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GMM Unit Root Inference in Generally Trending and Cross-Correlated Dynamic Panels

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  • Robertson, Donald
  • Sarafidis, Vasilis
  • Westerlund, Joakim

Abstract

This paper proposes a new panel unit root test based on the generalized method of moments approach for panels with a small number of time periods and a large number of cross-section units, N. In the model that we consider the deterministic trend function is essentially unrestricted and the errors are cross-sectionally correlated in a very general fashion. In spite of these allowances, the GMM-statistic is shown to be asymptotically unbiased, square root N-consistent and asymptotically normal for all values of the autoregressive (AR) coefficient, ρ, including unity, making it an ideal candidate for unit root inference. Results from both simulated and real data are provided to suggest that the asymptotic properties are borne out well in small samples.

Suggested Citation

  • Robertson, Donald & Sarafidis, Vasilis & Westerlund, Joakim, 2014. "GMM Unit Root Inference in Generally Trending and Cross-Correlated Dynamic Panels," MPRA Paper 53419, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:53419
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    References listed on IDEAS

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    1. Rembert De Blander & Geert Dhaene, 2012. "Unit root tests for panel data with AR(1) errors and small T," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 101-124, February.
    2. John Sutton, 1997. "Gibrat's Legacy," Journal of Economic Literature, American Economic Association, vol. 35(1), pages 40-59, March.
    3. Joakim Westerlund & Jörg Breitung, 2013. "Lessons from a Decade of IPS and LLC," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 547-591, August.
    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. Maurice J. G. Bun & Frank Windmeijer, 2010. "The weak instrument problem of the system GMM estimator in dynamic panel data models," Econometrics Journal, Royal Economic Society, vol. 13(1), pages 95-126, February.
    6. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    7. Chesher, Andrew, 1979. "Testing the Law of Proportionate Effect," Journal of Industrial Economics, Wiley Blackwell, vol. 27(4), pages 403-411, June.
    8. Robertson, Donald & Sarafidis, Vasilis, 2015. "IV estimation of panels with factor residuals," Journal of Econometrics, Elsevier, vol. 185(2), pages 526-541.
    9. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    10. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    11. Abadir,Karim M. & Magnus,Jan R., 2005. "Matrix Algebra," Cambridge Books, Cambridge University Press, number 9780521537469, October.
    12. Han, Chirok & Phillips, Peter C. B., 2010. "Gmm Estimation For Dynamic Panels With Fixed Effects And Strong Instruments At Unity," Econometric Theory, Cambridge University Press, vol. 26(1), pages 119-151, February.
    13. Kruiniger, Hugo, 2009. "Gmm Estimation And Inference In Dynamic Panel Data Models With Persistent Data," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1348-1391, October.
    14. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    15. 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.
    16. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, July-Dece.
    17. Richard E. Caves, 1998. "Industrial Organization and New Findings on the Turnover and Mobility of Firms," Journal of Economic Literature, American Economic Association, vol. 36(4), pages 1947-1982, December.
    18. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    19. 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.
    20. Kruiniger, Hugo, 2013. "Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions," Journal of Econometrics, Elsevier, vol. 173(2), pages 175-188.
    21. Jushan Bai, 2013. "Fixed‐Effects Dynamic Panel Models, a Factor Analytical Method," Econometrica, Econometric Society, vol. 81(1), pages 285-314, January.
    22. Patrick Sevestre & Laszlo Matyas, 2008. "The Econometrics of Panel Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00279977, HAL.
    23. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    24. 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.
    25. Stephen Bond & Céline Nauges & Frank Windmeijer, 2005. "Unit roots: identification and testing in micro panels," CeMMAP working papers CWP07/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. S. de Silva & K. Hadri & A. R. Tremayne, 2009. "Panel unit root tests in the presence of cross-sectional dependence: finite sample performance and an application," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 340-366, July.
    27. Kaddour Hadri & Rolf Larsson, 2005. "Testing for stationarity in heterogeneous panel data where the time dimension is finite," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 55-69, March.
    28. Bai, Jushan & Ng, Serena, 2010. "Panel Unit Root Tests With Cross-Section Dependence: A Further Investigation," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1088-1114, August.
    29. Kruiniger, Hugo, 2007. "An Efficient Linear Gmm Estimator For The Covariance Stationary Ar(1)/Unit Root Model For Panel Data," Econometric Theory, Cambridge University Press, vol. 23(3), pages 519-535, June.
    30. Jaroslava Hlouskova & Martin Wagner, 2006. "The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 85-116.
    31. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    32. repec:cup:cbooks:9780521822893 is not listed on IDEAS
    33. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    34. Edith Madsen, 2010. "Unit root inference in panel data models where the time-series dimension is fixed: a comparison of different tests," Econometrics Journal, Royal Economic Society, vol. 13(1), pages 63-94, February.
    35. 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.
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    Cited by:

    1. Artūras Juodis & Vasilis Sarafidis, 2018. "Fixed T dynamic panel data estimators with multifactor errors," Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 893-929, September.
    2. In Choi, 2019. "Unit Root Tests for Dependent Micropanels," The Japanese Economic Review, Springer, vol. 70(2), pages 145-167, June.
    3. 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.
    4. Juodis, Arturas & Sarafidis, Vasilis, 2015. "A Simple Estimator for Short Panels with Common Factors," MPRA Paper 68164, University Library of Munich, Germany.

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    More about this item

    Keywords

    Panel data; unit root test; cross-section dependence; common factors; GMM.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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