approach can be applied to estimation of a variety of models such as spatial and dynamic panel data models. In this paper we … focus on the latter and consider both univariate and multivariate panel data models with short time dimension. Simple Bias …

This paper considers a class of GMM estimators for general dynamic panel models, allowing for cross sectional …

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

This paper extends the Common Correlated Effects (CCE) approach developed by Pesaran (2006) to heterogeneous panel data … cross section averages must be included in individual equations of the panel, and the number of cross section averages must … dimension of the panel is sufficiently large. …

This paper provides an overview of the recent literature on estimation and inference in large panel data models with … cross-sectional dependence. It reviews panel data models with strictly exogenous regressors as well as dynamic models with …-sectional dependence. It considers a number of alternative estimators for static and dynamic panel data models, distinguishing between …

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

This paper proposes a quantile regression estimator for a heterogeneous panel model with lagged dependent variables and … the time series dimension of the panel is large. We present an application to the evaluation of Time-of-Use pricing using …

This paper considers testing the hypothesis that errors in a panel data model are weakly Cross-sectionally dependent … panel contains lagged values of the dependent variables, so long as there are no major asymmetries in the error distribution …. -- exponent of cross-sectional dependence ; diagnostic tests ; panel data models ; dynamic heterogenous panels …

This paper presents a new approach to estimation and inference in panel data models with unobserved common factors …