Generalized Method of Moments (GMM) estimation is discussed under the joint occurrence of fixed effects and random … measurement errors in an autoregressive panel data model. Finite memory of measurement errors is allowed for. Two GMM …, to illustrate finite sample biases, is considered. Overall, with respect to bias and IV strength, GMM specialization (ii …

memory of disturbances, latent regressors and measurement errors is considered. Finite sample properties of GMM estimators …

The Generalized Method of Moments (GMM) is discussed for handling the joint occurrence of fixed effects and random … is assumed. Two specializations of GMM are considered: (i) using instruments (IVs) in levels for a differenced version of … sample biases and IV quality are illustrated by Monte Carlo simulations. Overall, with respect to bias and IV strength, GMM …

GMM estimation of autoregressive panel data equations in error-ridden variables when the noise has memory, is … strength of autocorrelation and the size of the IV set. GMM procedures using IVs in differences on equations in levels, in …

memory of disturbances, latent regressors and measurement errors is considered. Finite sample properties of GMM estimators …

The Generalized Method of Moments (GMM) is discussed for handling the joint occurrence of fixed effects and random … is assumed. Two specializations of GMM are considered: (i) using instruments (IVs) in levels for a differenced version of … sample biases and IV quality are illustrated by Monte Carlo simulations. Overall, with respect to bias and IV strength, GMM …

GMM estimation of autoregressive panel data equations in error-ridden variables when the noise has memory, is … strength of autocorrelation and the size of the IV set. GMM procedures using IVs in differences on equations in levels, in …