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THE ASYMPTOTIC PROPERTIES OF THE SYSTEM GMM ESTIMATOR IN DYNAMIC PANEL DATA MODELS WHEN BOTH N AND T ARE LARGE

Published online by Cambridge University Press:  15 September 2014

Kazuhiko Hayakawa
Kazuhiko Hayakawa*
Affiliation:
Hiroshima University
*
*Address correspondence to Kazuhiko Hayakawa, Department of Economics, Hiroshima University, 1-2-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8525, Japan; e-mail: kazuhaya@hiroshima-u.ac.jp.
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Abstract

In this paper, we derive the asymptotic properties of the system generalized method of moments (GMM) estimator in dynamic panel data models with individual and time effects when both N and T, the dimensions of cross-section and time series, are large. Specifically, we show that the two-step system GMM estimator is consistent when a suboptimal weighting matrix where off-diagonal blocks are set to zero is used. Such consistency results theoretically support the use of the system GMM estimator in large N and T contexts even though it was originally developed for large N and small T panels. Simulation results indicate that the large N and large T asymptotic results approximate the finite sample behavior reasonably well unless persistency of data is strong and/or the variance ratio of individual effects to the disturbances is large.

Type
MISCELLANEA
Information
Econometric Theory , Volume 31 , Issue 3 , June 2015 , pp. 647 - 667
Copyright
Copyright © Cambridge University Press 2014 

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Footnotes

This paper is a revision of the second chapter of my Ph.D. thesis submitted to Hitotsubashi University. I am deeply grateful to my advisers Taku Yamamoto and Eiji Kurozumi for their guidance and suggestions. I also acknowledge Guido Kuersteiner (co-editor), two anonymous referees, Katsuto Tanaka, In Choi, Ryo Okui, Hiroaki Chigira, and the participants of the European Meeting of Econometric Society in Milan, a research seminar at HKUST, and the Kansai Econometrics Conference for their helpful comments. Part of this paper was written while the author is visiting University of Cambridge as a JSPS Postdoctoral Fellow for Research Abroad. I acknowledge the financial support from the JSPS Fellowship and the Grant-in-Aid for Scientific Research (KAKENHI 20830056, 22730178) provided by the JSPS. However, all remaining errors are my own.

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