Ordinary least squares

Statistics

Covariance matrix

Applied mathematics

Panel data

Economics

Mathematical optimization

Covariance

Least-squares function approximation

Mathematics

Estimator

Generalized least squares

Econometrics

Monte Carlo method

Heteroscedasticity

Cross-sectional data

Non-linear least squares

Empirical Economics

This paper considers generalized least squares (GLS) estimation for linear panel data models. By estimating the large error covariance matrix consistently, the proposed feasible GLS estimator is more efficient than the ordinary least squares in the presence of heteroskedasticity, serial and cross-sectional correlations. The covariance matrix used for the feasible GLS is estimated via the banding and thresholding method. We establish the limiting distribution of the proposed estimator. A Monte Carlo study is considered. The proposed method is applied to an empirical application.

Feasible generalized least squares for panel data with cross-sectional and serial correlations