Alternative GMM Estimators for First-order Autoregressive Panel Model: An Improving Efficiency Approach
Ahmed Youssef and
Mohamed Abonazel ()
MPRA Paper from University Library of Munich, Germany
This paper considers first-order autoregressive panel model which is a simple model for dynamic panel data (DPD) models. The generalized method of moments (GMM) gives efficient estimators for these models. This efficiency is affected by the choice of the weighting matrix which has been used in GMM estimation. The non-optimal weighting matrices have been used in the conventional GMM estimators. This led to a loss of efficiency. Therefore, we present new GMM estimators based on optimal or suboptimal weighting matrices. Monte Carlo study indicates that the bias and efficiency of the new estimators are more reliable than the conventional estimators.
Keywords: Dynamic panel data; Generalized method of moments; Kantorovich inequality upper bound; Monte Carlo simulation; Optimal and suboptimal weighting matrices (search for similar items in EconPapers)
JEL-codes: C4 C5 M21 (search for similar items in EconPapers)
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