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Panel Unit Root Tests in the Presence of Cross-Sectional Dependency and Heterogeneity

Author

Listed:
  • Yoosoon Chang

    (Department of Economics, Rice University)

  • Wonho Song

    (Department of Economics, Rice University)

Abstract
An IV approach, using as instruments nonlinear transformations of the lagged levels, is explored to test for unit roots in panels with general dependency and heterogeneity across cross-sectional units. We allow not only for the cross-sectional dependencies of innovations, but also for the presence of cointegration across cross sectional levels. Unbalanced panels and panels with differing individual short run dynamics and cross-sectionally related dynamics are also permitted. Panels with such cross-sectional dependencies and heterogeneities appear to be quite commonly observed in practical applications. Yet none of the currently available tests can be used to test for unit roots in such general panels. We also more carefully formulate the unit root hypothesis in panels. In particular, using order statistics we make it possible to test for and against the presence of unit roots in some of the individual units for a given panel. The individual IV t-ratios, which are the bases of our tests, are asymptotically normally distributed and cross-sectionally independent. Therefore, the critical values of the order statistics as well as the usual averaged statistic can be easily obtained from simple elementary probability computations. We show via a set of simulations that our tests work well, while other existing tests fail to perform properly. As an illustration, our tests are applied to some of the data sets that were used in earlier studies.

Suggested Citation

  • Yoosoon Chang & Wonho Song, 2002. "Panel Unit Root Tests in the Presence of Cross-Sectional Dependency and Heterogeneity," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B5-2, International Conferences on Panel Data.
    • Handle: RePEc:cpd:pd2002:b5-2
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    File URL: http://econpapers.repec.org/cpd/2002/56_Yoosoon.pdf
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    References listed on IDEAS

    as
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    6. repec:bla:germec:v:7:y:2006:i::p:65-86 is not listed on IDEAS
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    8. Syed A. Basher & Josep Lluís Carrion-i-Silvestre, 2007. "Another Look at the Null of Stationary RealExchange Rates. Panel Data with Structural Breaks and Cross-section Dependence," IREA Working Papers 200710, University of Barcelona, Research Institute of Applied Economics, revised May 2007.
    9. Chortareas, Georgios & Kapetanios, George, 2009. "Getting PPP right: Identifying mean-reverting real exchange rates in panels," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 390-404, February.
    10. Chang, Yoosoon, 2003. "Nonlinear IV Panel Unit Root Tests," Working Papers 2003-06, Rice University, Department of Economics.
    11. Martin Wagner & Jaroslava Hlouskova, 2004. "What's Really the Story with this Balassa-Samuelson Effect in the CEECs?," Diskussionsschriften dp0416, Universitaet Bern, Departement Volkswirtschaft.
    12. Kristofer Månsson & Ghazi Shukur & Pär Sjölander, 2013. "Testing for panel unit roots in the presence of spatial dependency," Applied Economics, Taylor & Francis Journals, vol. 45(29), pages 4152-4159, October.
    13. David Harris & Steve Leybourne & Brendan McCabe, 2003. "Panel Stationarity Tests with Cross-sectional Dependence," Econometrics 0311005, University Library of Munich, Germany.
    14. John C. Chao & Peter C. B. Phillips, 2019. "Uniform Inference in Panel Autoregression," Econometrics, MDPI, vol. 7(4), pages 1-28, November.
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    More about this item

    Keywords

    Panels with cross-sectional dependency and heterogeneity; unit root test; cointegration; covariate; nonlinear instrument; order statistics;
    All these keywords.

    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
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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