Spatial clustering of rural poverty and food insecurity in Sri Lanka

Abstract

We mapped poverty, with reference to a nutrition-based poverty line, to analyse its spatial clustering in Sri Lanka. We used the Divisional Secretariat poverty map, derived by combining the principal component analysis and the synthetic small area estimation technique, as the data source. Two statistically significant clusters appear. One cluster indicates that low poverty rural areas cluster around a few low poverty urban areas, where low agricultural employment and better access to roads are key characteristics. The other indicates a cluster of high poverty rural areas, where agriculture is the dominant economic activity, and where spatial clustering is associated with factors influencing agricultural production. Agricultural smallholdings are positively associated with spatial clustering of poor rural areas. In areas where water availability is low, better access to irrigation significantly reduces poverty. Finally, we discuss the use of poverty mapping for effective policy formulation and interventions for alleviating poverty and food insecurity.