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A Bias-Corrected Estimation for Dynamic Panel Models in Small Samples

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Author Info

  • Hiroaki Chigira
  • Taku Yamamoto

Abstract

This paper is concerned with the estimation of the autoregressive parameter of dynamic panel data models. We propose a bias-corrected GMM estimator whose bias is smaller than that of many existing GMM estimators. And we propose a small sample corrected estimator of the variance in order to reduce the size distortion of the Wald test. These estimators are easy to calculate and do not require preliminary estimates. The Monte Carlo experiments indicate that in terms of both bias and size distortion, the bias corrected estimator out performs Blundell and Bond's (1998) system estimator even when using Windmeijer's (2005) correction of the estimated variance of the system estimator.

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File URL: http://hi-stat.ier.hit-u.ac.jp/research/discussion/2006/pdf/D06-177.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 d06-177.

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Date of creation: Jul 2006
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Handle: RePEc:hst:hstdps:d06-177

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Related research

Keywords: Generalized method of moments; bias correction; panel data;

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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.

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