This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random …-sectional dependence in panel data models. …

This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random … models, and the more recent developments in the area of cross-sectional dependence in panel data models. …

This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random ….cient models, and the more recent developments in the area of cross-sectional dependence in panel data models. …

This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random … models, and the more recent developments in the area of cross-sectional dependence in panel data models. …

This paper proposes simple tests of error cross section dependence which are applicable to a variety of panel data … based on average of pair-wise correlation coefficients of the OLS residuals from the individual regressions in the panel … the theory, quite robust to the presence of unit roots and structural breaks. The use of the CD test is illustrated by …

The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models … for stationary panel regressions with multifactor error structure. This paper extends this work and examines the important …

This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross …

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

This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross …

The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models … for stationary panel regressions with multifactor error structure. This paper extends this work and examines the important …