Application of factorial analysis to a Brazilian metropolitan region considering the Millennium Development Goals
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The Millennium Development Goals (MDGs) were established by the United Nations (UN) in an attempt to mitigate environmental and economic distortions that exist worldwide. To identify opportunities to meet the aspirations of the MDGs, a few indicators (as Human Development-HDI-and the Gini indexes) were used in order to demonstrate existing inequalities among populations. This approach is also present in studies of such nature, in which electric energy intensity has been proposed as a way of overcoming the limitations of energy use assessment and its relationship with economic growth by means of the gross domestic product, seeking to impart evidence that can explain the environmental indexes more substantially. This article uses the factor analysis, a multivariate statistical analysis, to indicate the most closely correlated characteristics to the paths of human dignity and sustainable energy use. The aim of such analysis is to characterize regions and their clusters of typically urban cities to subsidize decision makers in the changes for the present and future populations of these cities. The chosen cities for this study are located in the Metropolitan Region of Paraiba Valley and Northern Coast (MRPV), at an economic hub represented by the cities of Sao Paulo and Rio de Janeiro, with historic features often associated with their economic development. However, social choices, the cultural background in the region and geographical limitations represented by the Serra da Mantiqueira and Serra do Mar have defined peculiar characteristics to the region. The contribution of using electric energy to the development of positive actions towards the MDGs when coupled with the provision of benefits to less favored populations, as well as the autonomy suggested by the results to women, a reduction of the proliferation of diseases and extreme poverty, among other aspects, were achieved with the proposed analysis. (C) 2015 Elsevier Ltd. All rights reserved.