Income Distribution Dynamics and Cross-Region Convergence in Europe. Spatial filtering and novel stochastic kernel representations

This paper suggests an empirical framework for analysing income distribution
dynamics and cross-region convergence in the European Union of 27 member states, 1995-
2003. The framework lies in the research tradition that allows the state income space to be
continuous, puts emphasis on both shape and intra-distribution dynamics and uses stochastic
kernels for studying transition dynamics and implied long-run behaviour. In this paper
stochastic kernels are described by conditional density functions, estimated by a product
kernel estimator of conditional density and represented by means of novel visualisation tools.
The technique of spatial filtering is used to account for spatial effects, in order to avoid
misguided inferences and interpretations caused by the presence of spatial autocorrelation in
the income distributions. The results reveal a slow catching-up of the poorest regions and a
process of polarisation, with a small group of very rich regions shifting away from the rest of
the cross-section. This is well evidenced by both, the unfiltered and the filtered ergodic
density view. Differences exist in detail, and these emphasise the importance to properly deal
with the spatial autocorrelation problem. (authors' abstract)