Estimating Error Component Models With General MA(q) Disturbances
提出一种仅用最小二乘回归即可估计具有一般MA(q)扰动项的误差成分模型的简单方法，在蒙特卡洛实验中表现良好，适用于面板数据回归。
This paper provides a simple estimation method for an error component regression model with general MA( q ) remainder disturbances. The estimation method utilizes the transformation derived by Baltagi and Li [3] for an error component model with autoregressive remainder disturbances, and a standard orthogonalizing algorithm for the general MA( q ) model. This estimation method is computationally simple utilizing only least-squares regressions. This is important for panel data regressions where brute force GLS is in many cases not feasible.This estimation method performs well relative to true GLS in Monte-Carlo experiments.