• conditional convergence
• distribution dynamics
• nonparametric methods
• spatial effects

Since the beginning of the 1990s, the issue of income convergence has received considerable
attention in economic research. Although a vast number of empirical studies has
emerged, evidence on the role of spatial interaction is still rather scarce. For Italy, many
empirical studies based on cross-sectional regression have examined the pattern of growth
at regional level (NUTS2), showing wide differences in the level of output per worker (or
per capita) and slow convergence between poor and rich regions, in particular after the
mid-Seventies. In my dissertation I investigate the dynamics of the relative productivity for
Italian Provinces (NUTS3) over the period 1995-2006. On the basis of Solow’s model the
analysis firstly follows the methodology developed by Barro-Sala-i-Martin to test the presence
of β and σ convergence; then in order to overcome the traditional drawbacks about this
approach I present non parametric estimates. The parametric regression underlines the presence
of convergence, while the non parametric analysis shows across the Italian Provinces
a polarization of provinces between two clusters. This evidence is further investigated by
an intra-cluster analysis which highlights the potential explanatory factors of such pattern.
Then, I assess the importance of spatial effects across provinces and describe a class of spatial
statistical methods used in the empirical analysis to individuate the implications of spatial
interaction effects.