Polycentricity and Social Services of General Interest: A Multivariate Analysis - Pedro Palma; Daniel Rauhut; Alois Humer (European Regional Science Association (ERSA), 2015)
The aim of this study is to discuss the impact of polycentric structures and other regional patterns on the provision of Social Services of General Interest (SSGI). Polycentricity has been a favoured spatial pattern of EU policies since the European Spatial Development Perspective ESDP 1999 which is promoted alongside efficient and resilient spatial structuring for socio-economic activities. The objective of a polycentric development was also taken further in the debate about European territorial cohesion policy (Faludi, 2006; Council of the European Union, 2006), being considered a key element to achieve territorial cohesion (Territorial Agenda, 2011). The theoretical background on SSGI provision builds upon the elaborations of ESPON/SeGI project (Rauhut et al. 2013) that defines SSGI as an open, normative EU policy field, nevertheless linked to national understandings of public services (Bjørnsen et al. 2013). First attempts of discussing the influence of polycentricity on SSGI provision have been made by Borges and Johansson (2013). In this study, the analysis shall be carried forward by using the single SSGI indicators as well as calculated SSGI indices by Humer and Palma (2013) as the dependent variables in a set of multivariate regression analyses. A multivariate cross-section OLS regression model will be used to estimate the relative impact of polycentricity on our dependent variables which is the provision of educational and health care SSGI in EU and EFTA countries. Besides a polycentricity index provided by ESPON, further explanatory/ independent variables about population densities, settlement structures as well as macro-economic indicators will help in the regression model to decipher the impact of polycentricity. An additional space-sensitive step is included by running the regression model for various dependent variables (i.e. SSGI of educational and health care sectors) of different centrality scales. We expect to see different importance of polycentricity according to the range and frequency of usage of certain services such as for instance primary schooling (local centrality), hospitals (regional centrality) or universities (supra-regional centrality) The chosen method enables to control for a subset of explanatory variables and examine the effect of selected independent variables when estimating the impact of polycentricity to the provision of SSGI. This study uses Eurostat and ESPON data.
Keywords: R12; I31; H41; 330; services of general interest; polycentricity; centrality; multivariate regression