Del concepto de crecimiento económico al de desarrollo de las naciones: una aplicación a la Unión Europea
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Abstract
En este trabajo se revisan los atributos y variables que caracterizan el desarrollo
en países de elevado nivel de riqueza (UE25). Se analiza la relación
entre su posición en términos de riqueza material y la derivada de distintas
estimaciones de índices sintéticos de desarrollo social (IDS).
Para ello se utilizan, en primer lugar, los indicadores estimados por el
PNUD. A continuación recurrimos a estimadores complementarios mediante
la propia metodología PNUD y métodos estadísticos multivariantes y de distancias
(análisis factorial y distancia P2). Los resultados obtenidos permiten
identificar qué países transforman mejor (o peor) el crecimiento económico en
desarrollo social, así como detectar qué dimensiones o variables del desarrollo
son las responsables de los cambios de posición en los diversos rankings
In this paper, the attributes and variables that characterize the development of rich countries (EU25) are reviewed. The relationship between the wealth levels and some estimates using synthetic indices of social development is analyzed (SDI). For this purpose, we firstly use the indicators estimated by UNDP. Afterwards, we turn to complementary estimators using UNDP methodology and multivariate statistical methods (factor analysis and distance P2). The results allow us to identify which countries do better (or worse) at turning economic growth into social development. They also contribute to detecting/ identifying the dimensions of development that are responsible for the changes in positions in several rankings
In this paper, the attributes and variables that characterize the development of rich countries (EU25) are reviewed. The relationship between the wealth levels and some estimates using synthetic indices of social development is analyzed (SDI). For this purpose, we firstly use the indicators estimated by UNDP. Afterwards, we turn to complementary estimators using UNDP methodology and multivariate statistical methods (factor analysis and distance P2). The results allow us to identify which countries do better (or worse) at turning economic growth into social development. They also contribute to detecting/ identifying the dimensions of development that are responsible for the changes in positions in several rankings







