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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 v2 = 1-α holds.

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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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Bibliographic Info

Paper provided by Institute of Economic Research, Hitotsubashi University in its series Hi-Stat Discussion Paper Series with number d05-129.

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Date of creation: Jan 2006
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Handle: RePEc:hst:hstdps:d05-129

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  1. 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.
  2. R Blundell & Steven Bond, . "Initial conditions and moment restrictions in dynamic panel data model," Economics Papers W14&104., Economics Group, Nuffield College, University of Oxford.
  3. 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, 07.
  4. Beck, Thorsten & Levine, Ross & Loayza, Norman, 1999. "Finance and the sources of growth," Policy Research Working Paper Series 2057, The World Bank.
  5. Dollar, David & Kraay, Aart, 2001. "Growth is good for the poor," Policy Research Working Paper Series 2587, The World Bank.
  6. Stephen Bond & Anke Hoeffler & Jonathan Temple, 2001. "GMM Estimation of Empirical Growth Models," Economics Papers 2001-W21, Economics Group, Nuffield College, University of Oxford.
  7. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  8. 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.
  9. Maurice J.G. Bun & Jan F. Kiviet, 2002. "The Effects of Dynamic Feedbacks on LS and MM Estimator Accuracy in Panel Data Models," Tinbergen Institute Discussion Papers 02-101/4, Tinbergen Institute, revised 19 Feb 2004.
  10. 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.
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Cited by:
  1. Beatrice D. Simo-Kengne & Manoel Bittencourt & Rangan Gupta, 2011. "House Prices and Economic Growth in South Africa: Evidence from Provincial-Level Data," Working Papers 201116, University of Pretoria, Department of Economics.
  2. 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, 09.
  3. Maurice J.G. Bun & Frank Windmeijer, 2009. "The Weak Instrument Problem of the System GMM Estimator in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 09-086/4, Tinbergen Institute.
  4. 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.
  5. 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.

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