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Comparison of GMM Estimators for Dynamic Panel AR(1) Models: An Application to the Cross-Country Growth Data

B. H. Beyaztas, E. Firuzan, A. Hacioglu


In this paper, we discuss generalized method of moment (GMM) estimators in the context of dynamic panel autoregressive models of order one (AR(1)) with fixed effects. An extensive simulation study under the Normal and t(5) distributed errors is conducted to evaluate the performances of one- and two-step first-differences, level and system GMM estimators by means of the estimation of autoregressive parameter, standard errors and mean squared errors of the estimators, and coverage probabilities of the constructed confidence intervals. Also, we apply the GMM estimators to country level panel data to analyze the dynamic structure of changes in population growth. Our results reveal that the GMM estimators under t(5) distributed errors have smaller bias and smaller standard errors than that for the standard normal distributed errors when individual-specific effects have standard normal distribution.


Generalized method of moments, Monte Carlo simulation, panel autoregressive models, linear dynamic panel data, population growth.

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