Robust Estimation of Parameter with One Half Rotating Panel

In this paper, based on stationary panel data model with one-way error component, FGLS estimation with one half rotating panel is investigated. It has been found that standard errors of FGLS estimators lead to extreme overconfldence. Therefore, based on FGLS estimation and PCSEs, a new estimation method is proposed to correct exorbitant overconfldence and make the estimation of parameters confldent. Under the assumed stationary conditions, we prove the consistency and the asymptotic normality. Monte Carlo simulation is conducted to analyze flnite sample properties. Compare to FGLS estimation, the method proposed in the paper can decrease the overconfldences on the premise of remaining A-Bias and MSE the same basically.