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Abstract

This mapping approach aims to make the marginalized and poor visible by identifying areas with difficult biophysical and socio-economic conditions. Mapping using different data sources and data types gives deeper insight into possible causal interlinkages and offers the opportunity for comprehensive analysis. The maps highlight areas where different dimensions of marginality overlap – the marginality hotspots – based on proxies for marginality dimensions representing different spheres of life. Furthermore, overlaying the marginality hotspots with the number of poor shows where most of the poor could be reached to help them to escape the spiral of poverty. Marginality hotspots can be found in particular in India and Nepal as well as in several countries in Central and Eastern Africa, such as Eritrea, Mozambique, Central African Republic, the Democratic Republic of Congo, Northern Sudan and large parts of Niger. Maps showing the overlap between marginality and poverty highlight that the largest number of marginalized poor are located in India and Bangladesh, as well as in Ethiopia, Southeastern Africa and some parts of Western Africa.

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