A Progressive Approach to the Measurement of Regional Performance in the European Union

Abstract

With a view to promote the European Union (EU) overall harmonious development, the EU Regional Policy –or Cohesion Policy- focuses on reducing disparities between the levels of development of the various regions and the backwardness of the least favoured regions. Structural Funds, the main instrument to achieve the EU Regional Policy objectives, are allocated by regional Gross Domestic Product (GDP) per capita. Furthermore, in the EU context, the socio-economic inequalities between both people and regions have been rising in the majority of Member States over the last three decades and are now higher than in 1980 regardless of consistent objectives for economic and social cohesion (Eurostat). This separation between economy and society could be potentially overcome by including a measure of social well-being in models of regional performance. However, and despite economic and social cohesion being core EU objectives since its foundation, the community regional performance is defined in a strict economic sense by the size and growth of the economy. Regions whose per capita income falls short off the threshold of the 75% of the EU average GDP per capita are less developed regions, and are thus eligible for Structural Funds support. The aim of this paper is to present a multidimensional approach to the measurement of regional performance as an alternative to a single criterion approach based on the GDP per capita. With this in mind: 1st. Drawing on the capabilities approach and the recent trends in well-being (i.e. Stiglitz-Sen-Fitoussi Report of 2009), we discuss the reasons that justify the revision of the current allocation mechanism of EU Structural Funds. 2nd. We develop a composite index to measure regional performance in the 269 regions of EU28 in 2009 from a multidimensional perspective (16 indicators of health, education, employment, inequalities, poverty, etc.) following two distinct multivariate methods (Principal Component Analysis and Distance P2). 3rd. We discuss some regional policy implications of a change in the rules. That is, we analyse the consequences of applying a multidimensional approach instead of the traditional GDP based allocation mechanism. We find that, with an equivalent budgetary effort regarding the population benefited from these funds, a distinct map of priority regions results. Based upon the indicators considered, Stockholm in Sweden is the most developed region with a development level that triples that achieved by the least developed region (Severozapaden in Bulgaria). Hence large territorial disparities exist. Employment (female and male) related aspects and GDP per capita adjusted by inequality are the key determining factors of regional development. Were the Structural Funds allocated by our regional development index instead of the GDP per capita, some regions of Belgium, France, Greece, Germany, Italy and Spain would be considered priority regions; whereas some other regions, mainly from Eastern Europe, would not be considered so.