an application to the estimation of panel data models with an infinite number of weak factors and a finite number of …

In this paper we propose a general approach for estimating stochastic frontier mod- els, suitable when using long panel … large, cross sectionally correlated, non-stationary panel data models to estimate the frontier function. Given the long time … span of the panel, we investigate whether the variables, including the unobservable common factors, are non-stationary, and …

This paper considers the statistical analysis of large panel data sets where even after condi-tioning on common … dependence. It is then established that the Common Correlated Effects (CCE) estimator of panel data model with a multifactor …

This paper proposes a new panel model of cross-sectional dependence. The model has a number of potential structural … approach to the modelling of interactions across panel units and can generate endogenous cross-sectional dependence that can …

panel data methods that allow one to account for unobserved heterogeneity, temporal persistence, and crosssection dependence …

This paper considers the statistical analysis of large panel data sets where even after conditioning on common observed … dependence. It is then established that the Common Correlated Effects (CCE) estimator of panel data model with a multifactor …

This paper proposes maximum likelihood estimators for panel seemingly unrelated regressions with both spatial lag and … spatial lag dependent variable and where the heterogeneity in the panel is incorporated via an error component specification … spatial autocorrelation and random effects for this spatial SUR panel model. The small sample performance of the proposed …

I consider a panel vector-autoregressive model with cross-sectional dependence of the disturbances characterized by a … transformed data and applies standard techniques for estimation of panel vector-autoregressive models. I compare the small …