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Robust Unit Root and Cointegration Rank Tests for Panels and Large Systems

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Abstract

This study develops new tests for unit roots and cointegration rank in heterogeneous time series panels using methods that are robust to the presence of both incidental trends and cross sectional dependency of unknown form. Furthermore, the procedures do not require a choice of lag truncation or bandwidth to accommodate higher order serial correlation. The cointegration rank tests can also be implemented in relatively large dimensioned systems of equations for which conventional VECM based tests become infeasible. Monte Carlo simulations demonstrate that the procedures have high power and good size properties even in panels with relatively small dimensions.

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  • Peter Pedroni & Tim Vogelsang, 2005. "Robust Unit Root and Cointegration Rank Tests for Panels and Large Systems," Department of Economics Working Papers 2005-04, Department of Economics, Williams College.
  • Handle: RePEc:wil:wileco:2005-04
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    File URL: http://web.williams.edu/Economics/wp/pedronirobust.pdf
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    References listed on IDEAS

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    1. Anindya Banerjee & Massimiliano Marcellino & Chiara Osbat, 2004. "Some cautions on the use of panel methods for integrated series of macroeconomic data," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 322-340, December.
    2. Christian Gengenbach & Franz C. Palm & Jean-Pierre Urbain, 2010. "Panel Unit Root Tests in the Presence of Cross-Sectional Dependencies: Comparison and Implications for Modelling," Econometric Reviews, Taylor & Francis Journals, vol. 29(2), pages 111-145, April.
    3. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(03), pages 597-625, June.
    4. 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.
    5. Chang, Yoosoon, 2004. "Bootstrap unit root tests in panels with cross-sectional dependency," Journal of Econometrics, Elsevier, vol. 120(2), pages 263-293, June.
    6. Peter Pedroni, 2000. "Fully Modified OLS for Heterogeneous Cointegrated Panels," Department of Economics Working Papers 2000-03, Department of Economics, Williams College.
    7. 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.
    8. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    9. Nicholas M. Kiefer & Timothy J. Vogelsang & Helle Bunzel, 2000. "Simple Robust Testing of Regression Hypotheses," Econometrica, Econometric Society, vol. 68(3), pages 695-714, May.
    10. Chang, Yoosoon, 2002. "Nonlinear IV unit root tests in panels with cross-sectional dependency," Journal of Econometrics, Elsevier, vol. 110(2), pages 261-292, October.
    11. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    12. Rolf Larsson & Johan Lyhagen & Mickael Lothgren, 2001. "Likelihood-based cointegration tests in heterogeneous panels," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 1-41.
    13. Peter C. B. Phillips & Donggyu Sul, 2003. "Dynamic panel estimation and homogeneity testing under cross section dependence *," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 217-259, June.
    14. Banerjee, Anindya, 1999. " Panel Data Unit Roots and Cointegration: An Overview," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 607-629, Special I.
    15. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    16. Breitung, Jorg, 2002. "Nonparametric tests for unit roots and cointegration," Journal of Econometrics, Elsevier, vol. 108(2), pages 343-363, June.
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    Cited by:

    1. Holly, Sean & Pesaran, M. Hashem & Yamagata, Takashi, 2010. "A spatio-temporal model of house prices in the USA," Journal of Econometrics, Elsevier, vol. 158(1), pages 160-173, September.
    2. Pedroni, Peter L. & Vogelsang, Timothy J. & Wagner, Martin & Westerlund, Joakim, 2015. "Nonparametric rank tests for non-stationary panels," Journal of Econometrics, Elsevier, vol. 185(2), pages 378-391.
    3. Chen, Ping-Yu & Chen, Sheng-Tung & Hsu, Chia-Sheng & Chen, Chi-Chung, 2016. "Modeling the global relationships among economic growth, energy consumption and CO2 emissions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 420-431.
    4. Sean Holly & Mehdi Raissi, 2009. "The Macroeconomic Effects of European Financial Development: A Heterogenous Panel Analysis," Working Paper / FINESS 1.4, DIW Berlin, German Institute for Economic Research.
    5. Mulatu F. Zehirun & Marthinus C. Breitenbach & Francis M. Kemegue, 2015. "Assessment of Monetary Union in SADC: Evidence from Cointegration and Panel Unit Root Tests," Working Papers 201502, University of Pretoria, Department of Economics.
    6. Peter Pedroni, 2007. "Social capital, barriers to production and capital shares: implications for the importance of parameter heterogeneity from a nonstationary panel approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 429-451.
    7. N. Vasudeva Murthy, 2009. "The Feldstein–Horioka puzzle in Latin American and Caribbean countries: a panel cointegration analysis," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(2), pages 176-188, April.

    More about this item

    Keywords

    Panel Unit Roots; Cointegration Rank Tests; Robust Autocovariance Estimation;

    JEL classification:

    • 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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