Intra-distribution dynamics of regional per-capita income in Europe: evidence from alternative conditional density estimators

This paper compares different conditional density stimators to analyze the cross-sectional distribution dynamics of regional per-capita incomes in Europe during the period 1980-2002. First, a kernel estimator with fixed bandwidth (the method traditionally applied in the literature on intra-distribution dynamics) gives evidence of convergence. With a modified estimator with variable bandwidth and mean-bias correction, the dominant income dynamics is that of persistence and lack of cohesion: only a fraction of very poor regions improves its position over time converging towards a low relative income (“poverty trap”). An alternative graphical technique (more informative than the traditional contour plot) is also proposed to visualize conditional densities. Finally, a first-order spatial autoregressive model is applied to estimate the effect of spatial dependence on the evolution of income distribution.