have smaller bias that is flatter as a function of first step smoothing leading to improved small sample properties. Series …

This papers studies and compares the asymptotic bias of GMM and generalized empirical likelihood (GEL) estimators in … offers much reduced mean and median bias, root mean squared error and mean absolute error, as compared with two-step GMM and … other GEL methods. Both analytical and bootstrap bias-adjusted two-step GMM estima-tors are compared. Analytical bias …

bias and so are important when the first step is machine learning. We derive LR moment conditions for dynamic discrete …

have smaller bias that is flatter as a function of first step smoothing leading to improved small sample properties. Series …

bias and so are important when the first step is machine learning. We derive LR moment conditions for dynamic discrete …

-consistency, due to first order bias in the expected influence function. We give a general bias correction that can be added to a … find that this bias correction can lead to large efficiency improvements and lower sensitivity to bandwidth choice …