Mapping the geographical electoral particularities. Case study: European Parliamentary elections (1979-2009) and National Legislative elections in Europe (1991-2010).

摘要

This paper aims to highlight several mapping methods for the elections within European territory, whether for the European Parliament or national parliamentary polls. Gene rally, the spatial perspectives are given at NUTS 2 level or their equivalent for the countries that are not EU member states. The statistical databases used regarding the elections for the European Parliament were Eurostat's Annual Statistics Books for the years previous to 1989, the European Parliament's website for the following years and also the websites of the na tional election authorities. For the national parliamentary elections, the data sources were the national election authorities, the Social Sc ience Data Services (NSD), Oslo, www.electoralgeography.com we bsite and also the paper Elections in Europe: A data handbook, published by Nohlen and Stover in 2010. The purpose of the study is to emphas ize particularities of the European electoral geography for the national elections registered after the Fall of the Iron Curtain (1991-2010). The data for national parliamentary polls were processed for five-year election peri ods: 1991-1995, 1996-2000, 2001-2005 and 2006-2010. This method was used in order to analyze the regions of each European country in the same election cycle but also to offer a comparison between all election peri ods. The data were processed in Microsoft Excel and then used in di fferent methods of mapping: graduated circles, thematic maps, hierarchical ascendant classification, principal component analysis and/or spatial distribution coefficients. Using several mapping methods allows observing the geographical features of the election process like the lower (gradually) turnou ts in European Pa rliament and also in national general elections or the electors' diversification of political options (especially in the East part of the continent after the fall of the communist regime). The combination between principal component analysis and hierarchical ascendant classification emphasized another conclusion of the study related to the correlations existent between the indicated variables (low turnouts and variation of political choices) and different social, demographic and/or economic indicators like population density, share of urban population, GDP per capita in PPS, employment rate, professional structure of the population, unemployment rate, etc.).