The aim of this paper is to develop subjective synthetic indicators that quantify the quality of life in the different countries of the EU-28, with data from the 2016 European Quality of Life Survey (EQLS). We add other indicators to the general synthetic ones in order to quantify the different dimensions of quality life due to its multidimensional nature. The successive but unchained application of the principal component analysis and the Mazziota-Pareto analysis allows us to classify 5 dimensions of quality of life: subjective component of governance, public services, environment, general satisfaction with life, and socioeconomic issues. We verify that countries with the lowest or highest positions in the general index usually keep that position in most dimensions. The spatial perspective is fundamental to study of regional development. For this reason, the next objective is the analysis of differences by spatial location using the variance analysis. The general indicator shows significant differences between EU countries but it does not show differences in the quality of life of European citizens in urban and rural areas.
Ya que no es lo mismo «ser pobre» que «sentirse pobre», el objetivo es el tratamiento subjetivo de la pobreza mediante las líneas de Kapteyn y Deeleck, así como la obtención de indicadores (subjetivos y objetivos) calculados para los diferentes tamaños del hogar y en función de la densidad poblacional; todo ello a partir de la Encuesta de Condiciones de Vida (ECV) en España para los años 2008, 2012 y 2016. Concluimos que los hogares que se sienten pobres son más numerosos que aquellos que lo son, debido a la sobreestimación de las tasas subjetivas de Kapteyn y Deeleck. Obtuvimos umbrales de pobreza subjetiva similares para los tamaños de hogar más frecuentes. Los hogares son y se sienten menos pobres en las zonas o áreas geográficas más densamente pobladas.
This paper studies the quality of life in the EU-28 from a multidimensional perspective that reflects what they feel and what European citizens really have, using data from the European Quality of Life Survey (EQLS) for the year 2016. After a selection of both subjective indicators (satisfactions of a social nature) and variables of economic type, we constructed by means of a sequential application of two different grouping methods (analysis of main components and Mazziotta-Pareto indicator) composite indicators. These synthetic indicators allow to establish differences between the countries analyzing the quality of life from two different approaches (subjective and economic), resulting to be highly correlated. In addition, it is concluded that the countries of the north and of Western Europe have a higher quality of life than those of the south and east of the EU.
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