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Panel Unit Root Tests with Structural Breaks

Author

Listed:
  • Pengyu Chen

    (University of Birmingham)

  • Yiannis Karavias

    (University of Birmingham)

  • Elias Tzavalis

    (Athens University of Economics and Business)

Abstract

This article introduces the xtbunitroot command in Stata, which implements the panel data unit root tests developed by Karavias and Tzavalis (2014). These tests allow for one or two structural breaks in deterministic components of the series and can be seen as panel data counterparts of the tests by Zivot and Andrews (1992) and Lumsdaine and Papell (1997). The dates of the breaks can be known or unknown. The tests allow for intercepts and linear trends, nonnormal errors and cross-section heteroskedasticity and dependence. They have power against homogeneous and heterogeneous alternatives, and can be applied to panels with small or large time series dimensions.

Suggested Citation

  • Pengyu Chen & Yiannis Karavias & Elias Tzavalis, 2021. "Panel Unit Root Tests with Structural Breaks," Discussion Papers 21-12, Department of Economics, University of Birmingham.
    • Handle: RePEc:bir:birmec:21-12
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    References listed on IDEAS

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    1. Jan Ditzen, 2021. "xtbreak: Estimation and tests for structural breaks in time series and panel data," 2021 Stata Conference 7, Stata Users Group.
    2. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-287, July.
    3. Robin L. Lumsdaine & David H. Papell, 1997. "Multiple Trend Breaks And The Unit-Root Hypothesis," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 212-218, May.
    4. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    5. Sebastian Kripfganz & Vasilis Sarafidis, 2021. "Instrumental-variable estimation of large-T panel-data models with common factors," Stata Journal, StataCorp LP, vol. 21(3), pages 659-686, September.
    6. Delis, Manthos D. & Karavias, Yiannis, 2015. "Optimal versus realized bank credit risk and monetary policy," Journal of Financial Stability, Elsevier, vol. 16(C), pages 13-30.
    7. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2020. "Forecasting With Dynamic Panel Data Models," Econometrica, Econometric Society, vol. 88(1), pages 171-201, January.
    8. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    9. Artūras Juodis & Yiannis Karavias & Vasilis Sarafidis, 2021. "A homogeneous approach to testing for Granger non-causality in heterogeneous panels," Empirical Economics, Springer, vol. 60(1), pages 93-112, January.
    10. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    11. Karavias, Yiannis & Tzavalis, Elias, 2014. "Testing for unit roots in short panels allowing for a structural break," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 391-407.
    12. Richard Harris & Elias Tzavalis, 2004. "Testing for Unit Roots in Dynamic Panels in the Presence of a Deterministic Trend: Re-examining the Unit Root Hypothesis for Real Stock Prices and Dividends," Econometric Reviews, Taylor & Francis Journals, vol. 23(2), pages 149-166.
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    5. Kostakis, Ioannis & Arauzo-Carod, Josep-Maria, 2023. "The key roles of renewable energy and economic growth in disaggregated environmental degradation: Evidence from highly developed, heterogeneous and cross-correlated countries," Renewable Energy, Elsevier, vol. 206(C), pages 1315-1325.

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    Keywords

    Panel data; Unit root; Structural break; Banking; COVID–19; xtbunitroot;
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