In this paper we discuss tests for residual cross section dependence in nonlinear panel data models. The tests are based on average pair-wise residual correlation coefficients. In nonlinear models, the definition of the residual is ambiguous and we consider two approaches: deviations of the...

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and...

This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random coefficient models and suggest a common framework for dealing with them. It considers the fundamental issues of statistical inference of a random coefficients formulation using...

In this paper we discuss tests for residual cross section dependence in nonlinear panel data models. The tests are based on average pair-wise residual correlation coefficients. In nonlinear models, the definition of the residual is ambiguous and we consider two approaches: deviations of the...

In this paper we discuss tests for residual cross section dependence in nonlinear panel data models. The tests are based on average pair-wise residual correlation coefficients. In nonlinear models, the definition of the residual is ambiguous and we consider two approaches: deviations of the...

This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random coe.cients models and suggest a common framework for dealing with them. It considers the fundamental issues of statistical inference of a random coe.cients formulation using both...

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension is finite and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and shown to be...

This paper considers estimation and inference in panel vector autoregressions with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood estimator based on a transformed likelihood function is proposed and shown to be...