MULTIDIMENSIONAL MEASUREMENT OF ECONOMIC INEQUALITY, FOOD SECURITY AND SOCIAL INCLUSION: AN APPROACH BASED ON PRINCIPAL COMPONENT ANALYSIS

Abstract

Economic inequality, food insecurity and social exclusion represent interrelated challenges to sustainable development. This study proposes a comprehensive methodological approach based on Principal Component Analysis (PCA) to build a multidimensional index that allows these problems to be measured together. Data from national surveys and socioeconomic indicators from 2023 in Latin America were used. The results show that it is possible to synthesize multiple dimensions into components that explain more than 75% of the total variance, allowing regions to be classified according to their multidimensional vulnerability. This analytical tool can guide targeted and efficient public policies in contexts of high structural inequality.