Convergence in Per-capita GDP across European Regions using Panel Data Models Extended to Spatial Autocorrelation Effects

Abstract

This paper studies the convergence of per-capita GDP across European regions over a fairly long period. Most of the works in the field are based on either cross-sectional or fixed-effects estimates. We propose the estimation of convergence in per-capita GDP across European regions by making use of panel-data models extended to include spatial error autocorrelation (Anselin, 1988; Elhorst, 2003). This will allow us to extend the traditional beta-convergence model to include a rigorous treatment of the spatial correlation among the intercept terms. A spatial analysis of such intercept terms will also be performed in order to shed light on the concept of spatially conditional convergence.