc:ect:emjrnl:v:9:y:2006:i:1:p:123-158
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    Cited by:

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    3. Hadri, Kaddour & Kurozumi, Eiji, 2012. "A simple panel stationarity test in the presence of serial correlation and a common factor," Economics Letters, Elsevier, vol. 115(1), pages 31-34.
    4. 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.
    5. Acikgoz, Senay & Ben Ali, Mohamed Sami, 2019. "Where does economic growth in the Middle Eastern and North African countries come from?," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 172-183.
    6. Diego Romero-Avila, 2008. "A confirmatory analysis of the unit root hypothesis for OECD consumption-income ratios," Applied Economics, Taylor & Francis Journals, vol. 40(17), pages 2271-2278.
    7. Alejandro C. García-Cintado & Diego Romero-Ávila & Carlos Usabiaga, 2016. "The economic integration of Spain: a change in the inflation pattern," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 25(1), pages 1-41, December.
    8. Hadri, Kaddour & Kurozumi, Eiji, 2011. "A Locally Optimal Test for No Unit Root in Cross-sectionally Dependent Panel Data," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 52(2), pages 165-184, December.
    9. Hadri, Kaddour & Kurozumi, Eiji & 黒住, 英司, 2008. "A Simple Panel Stationarity Test in the Presence of Cross-Sectional Dependence," CCES Discussion Paper Series 7, Center for Research on Contemporary Economic Systems, Graduate School of Economics, Hitotsubashi University.
    10. Matei Demetrescu & Uwe Hassler & Adina Tarcolea, 2010. "Testing for stationarity in large panels with cross-dependence, and US evidence on unit labor cost," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(8), pages 1381-1397.
    11. repec:ebl:ecbull:v:3:y:2008:i:25:p:1-8 is not listed on IDEAS
    12. Nazlioglu, Saban & Karul, Cagin, 2017. "A panel stationarity test with gradual structural shifts: Re-investigate the international commodity price shocks," Economic Modelling, Elsevier, vol. 61(C), pages 181-192.
    13. Paresh Narayan, 2008. "Is Asian per capita GDP panel stationary?," Empirical Economics, Springer, vol. 34(3), pages 439-449, June.

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    More about this item

    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
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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