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

an application to the estimation of panel data models with an infinite number of weak factors and a finite number of … on the nature of the unobserved common effects. -- panels ; strong and weak cross section dependence ; weak and strong …

an application to the estimation of panel data models with an infinite number of weak factors and a finite number of … on the nature of the unobserved common effects. -- Panels ; strong and weak cross section dependence ; weak and strong …

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 …

We propose two types of equal predictive ability (EPA) tests with panels to compare the predictions made by two … over all panel units and over time. The second, called C-statistics, focuses on the clustered EPA hypothesis where the EPA … holds jointly for a fixed number of clusters of panel units. The asymptotic properties of the proposed tests are evaluated …

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 …

This paper provides an approach to estimation and inference for non-linear conditional mean panel data models, in the …

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 …