Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context … offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources …) heteroskedasticity and nonlinearity in the relation between the error-ridden covariate and another, error-free, covariate in the equation …

errors following a bivariate and diagonal GARCH(1,1) process. The associated estimator is a GMM estimator shown to have the …

Empirical research based on panel data has to pay special attention to measurement errors. Utility maximization often …

An autoregressive fixed effects panel data equation in error-ridden endogenous and exogenous variables, with finite … memory of disturbances, latent regressors and measurement errors is considered. Finite sample properties of GMM estimators … signal and noise memory, the strength of autocorrelation, the size of the IV set, and the panel length. Finally, some …

measurement errors in an autoregressive panel data model. Finite memory of measurement errors is allowed for. Two GMM …Generalized Method of Moments (GMM) estimation is discussed under the joint occurrence of fixed effects and random … identification, problems of “IV proliferation” and “weak IVs” may arise unless the panel is short. An application based on data for …

The Generalized Method of Moments (GMM) is discussed for handling the joint occurrence of fixed effects and random … measurement errors in an autoregressive panel data model. Finite memory of disturbances, latent regressors and measurement errors … is assumed. Two specializations of GMM are considered: (i) using instruments (IVs) in levels for a differenced version of …

moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short …-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short …-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of …

quasi-maximum likelihood estimator (QMLE) for the MESS is consistent under heteroskedasticity, a property not shared by the …,1), the QMLE can be consistent under unknown heteroskedasticity when the spatial weights matrices in the two MESS processes …