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Testing For Stationarity With A Break In Panels Where The Time Dimension Is Finite

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  • Kaddour Hadri
  • Rolf Larsson
  • Yao Rao

Abstract

In this paper, we consider the case of finite time dimension in the panel stationarity tests with structural breaks. By fixing T; the finite sample properties of the tests for both micro (T small and N large) and macro (both T and N large) panel data are generally greatly improved. More importantly, the derivation of the tests for finite T and N -> infinity, as opposed to joint asymptotic where N and T -> infinity simultaneously, avoids the imposition of the rate condition N/T -> 0; making the test valid for any (T;N) blend. Four models corresponding to the usual combination of breaks are considered. The asymptotic distributions of the test are derived under the null and are shown to be normally distributed. Their moments for T fixed are derived analytically employing two approaches. The first method is based on the Laplace Transform and the second derivation is based on Ghazal’s (1994) corollary. The case with unknown breaks is also considered. The proposed tests have generally empirical sizes that are very close to the nominal size. The Monte-Carlo simulations show that the power of the test statistics increases substantially with N and T.
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Suggested Citation

  • Kaddour Hadri & Rolf Larsson & Yao Rao, 2012. "Testing For Stationarity With A Break In Panels Where The Time Dimension Is Finite," Bulletin of Economic Research, Wiley Blackwell, vol. 64(Supplemen), pages 123-148, December.
    • Handle: RePEc:bla:buecrs:v:64:y:2012:i:s1:p:s123-s148
    DOI: j.1467-8586.2012.00457.x
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    File URL: http://hdl.handle.net/10.1111/j.1467-8586.2012.00457.x
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    Cited by:

    1. Yiannis Karavias & Elias Tzavalis, 2013. "The power performance of fixed-T panel unit root tests allowing for structural breaks," Discussion Papers 13/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    2. Kaddour Hadri & Eiji Kurozumi & Yao Rao, 2015. "Novel panel cointegration tests emending for cross‐section dependence with N fixed," Econometrics Journal, Royal Economic Society, vol. 18(3), pages 363-411, October.
    3. 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.
    4. Tolga Omay & Mübariz Hasanov & Yongcheol Shin, 2018. "Testing for Unit Roots in Dynamic Panels with Smooth Breaks and Cross-Sectionally Dependent Errors," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 167-193, June.
    5. Akpolat, Ahmet Gökce & Bakırtaş, Tahsin, 2024. "The nonlinear impact of renewable energy, fossil energy and CO2 emissions on human development index for the eight developing countries," Energy, Elsevier, vol. 312(C).
    6. Kézdi, Gábor & Mátyás, László & Balázsi, László & Divényi, János Károly, 2014. "A közgazdasági adatforradalom és a panelökonometria [The revolution in economic data and panel econometrics]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1319-1340.
    7. Yiannis Karavias & Elias Tzavalis, 2014. "Testing for unit roots in panels with structural changes, spatial and temporal dependence when the time dimension is finite," Discussion Papers 14/03, University of Nottingham, Granger Centre for Time Series Econometrics.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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