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An Alternative System GMM Estimation in Dynamic Panel Models

Housung Jung and Hyeog Ug Kwon

Hi-Stat Discussion Paper Series from Institute of Economic Research, Hitotsubashi University

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.

Keywords: Dynamic panel data; sub-optimal weighting matrix; KI upper boud (search for similar items in EconPapers)
Date: 2007-07
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:hst:hstdps:d07-217

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