The law of iterated logarithm of estimators for partially linear panel data models

This paper studies the asymptotic theory for a semiparametric partially linear panel data model with a one-way error component structure, which has a wide range of applications in many important areas. We establish the law of iterated logarithm of the feasible semiparametric generalized least squares estimator of the linear regression coefficients as well as the estimators of the one-way error variances. In addition, the optimal strong convergence rate of the estimator of the function for the nonlinear component is derived as well.