This paper suggests random and fixed effects spatial two-stage least squares estimators for the generalized mixed regressive spatial autoregressive panel data model. This extends the generalized spatial panel model of Baltagi, Egger and Pfaffermayr (2013) by the inclusion of a spatial lag...

The estimation of linear, static regression equations from panel data with measurement errors in the regressors is considered. If the latent regressor is autocorrelated or non-stationary, several consistent instrumental variables (IV) and generalized method of moments (GMM) estimators usually...

We propose theory-based Monte Carlo simulations to quantify the extent to which the estimated speed of convergence depends on the underlying econometric techniques. Based on a theoretical growth model as the data generating process, we find that, given a true speed of convergence of around 5%,...

General Method of Moments (GMM) estimation of a linear one-equation model using panel data with errors-in-variables is considered. To eliminate fixed individual heterogeneity, the equation is differenced across one or more than one periods and estimated by means of instrumental variables. With...

We consider a framework for analyzing panel data characterized by: (i) a system of regressions equations, (ii) random individual heterogeneity in both intercepts and slope coefficients, and (iii) unbalanced panel data, i.e., panel data where the individual time series have unequal length. A...

For a balanced panel data regression model with random effects, we discuss the efficiency of the GLS estimator relative to the OLS, the between, and the within estimators. Focus is on how the efficiency responds to changes in (a) the relative variance components and (b) the composition of the...

In this paper, we consider the formulation and estimation of systems of regression equations with random individual effects in the intercept terms from unbalanced panel data, i.e., panel data where the individual time series have unequal length. Generalized Least Squares (GLS) estimation and...

For a random effects regression model with unbalanced panel data, we demonstrate that the Generalized Least Squares (GLS) estimator can be expressed as a (matrix) weighted average of estimators which utilize the within individual and the between individual variation in the data set. We thus...

We propose theory-based Monte Carlo simulations to quantify the extent to which the estimated speed of convergence depends on the underlying econometric techniques. Based on a theoretical growth model as the data generating process, we find that, given a true speed of convergence of around 5%,...

General Method of Moments (GMM) estimation of a linear one-equation model using panel data with errors-in-variables is considered. To eliminate fixed individual heterogeneity, the equation is differenced across one or more than one periods and estimated by means of instrumental variables. With...