Model averaging estimation of panel data models with many instruments and boosting

Applied researchers often confront two issues when using the fixed effect-two-stage least squares (FE-2SLS) estimator for panel data models. One is that it may lose its consistency due to too many instruments. The other gain of FE-2SLS not exceed loss endogeneity weak. In this paper, an L2Boosting regularization procedure models proposed tackle instruments issue. We then construct a Stein-like model-averaging take advantage FE and FE-2SLS-Boosting estimators. Finite sample properties are examined in Monte Carlo empirical application presented.