This paper proposes bias-adjusted normal approximation versions of Lagrange multiplier (NLM) test of error cross section independence of Breusch and Pagan (1980) in the case of panel models with strictly exogenous regressors and normal errors. The exact mean and variance of the Lagrange...

This argues for a closer link between the modelling of the long-run relations in applied economics and the intertemporal equilibrium notion from economic theory.

This paper proposes simple tests of error cross section dependence which are applicable to a variety of panel data models, including stationary and unit root dynamic heterogeneous panels with short T and large N. The proposed tests are based on average of pair-wise correlation coefficients of...

The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recent work by Pesaran (2006) suggests a method which makes use of cross-sectional averages to provide valid inference for stationary panel regressions with multifactor error...

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

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 presents a new approach to estimation and inference in panel data models with unobserved common factors possibly correlated with exogenously given individual-specific regressors and/or the observed common effects. The basic idea behind the proposed estimation procedure is to filter...

This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross section dependence. A popular method for modelling such dependence uses a factor error structure. Such models raise new problems for estimation and inference. This paper compares...

This paper takes a computationnaly simple LS approach to develop a more efficient estimation procedure, which we call Residual Augmented Least Square (RALS), than OLS when the errors are not normally distributed. The efficiency gain is from manipulating the higher moment conditions implied by...

This paper considers testing the hypothesis that errors in a panel data model are weakly cross sectionally dependent, using the exponent of cross-sectional dependence <img src="http://www.econ.cam.ac.uk/faculty/pesaran/wp12/image3.png" width="11" height="13" />, introduced recently in Bailey, Kapetanios and Pesaran (2012). It is shown that the implicit null of the <em>CD</em> test depends on the...