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An Alternative System GMM Estimation in Dynamic Panel Models

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  • Housung Jung
  • Hyeog Ug Kwon

Abstract

The system GMM estimator in dynamic panel data models which combines two moment conditions, i.e., for the differenced equation and for the model in levels, is known to be more efficient than the first-difference GMM estimator. However, an initial optimal weight matrix is not known for the system estimation procedure. Therefore, we suggest the use of 'a suboptimal weight matrix' which may reduce the finite sample bias whilst increasing its efficiency. Using the Kantorovich inequality, we find that the potential efficiency gain becomes large when the variance of individual effects increases compared to the variance of the idiosyncratic errors. (Our Monte Carlo experiments show that the small sample properties of the suboptimal system estimator are shown to be much more reliable than any other conventional system GMM estimator in terms of bias and efficiency.

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File URL: http://hi-stat.ier.hit-u.ac.jp/research/discussion/2007/pdf/D07-217.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 d07-217.

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Date of creation: Jul 2007
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Handle: RePEc:hst:hstdps:d07-217

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Related research

Keywords: Dynamic panel data; sub-optimal weighting matrix; KI upper boud;

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  1. César Alonso-Borrego & Rocío Sánchez-Mangas, 2001. "Gmm Estimation Of A Production Function With Panel Data: An Application To Spanish Manufacturing Firms," Statistics and Econometrics Working Papers ws015527, Universidad Carlos III, Departamento de Estadística y Econometría.
  2. 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.
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