Small sample performance of dynamic panel data estimators in estimating the growth-convergence equation: A Monte Carlo study

Abstract

This chapter conducts a Monte Carlo investigation into small sample properties of some of the dynamic panel data estimators that have been applied to estimate the growth-convergence equation using Summers-Heston data set. The results show that the OLS estimation of this equation is likely to yield seriously upward biased estimates. However, indiscriminate use of panel estimators is also risky, because some of them display large bias and mean square error. Yet, there are panel estimators that have much smaller bias and mean square error. Through a judicious choice of panel estimators it is therefore possible to obtain better estimates of the parameters of the growth-convergence equation. The growth researchers may make use of this potential.

Citation

Islam, N. (2001), "Small sample performance of dynamic panel data estimators in estimating the growth-convergence equation: A Monte Carlo study", Baltagi, B.H., Fomby, T.B. and Carter Hill, R. (Ed.) Nonstationary Panels, Panel Cointegration, and Dynamic Panels (Advances in Econometrics, Vol. 15), Emerald Group Publishing Limited, Leeds, pp. 317-339. https://doi.org/10.1016/S0731-9053(00)15012-1