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Econometrics 2016, 4(4), 47;

Subset-Continuous-Updating GMM Estimators for Dynamic Panel Data Models

Department of Economics, Virginia Tech, Blacksburg, VA 24060, USA
Department of Economics and Finance, University of Texas at El Paso, El Paso, TX 79968, USA
Author to whom correspondence should be addressed.
Academic Editors: In Choi, Ryo Okui, Marc S. Paolella and Kerry Patterson
Received: 25 May 2016 / Revised: 23 November 2016 / Accepted: 25 November 2016 / Published: 30 November 2016
(This article belongs to the Special Issue Recent Developments in Panel Data Methods)
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The two-step GMM estimators of Arellano and Bond (1991) and Blundell and Bond (1998) for dynamic panel data models have been widely used in empirical work; however, neither of them performs well in small samples with weak instruments. The continuous-updating GMM estimator proposed by Hansen, Heaton, and Yaron (1996) is in principle able to reduce the small-sample bias, but it involves high-dimensional optimizations when the number of regressors is large. This paper proposes a computationally feasible variation on these standard two-step GMM estimators by applying the idea of continuous-updating to the autoregressive parameter only, given the fact that the absolute value of the autoregressive parameter is less than unity as a necessary requirement for the data-generating process to be stationary. We show that our subset-continuous-updating method does not alter the asymptotic distribution of the two-step GMM estimators, and it therefore retains consistency. Our simulation results indicate that the subset-continuous-updating GMM estimators outperform their standard two-step counterparts in finite samples in terms of the estimation accuracy on the autoregressive parameter and the size of the Sargan-Hansen test. View Full-Text
Keywords: dynamic panel data models; Arellano-Bond GMM estimator; Blundell-Bond GMM estimator; subset-continuous-updating GMM estimators dynamic panel data models; Arellano-Bond GMM estimator; Blundell-Bond GMM estimator; subset-continuous-updating GMM estimators
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Ashley, R.A.; Sun, X. Subset-Continuous-Updating GMM Estimators for Dynamic Panel Data Models. Econometrics 2016, 4, 47.

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