Regional Convergence in the European Union: A Stochastic Dominance Approach

Abstract

This article offers a new approach in assessing the presence of regional convergence in income per capita and applies it to data for sixty-five regions of the European Union over the decade leading up to the entry into force of the Maastricht Treaty. Within the framework of distributional dynamics analysis, the author proposes the use of quantitative techniques traditionally employed to inform investment decision making under uncertainty. After investigating the intradistributional dynamics with Markov chains, the author tests for regional convergence using secondorder stochastic dominance. For the sample and time horizon considered, the author finds evidence of regional convergence that is neither fast nor continuous. In other words, the regions in the sample display high persistence in belonging to a certain income group, while subperiods of convergence and divergence in income per capita are discernible. The approach proposed is grounded in economic theory, offers information about changes across the entire distribution, and can be adapted to incorporate location into the analysis.