of bias of (generalized) MMestimators tends to increase with the number of moment conditions exploited. Forvarious … feedbacks none of the techniques examined dominates. However, asimple bias corrected LS estimator which presupposes strict …

This paper studies the behaviour of the bias corrected LSDV estimator and GMM-based estimators in dynamic panel data … models with endogenous regressors. We obtain an expansion of the conditional bias of the LSDV estimator with the leading term … although the bias has similar structure whether or not the exogeneity assumption holds, the approximation technique that the …

the first order autoregressive case. A comparison between asymptotic bias and small sample simulated bias has also been …

magnitude of bias of (generalized) MM estimators tends to increase with the number of moment conditions exploited. For various … feedbacks none of the techniques examined dominates. However, a simple bias corrected LS estimator which presupposes strict …

a k-step parametric bootstrap bias corrected estimator. We prove that our estimator is asymptotically normal and is … centered at the true parameter if T grows faster than ∛n. In addition to bias correction, we construct a confidence interval …’s is smaller than those of the alternatives. We also propose bias correction for average marginal effects …

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 …