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Panel Cointegration Testing in the Presence of a Time Trend

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  • Bernd Droge
  • Deniz Dilan Karaman Örsal

Abstract

The purpose of this paper is to propose a new likelihood-based panel cointegration test in the presence of a linear time trend in the data generating process. This new test is an extension of the likelihood ratio (LR) test of Saikkonen & Lütkepohl (2000) for trend-adjusted data to the panel data framework, and is called the panel SL test. The idea is first to take the average of the individual LR (trace) statistics over the cross-sections and then to standardize the test statistic with the appropriate asymptotic moments. Under the null hypothesis, this standardized statistic has a limiting normal distribution as the number of time periods (T) and the number of cross-sections (N) tend to infinity sequentially. In addition to the approximation based on asymptotic moments, a second approximation approach involving the moments from a vector autoregressive process of order one is also introduced. By means of a Monte Carlo study the finite sample size and size-adjusted power properties of the test are investigated. The test presents reasonable size with the increase in T and N, and has high power in small samples.

Suggested Citation

  • Bernd Droge & Deniz Dilan Karaman Örsal, 2009. "Panel Cointegration Testing in the Presence of a Time Trend," SFB 649 Discussion Papers SFB649DP2009-005, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2009-005
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    References listed on IDEAS

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    1. Carsten Trenkler, 2008. "Determining p-values for systems cointegration tests with a prior adjustment for deterministic terms," Computational Statistics, Springer, vol. 23(1), pages 19-39, January.
    2. 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.
    3. Jorg Breitung, 2005. "A Parametric approach to the Estimation of Cointegration Vectors in Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 151-173.
    4. Doornik, Jurgen A, 1998. " Approximations to the Asymptotic Distributions of Cointegration Tests," Journal of Economic Surveys, Wiley Blackwell, vol. 12(5), pages 573-593, December.
    5. Groen, Jan J J & Kleibergen, Frank, 2003. "Likelihood-Based Cointegration Analysis in Panels of Vector Error-Correction Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 295-318, April.
    6. Joakim Westerlund, 2007. "Testing for Error Correction in Panel Data," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(6), pages 709-748, December.
    7. Helmut Lütkepohl & Pentti Saikkonen & Carsten Trenkler, 2001. "Maximum eigenvalue versus trace tests for the cointegrating rank of a VAR process," Econometrics Journal, Royal Economic Society, vol. 4(2), pages 1-8.
    8. 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.
    9. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    10. Bénédicte Vidaillet & V. D'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    11. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
    12. Deniz Dilan Karaman Örsal & Bernd Droge, 2009. "On the Existence of the Moments of the Asymptotic Trace Statistic," SFB 649 Discussion Papers SFB649DP2009-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Lutkepohl, Helmut & Saikkonen, Pentti, 2000. "Testing for the cointegrating rank of a VAR process with a time trend," Journal of Econometrics, Elsevier, vol. 95(1), pages 177-198, March.
    14. Toda, Hiro Y, 1994. "Finite Sample Properties of Likelihood Ratio Tests for Cointegrating Ranks when Linear Trends are Present," The Review of Economics and Statistics, MIT Press, vol. 76(1), pages 66-79, February.
    15. Toda, Hiro Y., 1995. "Finite Sample Performance of Likelihood Ratio Tests for Cointegrating Ranks in Vector Autoregressions," Econometric Theory, Cambridge University Press, vol. 11(05), pages 1015-1032, October.
    16. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    17. Richard G. Anderson & Hailong Qian & Robert H. Rasche, 2006. "Analysis of panel vector error correction models using maximum likelihood, the bootstrap, and canonical-correlation estimators," Working Papers 2006-050, Federal Reserve Bank of St. Louis.
    18. MacKinnon, James G, 1994. "Approximate Asymptotic Distribution Functions for Unit-Root and Cointegration Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 167-176, April.
    19. Pentti Saikkonen, 1999. "Testing normalization and overidentification of cointegrating vectors in vector autoregressive processes," Econometric Reviews, Taylor & Francis Journals, vol. 18(3), pages 235-257.
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    Citations

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    Cited by:

    1. Roland Strausz, 2009. "The Political Economy of Regulatory Risk," SFB 649 Discussion Papers SFB649DP2009-040, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    2. Uwe Hassler & Mehdi Hosseinkouchack, 2016. "Panel Cointegration Testing in the Presence of Linear Time Trends," Econometrics, MDPI, Open Access Journal, vol. 4(4), pages 1-16, November.
    3. Michał Grajek & Lars-Hendrik Röller, 2012. "Regulation and Investment in Network Industries: Evidence from European Telecoms," Journal of Law and Economics, University of Chicago Press, vol. 55(1), pages 189-216.
    4. Erdal Özmen & Fatma Taşdemir, 2018. "Gross Capital Inflows And Outflows: Twins Or Distant Cousins?," ERC Working Papers 1807, ERC - Economic Research Center, Middle East Technical University, revised Apr 2018.
    5. Barbara Choroś & Wolfgang Härdle & Ostap Okhrin, 2009. "CDO and HAC," SFB 649 Discussion Papers SFB649DP2009-038, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Maria Grith & Wolfgang Härdle & Juhyun Park, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers SFB649DP2009-041, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Daniel Kohlert, 2010. "The determinants of regional real estate returns in the United Kingdom: a vector error correction approach," Journal of Property Research, Taylor & Francis Journals, vol. 27(1), pages 87-117, June.
    8. Antonia Arsova & Deniz Dilan Karaman Oersal, 2013. "Likelihood-based panel cointegration test in the presence of a linear time trend and cross-sectional dependence," Working Paper Series in Economics 280, University of Lüneburg, Institute of Economics.

    More about this item

    Keywords

    Panel Cointegration Test; Likelihood Ratio; Time Trend; Monte Carlo Study;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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

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