finite sample performance characteristics that dominate other procedures, such as bias corrected least squares, GMM and … system GMM methods. The asymptotic theory holds as long as the cross section (n) or time series (T) sample size is large …

for the "verify-out-of-sample" case. We show that sieve conditional expectation projection based GMM estimators achieve … mild regularity conditions. Although inverse probability weighting based GMM estimators are also shown to be …

This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimators when the number … certain regularity conditions, the GMM estimators are shown to converge in probability but not necessarily to the true … parameter, and conditions for consistent GMM estimation are given. A general framework for the GMM limit distribution theory is …

(GIVE) method and the generalized method of moments (GMM) estimator are developed. In models with both stationary and … nonstationary components, the FM-GIVE and FM-GMM techniques provide efficiency gains over FM-IV in the estimation of the stationary … and GMM estimators with respect to the stationary components. The theory applies even when there is no prior knowledge of …