This paper, using the Bewley (1979) transformation of the autoregressive distributed lag model, proposes a novel pooled Bewley (PB) estimator of long-run coefficients for dynamic panels with heterogeneous short-run dynamics, in the same setting as the widely used Pooled Mean Group (PMG)...

This paper provides a new methodology for the analysis of multiple long run relations in panel data models where the cross section dimension, n, is large relative to the time series dimension, T. For panel data models with large n researchers have focussed on panels with a single long run...

This paper proposes a structural econometric approach to estimating the basic reproduction number (R0) of Covid-19. This approach identifies R0 in a panel regression model by filtering out the effects of mitigating factors on disease diffusion and is easy to implement. We apply the method to...

This paper considers testing the hypothesis that errors in a panel data model are weakly Cross-sectionally dependent (CD), using the exponent of cross-sectional dependence introduced recently in Bailey, Kapetanios and Pesaran (2012). It is shown that the implicit null of the CD test depends on...

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

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 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 testing the hypothesis that errors in a panel data model are weakly cross sectionally dependent, using the exponent of cross-sectional dependence α, introduced recently in Bailey, Kapetanios and Pesaran (2012). It is shown that the implicit null of the CD test depends on...

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