A recent Monte Carlo study claims that the BE estimator outperforms other panel estimators in terms of average estimation bias in a dynamic specification of the Solow model in levels (Hauk and Wacziarg in J Econ Growth 14(2):103-147, 2009). Our simulation results show that the reported performance of the BE estimator depends on the selected parameterization of the data generating process. Using alternative parameter values, a different model specification, and a restricted cross-section estimator, we find that the BE estimator tends to produce a coefficient of the lagged endogenous variable that is biased toward 1.
A recent Monte Carlo study claims that the BE estimator outperforms other panel estimators in terms of average estimation bias in a dynamic specification of the Solow model in levels (Hauk and Wacziarg in J Econ Growth 14(2):103-147, 2009). Our simulation results show that the reported performance of the BE estimator depends on the selected parameterization of the data generating process. Using alternative parameter values, a different model specification, and a restricted cross-section estimator, we find that the BE estimator tends to produce a coefficient of the lagged endogenous variable that is biased toward 1.