Greece and Its Regions: Exploring Spatial Patterns and Their Similarity Across Socio-Economic Indicators

Techniques for the analysis of spatial data have advanced rapidly over the recent years, allowing new insights to be gained about the distribution and inter-connectedness of socio-demographic and economic outcomes across space. With the advancement of spatial econometrics a large empirical literature has developed exploring a number of traditional economic questions within a new, spatial economics context that identifies specific spatial dynamics in the determination of economic and other outcomes. Despite such advances, however, relatively little effort has been placed in exploring how –and why– such spatial dynamics vary across variables, i.e., how/why spatial dynamics differ across a range of socio-economic indicators within a given geography. For example, if high-education employment is associated with above-average wage growth, is it also true that spatial clusters of wage growth overlap with spatial clusters of high-education employment? And if not, what does this imply for the substantive relation between education and growth? The purpose of this paper is to provide a first approach towards such a comparative analysis of spatial patterns of association at the prefecture level for Greece. We perform an extensive exploratory spatial data analysis (ESDA) for a range of demographic, social, economic, and labour market indicators and identify variable-specific spatial patterns of association (dependence, competition, clustering). Following, we utilise a number of alternative techniques –including econometric (co-movement), statistical (randomness / independence) and GIS (map comparison statistics)– in an attempt to link the information gathered in the first step and thus identify more ‘universal’ spatial patterns (i.e., ones applying to a wider selection of socio-economic variables). The analysis has obvious implications for Greek economic and regional policy. The identification of ‘universal’ spatial linkages (across a set of indicators) for the Greek regions can help understand better the spatial dynamics that characterise and link the sub-regional economies of the country, enabling the design in the future of more informed, focused, and effective territorial policies. More importantly, however, the analysis of this study is of particular interest also for applied spatial analysts, as it elaborates on the method of ESDA and highlights new areas of research in the field.