Regional Migration in Europe from a Network Perspective

This study analyzes patterns of intra-country regional migration in Europe. Using network analysis, we study structures and properties of interregional migration networks, their similarities and diversity across the countries, and their evolution over time. Despite a wide spread of theoretical literature on the location choice of individuals, there is still a deficiency of empirical studies. The new economic geography models stress a strong effect of an access to a market on individuals’ migration choices (Krugman 1991). Many studies have shown that the labor migration between regions is related to market potentials of these regions and a real wage disparity between them. However, some recent empirical investigations based on a number of European countries show an insignificant effect of expected wages in receiving regions on agent’s decision to migrate there (Crozet 2004), while in other countries a wealth improvement is a core attractive force for migration decisions. This study attempts to recognize differences in a formation of regional migration flows among countries through a network perspective. We check a hypothesis about a bell-shaped relationship of spatial distribution of economic activity (Tabuchi, Thisse 2002). The hypothesis supposes that a technology improvement in developing countries accelerates agglomeration forces as individuals are looking for a better economic wellbeing, whereas in more developed regions, non-economic characteristics of regions are more important for migrants. In this way we expect to find considerable differences in formation of regional migration between “old” (developed) and “new” (post-soviet) European countries. In particular, our main hypothesis is that “new” (post-soviet) European countries, where industrial forces are more rapid, exhibit strongest core-periphery structures of regional migration rather than “old” (developed) European countries, those are already industrialized, and growth is stable. These distinctions could be identified through a comprehensive network analysis. Although migration flows could be perfectly represented as a network, only a few studies have tried to analyze patterns of migration using a network perspective (Slater 2009, Fagiolo 2013, Davis 2013). Thus, topologies of migration networks as well as their evolution over time still remain poorly understood.