Uncovering Nuanced Poverty Differences Through Spatial Analysis: Insights From Colombia's Pacific Region Academic Article in Scopus uri icon

abstract

  • Sustainable development spans health, education, economic stability, and access to essential infrastructure, such as electricity, water, and transportation. In marginalized rural communities, all these dimensions appear equally urgent, masking the nuanced differences in needs that are shaped by geographic location. Generalized policies often fail to address these variations, perpetuating disparities and limiting the effectiveness of interventions. This study examines Colombia's Pacific Coast, a region marked by high poverty levels and severe infrastructure deficits, where rural communities face pronounced but varied development challenges. Using spatial analysis techniques¿Global Moran's I, Getis-Ord (Formula presented.) statistic, and Ward-type hierarchical clustering¿this study uncovers significant spatial disparities, identifying five distinct development clusters. Communities in the most isolated areas face acute deprivation, with poverty rates exceeding 50% and severe deficiencies in electricity, water, and transportation access. Conversely, regions closer to urban centers and transport corridors exhibit better socio-economic conditions, including lower poverty and illiteracy rates. Notably, school non-attendance presents a distinct spatial pattern, worsening in economically active areas due to higher opportunity costs for youth. This research addresses a critical gap by providing a spatial framework to identify and interpret these nuanced differences, offering actionable insights for targeted interventions. Tailored investments in infrastructure, education, and economic initiatives can address the specific needs of each cluster, promoting more effective resource allocation and fostering equitable and sustainable development. This approach contributes to global efforts to design place-based strategies for marginalized rural communities, particularly in geographically isolated areas. © 2025 ERP Environment and John Wiley & Sons Ltd.

publication date

  • January 1, 2026