"The Limited Information Maximum Likelihood Approach to Dynamic Panel Structural Equations"

We develop the panel limited information maximum likelihood (PLIML) approach for estimating dynamic panel structural equation models. When there are dynamic effects and endogenous variables with individual effects at the same time, the PLIML estimation method for the filtered data does give not only a consistent estimator, but also it has the asymptotic normality and often attains the asymptotic bound when the number of orthogonal conditions is large. Our formulation includes Alvarez and Arellano (2003), Blundell and Bond (2000) and other linear dynamic panel models as special cases. We also compare the PLIML and Panel GMM methods and propose an improvement of PLIML for heteroscedastic disturbances among many indivisuals.