Space-time analysis of GDP disparities among European regions: A Markov chains approach

The purpose of this article is to study the evolution of GDP disparities among 138 European regions over the period from 1980 to 1995. Regional per capita GDP cross-sectional distribution is characterized by means of nonparametric estimations of density functions, and the growth process is modeled as a first-order stationary Markov chain. Spatial effects are then introduced within the Markov chain framework using regional conditioning and spatial Markov chains. The results of the analysis indicate the persistence of regional disparities, a progressive bias toward a poverty trap, and the importance of geography in the convergence process.