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The Asymptotic Properties of the System GMM Estimator in Dynamic Panel Data Models When Both N and T are Large

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  • Kazuhiko Hayakawa

Abstract

This paper complements Alvarez and Arellano (2003) by showing the asymptotic properties of the system GMM estimator for AR(1) panel data models when both N and T tend to infinity. We show that the system GMM estimator with the instruments which Blundell and Bond (1998) used will be inconsistent when both N and T are large. We also show that the system GMM estimator with all available instruments, including redundant ones, will be consistent if σ η 2 /σ v 2 = 1-α holds.

Suggested Citation

  • Kazuhiko Hayakawa, 2006. "The Asymptotic Properties of the System GMM Estimator in Dynamic Panel Data Models When Both N and T are Large," Hi-Stat Discussion Paper Series d05-129, Institute of Economic Research, Hitotsubashi University.
    • Handle: RePEc:hst:hstdps:d05-129
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    File URL: http://hi-stat.ier.hit-u.ac.jp/research/discussion/2005/pdf/D05-129.pdf
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    References listed on IDEAS

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    1. Stephen Bond & Anke Hoeffler & Jonathan Temple, 2001. "GMM Estimation of Empirical Growth Models," Economics Papers 2001-W21, Economics Group, Nuffield College, University of Oxford.
    2. Alonso-Borrego, Cesar & Arellano, Manuel, 1999. "Symmetrically Normalized Instrumental-Variable Estimation Using Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 36-49, January.
    3. Dollar, David & Kraay, Aart, 2002. "Growth Is Good for the Poor," Journal of Economic Growth, Springer, vol. 7(3), pages 195-225, September.
    4. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    5. Javier Alvarez & Manuel Arellano, 2003. "The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators," Econometrica, Econometric Society, vol. 71(4), pages 1121-1159, July.
    6. Asli Demeirgüç-Kunt & Ross Levine (ed.), 0. "Finance and Growth," Books, Edward Elgar Publishing, number 17119.
    7. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    8. 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.
    9. Bun, Maurice J.G. & Kiviet, Jan F., 2006. "The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 409-444, June.
    10. Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
    11. Stephen Bond & Anke Hoeffler, 2001. "GMM Estimation of Empirical Growth Models," Economics Series Working Papers 2001-W21, University of Oxford, Department of Economics.
    12. Beck, Thorsten & Levine, Ross & Loayza, Norman, 2000. "Finance and the sources of growth," Journal of Financial Economics, Elsevier, vol. 58(1-2), pages 261-300.
    13. Hayakawa, Kazuhiko, 2007. "Small sample bias properties of the system GMM estimator in dynamic panel data models," Economics Letters, Elsevier, vol. 95(1), pages 32-38, April.
    14. 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.
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    Cited by:

    1. Hayakawa, Kazuhiko, 2010. "The effects of dynamic feedbacks on LS and MM estimator accuracy in panel data models: Some additional results," Journal of Econometrics, Elsevier, vol. 159(1), pages 202-208, November.
    2. 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.
    3. Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
    4. Beatrice Simo-Kengne & Manoel Bittencourt & Rangan Gupta, 2012. "House Prices and Economic Growth in South Africa: Evidence From Provincial-Level Data," Journal of Real Estate Literature, Taylor & Francis Journals, vol. 20(1), pages 97-117, January.
    5. Dang, Viet Anh & Kim, Minjoo & Shin, Yongcheol, 2015. "In search of robust methods for dynamic panel data models in empirical corporate finance," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 84-98.
    6. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    7. Georg Graevenitz & Stefan Wagner & Dietmar Harhoff, 2013. "Incidence and Growth of Patent Thickets: The Impact of Technological Opportunities and Complexity," Journal of Industrial Economics, Wiley Blackwell, vol. 61(3), pages 521-563, September.
    8. van Zanden, Jan Luiten & Papaioannou, Jason, 2012. "The Dictator Effect: How Long Years in Office Affects Economic Development in Africa and the Near East," CEPR Discussion Papers 8962, C.E.P.R. Discussion Papers.
    9. repec:cep:stiecm:/2014/577 is not listed on IDEAS
    10. Shobande Olatunji Abdul, 2020. "Fiscal Rule in Africa," Open Economics, De Gruyter, vol. 3(1), pages 112-120, January.

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