DEEP’s approach to SAE delivers accurate, granular and frequent poverty data – and helps governments respond more effectively to extreme poverty.

Decision makers often lack the information needed to understand how and where poverty is changing across a country. Household surveys typically provide data at regional level, without offering disaggregation for smaller areas. Remote and isolated households are often missed out completely.

DEEP’s Small Area Estimation (SAE) tool provides a powerful solution. It’s a statistical modelling technique that helps users combine household survey data with other external data sources to get a more granular understanding of poverty. By using geo-spatial satellite data, for instance, SAE can suggest the nature and impact of poverty in areas not covered by existing household surveys.