Bias Reduction in Estimating Long-run Relationships from Dynamic Heterogenous Panels

This paper considers the small sample properties of the mean group estimator of the long-run coefficients in dynamic heterogeneous panels, and using Monte Carlo techniques examines the effectiveness of a number of alternative bias-correction procedures in reducing the small sample bias of these estimates. Four different bias-corrected estimators of the long-run coefficients are considered. A `naive' procedure which attempts to bias-correct the estimator of the long-run coefficients, two variations of a direct approach which derives bias-corrections of the estimators of the short-run coefficients, and a bootstrap bias- correction procedure.