Marcella D'Uva

Club convergence in European regions

This study investigates the ‘club convergence’ hypothesis applying the stochastic notion of convergence to groups of European regions. In order to avoid the group selection bias problem, the innovative regression tree technique was applied to select endogenously the most important variables in achieving the best identification of groups on the base of per capita income and productive specialization. Tests on stochastic convergence in each group evidences a strong convergence among the wealthiest regions of the European Union and a trend of weak convergence among the remaining groups, confirming Baumols hypothesis of convergence.

Time series approaches to Italian regional convergence

This article investigates the evolution of the gap between Italian regions and Italy as a whole during the period of 1980 to 2007. We tested for the presence of the stochastic and β-convergence hypotheses using different time series approaches. The former was studied, first, for the entire sample period and then, with an exogenous instantaneous break in the series. The presence of β-convergence, instead, was estimated considering a known and an unknown trend break date model. Our results show that most of the regions do not converge in an ‘actual’ way, since they do not present a stochastic and β-convergence simultaneously.